Computer Science Computer Networks and Communications

Cognitive Radio Networks and Spectrum Sensing

Description

This cluster of papers focuses on cognitive radio networks, spectrum sensing, dynamic spectrum access, cooperative sensing, and opportunistic spectrum access. It covers topics such as spectrum sharing, MAC protocols, security threats, and game theory in the context of cognitive radio and wireless networks.

Keywords

Cognitive Radio; Spectrum Sensing; Dynamic Spectrum Access; Cooperative Sensing; Opportunistic Spectrum Access; Wireless Networks; Spectrum Sharing; MAC Protocols; Security Threats; Game Theory

The public mobile radio spectrum has become a scarce resource while wide spectral ranges are only rarely used. Here, the new strategy called spectrum pooling is considered. It aims at … The public mobile radio spectrum has become a scarce resource while wide spectral ranges are only rarely used. Here, the new strategy called spectrum pooling is considered. It aims at enabling public access to these spectral ranges without sacrificing the transmission quality of the actual license owners. Unfortunately, using OFDM modulation in a spectrum pooling system has some drawbacks. There is an interaction between the licensed system and the OFDM based rental system due to the non-orthogonality of their respective transmit signals. This interaction is described mathematically, providing a quantitative evaluation of the mutual interference that leads to an SNR loss in both systems. However, this interference can be mitigated by windowing the OFDM signal in the time domain or by the adaptive deactivation of adjacent subcarriers providing flexible guard bands between licensed and rental system. It is obvious that both approaches sacrifice bandwidth of the rental system. A quantitative comparison of both approaches is given as a tradeoff between interference reduction and throughput in the rental system.
This article describes the technical challenges that have to be met when implementing the interesting new technology of spectrum pooling. This notion represents the coexistence of two mobile radio systems … This article describes the technical challenges that have to be met when implementing the interesting new technology of spectrum pooling. This notion represents the coexistence of two mobile radio systems within the same frequency range. It enables the secondary utilization of already licensed frequency bands as aimed at by several regulatory authorities worldwide. The goal of spectrum pooling is to enhance spectral efficiency by overlaying a new mobile radio system on an existing one without requiring any changes to the actual licensed system. Several demanding tasks originate from this idea. Some of them have been solved in recent research projects. Others are subject to ongoing investigations. Here, the state of the art in spectrum pooling is presented.
This letter addresses the problem of energy detection of an unknown signal over a multipath channel. It starts with the no-diversity case, and presents some alternative closed-form expressions for the … This letter addresses the problem of energy detection of an unknown signal over a multipath channel. It starts with the no-diversity case, and presents some alternative closed-form expressions for the probability of detection to those recently reported in the literature. Detection capability is boosted by implementing both square-law combining and square-law selection diversity schemes
Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is … Cognitive radio has emerged as one of the most promising candidate solutions to improve spectrum utilization in next generation cellular networks. A crucial requirement for future cognitive radio networks is wideband spectrum sensing: secondary users reliably detect spectral opportunities across a wide frequency range. In this article, various wideband spectrum sensing algorithms are presented, together with a discussion of the pros and cons of each algorithm and the challenging issues. Special attention is paid to the use of sub-Nyquist techniques, including compressive sensing and multichannel sub- Nyquist sampling techniques.
Cognitive radio networks will provide high bandwidth to mobile users via heterogeneous wireless architectures and dynamic spectrum access techniques. However, CR networks impose challenges due to the fluctuating nature of … Cognitive radio networks will provide high bandwidth to mobile users via heterogeneous wireless architectures and dynamic spectrum access techniques. However, CR networks impose challenges due to the fluctuating nature of the available spectrum, as well as the diverse QoS requirements of various applications. Spectrum management functions can address these challenges for the realization of this new network paradigm. To provide a better understanding of CR networks, this article presents recent developments and open research issues in spectrum management in CR networks. More specifically, the discussion is focused on the development of CR networks that require no modification of existing networks. First, a brief overview of cognitive radio and the CR network architecture is provided. Then four main challenges of spectrum management are discussed: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility.
Cognitive radio is widely expected to be the next Big Bang in wireless communications. Spectrum sensing, that is, detecting the presence of the primary users in a licensed spectrum, is … Cognitive radio is widely expected to be the next Big Bang in wireless communications. Spectrum sensing, that is, detecting the presence of the primary users in a licensed spectrum, is a fundamental problem for cognitive radio. As a result, spectrum sensing has reborn as a very active research area in recent years despite its long history. In this paper, spectrum sensing techniques from the optimal likelihood ratio test to energy detection, matched filtering detection, cyclostationary detection, eigenvalue-based sensing, joint space-time sensing, and robust sensing methods are reviewed. Cooperative spectrum sensing with multiple receivers is also discussed. Special attention is paid to sensing methods that need little prior information on the source signal and the propagation channel. Practical challenges such as noise power uncertainty are discussed and possible solutions are provided. Theoretical analysis on the test statistic distribution and threshold setting is also investigated.
Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is … Cognitive radio is viewed as a novel approach for improving the utilization of a precious natural resource: the radio electromagnetic spectrum. The cognitive radio, built on a software-defined radio, is defined as an intelligent wireless communication system that is aware of its environment and uses the methodology of understanding-by-building to learn from the environment and adapt to statistical variations in the input stimuli, with two primary objectives in mind: /spl middot/ highly reliable communication whenever and wherever needed; /spl middot/ efficient utilization of the radio spectrum. Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks. 1) Radio-scene analysis. 2) Channel-state estimation and predictive modeling. 3) Transmit-power control and dynamic spectrum management. This work also discusses the emergent behavior of cognitive radio.
In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum … In a cognitive radio network, the secondary users are allowed to utilize the frequency bands of primary users when these bands are not currently being used. To support this spectrum reuse functionality, the secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance in cognitive radio networks. There are two parameters associated with spectrum sensing: probability of detection and probability of false alarm. The higher the probability of detection, the better the primary users are protected. However, from the secondary users' perspective, the lower the probability of false alarm, the more chances the channel can be reused when it is available, thus the higher the achievable throughput for the secondary network. In this paper, we study the problem of designing the sensing duration to maximize the achievable throughput for the secondary network under the constraint that the primary users are sufficiently protected. We formulate the sensing-throughput tradeoff problem mathematically, and use energy detection sensing scheme to prove that the formulated problem indeed has one optimal sensing time which yields the highest throughput for the secondary network. Cooperative sensing using multiple mini-slots or multiple secondary users are also studied using the methodology proposed in this paper. Computer simulations have shown that for a 6 MHz channel, when the frame duration is 100 ms, and the signal-to-noise ratio of primary user at the secondary receiver is -20 dB, the optimal sensing time achieving the highest throughput while maintaining 90% detection probability is 14.2 ms. This optimal sensing time decreases when distributed spectrum sensing is applied.
Dynamic spectrum access stands as a promising and spectrum-efficient communication approach for resource-constrained multihop wireless sensor networks due to their event-driven communication nature, which generally yields bursty traffic depending on … Dynamic spectrum access stands as a promising and spectrum-efficient communication approach for resource-constrained multihop wireless sensor networks due to their event-driven communication nature, which generally yields bursty traffic depending on the event characteristics. In addition, opportunistic spectrum access may also help realize the deployment of multiple overlaid sensor networks, and eliminate collision and excessive contention delay incurred by dense node deployment. Incorporating cognitive radio capability in sensor networks yields a new sensor networking paradigm (i.e., cognitive radio sensor networks). In this article the main design principles, potential advantages, application areas, and network architectures of CRSNs are introduced. The existing communication protocols and algorithms devised for cognitive radio networks and WSNs are discussed along with the open research avenues for the realization of CRSNs.
The ever-increasing demand for higher data rates in wireless communications in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio. Traditionally, licensed spectrum is … The ever-increasing demand for higher data rates in wireless communications in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio. Traditionally, licensed spectrum is allocated over relatively long time periods and is intended to be used only by licensees. Various measurements of spectrum utilization have shown substantial unused resources in frequency, time, and space [1], [2]. The concept behind cognitive radio is to exploit these underutilized spectral resources by reusing unused spectrum in an opportunistic manner [3], [4]. The phrase cognitive radio is usually attributed to Mitola [4], but the idea of using learning and sensing machines to probe the radio spectrum was envisioned several decades earlier (cf., [5]).
The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this … The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.
We consider cooperative spectrum sensing in which multiple cognitive radios collaboratively detect the spectrum holes through energy detection and investigate the optimality of cooperative spectrum sensing with an aim to … We consider cooperative spectrum sensing in which multiple cognitive radios collaboratively detect the spectrum holes through energy detection and investigate the optimality of cooperative spectrum sensing with an aim to optimize the detection performance in an efficient and implementable way. We derive the optimal voting rule for any detector applied to cooperative spectrum sensing. We also optimize the detection threshold when energy detection is employed. Finally, we propose a fast spectrum sensing algorithm for a large network which requires fewer than the total number of cognitive radios in cooperative spectrum sensing while satisfying a given error bound.
Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access: the policy that addresses the spectrum scarcity problem that is encountered in many countries. Thus, CR is widely … Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access: the policy that addresses the spectrum scarcity problem that is encountered in many countries. Thus, CR is widely regarded as one of the most promising technologies for future wireless communications. To make radios and wireless networks truly cognitive, however, is by no means a simple task, and it requires collaborative effort from various research communities, including communications theory, networking engineering, signal processing, game theory, software–hardware joint design, and reconfigurable antenna and radio-frequency design. In this paper, we provide a systematic overview on CR networking and communications by looking at the key functions of the physical (PHY), medium access control (MAC), and network layers involved in a CR design and how these layers are crossly related. In particular, for the PHY layer, we will address signal processing techniques for spectrum sensing, cooperative spectrum sensing, and transceiver design for cognitive spectrum access. For the MAC layer, we review sensing scheduling schemes, sensing-access tradeoff design, spectrum-aware access MAC, and CR MAC protocols. In the network layer, cognitive radio network (CRN) tomography, spectrum-aware routing, and quality-of-service (QoS) control will be addressed. Emerging CRNs that are actively developed by various standardization committees and spectrum-sharing economics will also be reviewed. Finally, we point out several open questions and challenges that are related to the CRN design.
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy … <para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and to opportunistically use under-utilized frequency bands without causing harmful interference to legacy (primary) networks. In this paper, a novel wideband spectrum sensing technique referred to as <emphasis emphasistype="boldital">multiband joint detection</emphasis> is introduced, which jointly detects the primary signals over multiple frequency bands rather than over one band at a time. Specifically, the spectrum sensing problem is formulated as a class of optimization problems, which maximize the <emphasis emphasistype="boldital">aggregated opportunistic throughput</emphasis> of a cognitive radio system under some constraints on the interference to the primary users. By exploiting the hidden convexity in the seemingly nonconvex problems, optimal solutions can be obtained for multiband joint detection under practical conditions. The situation in which individual cognitive radios might not be able to reliably detect weak primary signals due to channel fading/shadowing is also considered. To address this issue by exploiting the spatial diversity, a cooperative wideband spectrum sensing scheme refereed to as <emphasis emphasistype="boldital">spatial-spectral joint detection</emphasis> is proposed, which is based on a linear combination of the local statistics from multiple spatially distributed cognitive radios. The cooperative sensing problem is also mapped into an optimization problem, for which suboptimal solutions can be obtained through mathematical transformation under conditions of practical interest. Simulation results show that the proposed spectrum sensing schemes can considerably improve system performance. This paper establishes useful principles for the design of distributed wideband spectrum sensing algorithms in cognitive radio networks. </para>
We define a cyclostationary signature as a feature which may be intentionally embedded in a digital communications signal, detected through cyclostationary analysis and used as a unique identifier. The purpose … We define a cyclostationary signature as a feature which may be intentionally embedded in a digital communications signal, detected through cyclostationary analysis and used as a unique identifier. The purpose of this paper is to demonstrate how cyclostationary signatures can be exploited to overcome a number of the challenges associated with network coordination in emerging cognitive radio applications and spectrum sharing regimes. In particular we show their uses for signal detection, network identification and rendezvous and discuss these in the context of dynamic spectrum access. We present a theoretical discussion followed by application-oriented examples of the cyclostationary signatures used in practical cognitive radio and dynamic spectrum usage scenarios. We focus on orthogonal frequency division multiplexing (OFDM) based systems and present an analysis of a transceiver implementation employing these techniques developed on a cognitive radio test platform.
Opportunistic unlicensed access to the (temporarily) unused frequency bands across the licensed radio spectrum is currently being investigated as a means to increase the efficiency of spectrum usage. Such opportunistic … Opportunistic unlicensed access to the (temporarily) unused frequency bands across the licensed radio spectrum is currently being investigated as a means to increase the efficiency of spectrum usage. Such opportunistic access calls for implementation of safeguards so that ongoing licensed operations are not compromised. Among different candidates, sensing-based access, where the unlicensed users transmit if they sense the licensed band to be free, is particularly appealing due to its low deployment cost and its compatibility with the legacy licensed systems. The ability to reliably and autonomously identify unused frequency bands is envisaged as one of the main functionalities of cognitive radios. In this article we provide an overview of the regulatory requirements and major challenges associated with the practical implementation of spectrum sensing functionality in cognitive radio systems. Furthermore, we outline different design trade-offs that have to be made in order to enhance various aspects of the system's performance.
Sensing/monitoring of spectrum-availability has been identified as a key requirement for dynamic spectrum allocation in cognitive radio networks (CRNs). An important issue associated with MAC-layer sensing in CRNs is how … Sensing/monitoring of spectrum-availability has been identified as a key requirement for dynamic spectrum allocation in cognitive radio networks (CRNs). An important issue associated with MAC-layer sensing in CRNs is how often to sense the availability of licensed channels and in which order to sense those channels. To resolve this issue, we address (1) how to maximize the discovery of spectrum opportunities by sensing-period adaptation and (2) how to minimize the delay in finding an available channel. Specifically, we develop a sensing-period optimization mechanism and an optimal channel-sequencing algorithm, as well as an environment- adaptive channel-usage pattern estimation method. Our simulation results demonstrate the efficacy of the proposed schemes and its significant performance improvement over nonoptimal schemes. The sensing-period optimization discovers more than 98 percent of the analytical maximum of discoverable spectrum-opportunities, regardless of the number of channels sensed. For the scenarios tested, the proposed scheme is shown to discover up to 22 percent more opportunities than nonoptimal schemes, which may become even greater with a proper choice of initial sensing periods. The idle-channel discovery delay with the optimal channel-sequencing technique ranges from 0.08 to 0.35 seconds under the tested scenarios, which is much faster than nonoptimal schemes. Moreover, our estimation method is shown to track time-varying channel-parameters accurately.
Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio.Since the statistical covariances of received signal and noise are usually … Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio.Since the statistical covariances of received signal and noise are usually different, they can be used to differentiate the case where the primary user's signal is present from the case where there is only noise.In this paper, spectrum sensing algorithms are proposed based on the sample covariance matrix calculated from a limited number of received signal samples.Two test statistics are then extracted from the sample covariance matrix.A decision on the signal presence is made by comparing the two test statistics.Theoretical analysis for the proposed algorithms is given.Detection probability and associated threshold are found based on statistical theory.The methods do not need any information of the signal, the channel and noise power a priori.Also, no synchronization is needed.Simulations based on narrowband signals, captured digital television (DTV) signals and multiple antenna signals are presented to verify the methods.
Cognitive Radio (CR) is a promising technology that can alleviate the spectrum shortage problem by enabling unlicensed users equipped with CRs to coexist with incumbent users in licensed spectrum bands … Cognitive Radio (CR) is a promising technology that can alleviate the spectrum shortage problem by enabling unlicensed users equipped with CRs to coexist with incumbent users in licensed spectrum bands while causing no interference to incumbent communications. Spectrum sensing is one of the essential mechanisms of CRs and its operational aspects are being investigated actively. However, the security aspects of spectrum sensing have garnered little attention. In this paper, we identify a threat to spectrum sensing, which we call the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">primary user emulation (PUE) attack</i> . In this attack, an adversary's CR transmits signals whose characteristics emulate those of incumbent signals. The highly flexible, software-based air interface of CRs makes such an attack possible. Our investigation shows that a PUE attack can severely interfere with the spectrum sensing process and significantly reduce the channel resources available to legitimate unlicensed users. To counter this threat, we propose a transmitter verification scheme, called <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LocDef (localization-based defense)</i> , which verifies whether a given signal is that of an incumbent transmitter by estimating its location and observing its signal characteristics. To estimate the location of the signal transmitter, LocDef employs a <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">non-interactive localization</i> scheme. Our security analysis and simulation results suggest that LocDef is effective in identifying PUE attacks under certain conditions.
We propose the cross-layer based opportunistic multi-channel medium access control (MAC) protocols, which integrate the spectrum sensing at physical (PHY) layer with the packet scheduling at MAC layer, for the … We propose the cross-layer based opportunistic multi-channel medium access control (MAC) protocols, which integrate the spectrum sensing at physical (PHY) layer with the packet scheduling at MAC layer, for the wireless ad hoc networks. Specifically, the MAC protocols enable the secondary users to identify and utilize the leftover frequency spectrum in a way that constrains the level of interference to the primary users. In our proposed protocols, each secondary user is equipped with two transceivers. One transceiver is tuned to the dedicated control channel, while the other is designed specifically as a cognitive radio that can periodically sense and dynamically use the identified un-used channels. To obtain the channel state accurately, we propose two collaborative channel spectrum-sensing policies, namely, the random sensing policy and the negotiation-based sensing policy, to help the MAC protocols detect the availability of leftover channels. Under the random sensing policy, each secondary user just randomly selects one of the channels for sensing. On the other hand, under the negotiation-based sensing policy, different secondary users attempt to select the distinct channels to sense by overhearing the control packets over the control channel. We develop the Markov chain model and the M/G <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Y</sup> /1-based queueing model to characterize the performance of our proposed multi-channel MAC protocols under the two types of channel-sensing policies for the saturation network and the non-saturation network scenarios, respectively. In the non-saturation network case, we quantitatively identify the tradeoff between the aggregate traffic throughput and the packet transmission delay, which can provide the insightful guidelines to improve the delay-QoS provisionings over cognitive radio wireless networks.
In November/2004, we witnessed the formation of the first worldwide effort to define a novel wireless air interface (i.e., MAC and PHY) standard based on Cognitive Radios (CRs): the IEEE … In November/2004, we witnessed the formation of the first worldwide effort to define a novel wireless air interface (i.e., MAC and PHY) standard based on Cognitive Radios (CRs): the IEEE 802.22 Working Group (WG). The IEEE 802.22 WG is chartered with the development of a CR-based Wireless Regional Area Network (WRAN) Physical (PHY) and Medium Access Control (MAC) layers for use by license-exempt devices in the spectrum that is currently allocated to the Television (TV) service. Since 802.22 is required to reuse the fallow TV spectrum without causing any harmful interference to incumbents (i.e., the TV receivers), cognitive radio techniques are of primary importance in order to sense and measure the spectrum and detect the presence/absence of incumbent signals. On top of that, other advanced techniques that facilitate coexistence such as dynamic spectrum management and radio environment characterization could be designed. In this paper, we provide a detailed overview of the 802.22 draft specification, its architecture, requirements, applications, and coexistence considerations. These not only form the basis for the definition of this groundbreaking wireless air interface standard, but will also serve as foundation for future research in the promising area of CRs.
Cognitive Radios have been advanced as a technology for the opportunistic use of under-utilized spectrum since they are able to sense the spectrum and use frequency bands if no Primary … Cognitive Radios have been advanced as a technology for the opportunistic use of under-utilized spectrum since they are able to sense the spectrum and use frequency bands if no Primary user is detected. However, the required sensitivity is very demanding since any individual radio might face a deep fade. We propose light-weight cooperation in sensing based on hard decisions to mitigate the sensitivity requirements on individual radios. We show that the "link budget" that system designers have to reserve for fading is a significant function of the required probability of detection. Even a few cooperating users (~10-20) facing independent fades are enough to achieve practical threshold levels by drastically reducing individual detection requirements. Hard decisions perform almost as well as soft decisions in achieving these gains. Cooperative gains in a environment where shadowing is correlated, is limited by the cooperation footprint (area in which users cooperate). In essence, a few independent users are more robust than many correlated users. Unfortunately, cooperative gain is very sensitive to adversarial/failing Cognitive Radios. Radios that fail in a known way (always report the presence/absence of a Primary user) can be compensated for by censoring them. On the other hand, radios that fail in unmodeled ways or may be malicious, introduce a bound on achievable sensitivity reductions. As a rule of thumb, if we believe that 1/N users can fail in an unknown way, then the cooperation gains are limited to what is possible with N trusted users.
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network … <para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Cognitive radios hold tremendous promise for increasing spectral efficiency in wireless systems. This paper surveys the fundamental capacity limits and associated transmission techniques for different wireless network design paradigms based on this promising technology. These paradigms are unified by the definition of a cognitive radio as an intelligent wireless communication device that exploits side information about its environment to improve spectrum utilization. This side information typically comprises knowledge about the activity, channels, codebooks, and/or messages of other nodes with which the cognitive node shares the spectrum. Based on the nature of the available side information as well as <emphasis emphasistype="italic">a priori</emphasis> rules about spectrum usage, cognitive radio systems seek to underlay, overlay, or interweave the cognitive radios' signals with the transmissions of noncognitive nodes. We provide a comprehensive summary of the known capacity characterizations in terms of upper and lower bounds for each of these three approaches. The increase in system degrees of freedom obtained through cognitive radios is also illuminated. This information-theoretic survey provides guidelines for the spectral efficiency gains possible through cognitive radios, as well as practical design ideas to mitigate the coexistence challenges in today's crowded spectrum. </para>
We consider a population of terminals communicating with a central station over a packet-switched multiple-access radio channel. The performance of carrier sense multiple access (CSMA) [1] used as a method … We consider a population of terminals communicating with a central station over a packet-switched multiple-access radio channel. The performance of carrier sense multiple access (CSMA) [1] used as a method for multiplexing these terminals is highly dependent on the ability of each terminal to sense the carrier of any other transmission on the channel. Many situations exist in which some terminals are "hidden" from each other (either because they are out-of-sight or out-of-range). In this paper we show that the existence of hidden terminals significantly degrades the performance of CSMA. Furthermore, we introduce and analyze the busy-tone multiple-access (BTMA) mode as a natural extension of CSMA to eliminate the hidden-terminal problem. Numerical results giving the bandwidth utilization and packet delays are shown, illustrating that BTMA with hidden terminals performs almost as well as CSMA without hidden terminals.
We propose decentralized cognitive MAC protocols that allow secondary users to independently search for spectrum opportunities without a central coordinator or a dedicated communication channel. Recognizing hardware and energy constraints, … We propose decentralized cognitive MAC protocols that allow secondary users to independently search for spectrum opportunities without a central coordinator or a dedicated communication channel. Recognizing hardware and energy constraints, we assume that a secondary user may not be able to perform full-spectrum sensing or may not be willing to monitor the spectrum when it has no data to transmit. We develop an analytical framework for opportunistic spectrum access based on the theory of partially observable Markov decision process (POMDP). This decision-theoretic approach integrates the design of spectrum access protocols at the MAC layer with spectrum sensing at the physical layer and traffic statistics determined by the application layer of the primary network. It also allows easy incorporation of spectrum sensing error and constraint on the probability of colliding with the primary users. Under this POMDP framework, we propose cognitive MAC protocols that optimize the performance of secondary users while limiting the interference perceived by primary users. A suboptimal strategy with reduced complexity yet comparable performance is developed. Without additional control message exchange between the secondary transmitter and receiver, the proposed decentralized protocols ensure synchronous hopping in the spectrum between the transmitter and the receiver in the presence of collisions and spectrum sensing errors
In this letter, we consider cooperative spectrum sensing based on energy detection in cognitive radio networks. Soft combination of the observed energies from different cognitive radio users is investigated. Based … In this letter, we consider cooperative spectrum sensing based on energy detection in cognitive radio networks. Soft combination of the observed energies from different cognitive radio users is investigated. Based on the Neyman-Pearson criterion, we obtain an optimal soft combination scheme that maximizes the detection probability for a given false alarm probability. Encouraged by the performance gain of soft combination, we further propose a new softened hard combination scheme with two-bit overhead for each user and achieve a good tradeoff between detection performance and complexity.
Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum. Such revolutionary and transforming technology represents a … Cognitive radio is an exciting emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum. Such revolutionary and transforming technology represents a paradigm shift in the design of wireless systems, as it will allow the agile and efficient utilization of the radio spectrum by offering distributed terminals or radio cells the ability of radio sensing, self-adaptation, and dynamic spectrum sharing. Cooperative communications and networking is another new communication technology paradigm that allows distributed terminals in a wireless network to collaborate through some distributed transmission or signal processing so as to realize a new form of space diversity to combat the detrimental effects of fading channels. In this paper, we consider the application of these technologies to spectrum sensing and spectrum sharing. One of the most important challenges for cognitive radio systems is to identify the presence of primary (licensed) users over a wide range of spectrum at a particular time and specific geographic location. We consider the use of cooperative spectrum sensing in cognitive radio systems to enhance the reliability of detecting primary users. We shall describe spectrum sensing for cognitive radios and propose robust cooperative spectrum sensing techniques for a practical framework employing cognitive radios. We also investigate cooperative communications for spectrum sharing in a cognitive wireless relay network. To exploit the maximum spectrum opportunities, we present a cognitive space-time-frequency coding technique that can opportunistically adjust its coding structure by adapting itself to the dynamic spectrum environment.
Compounding the confusion is the use of the broad term cognitive radio as a synonym for dynamic spectrum access. As an initial attempt at unifying the terminology, the taxonomy of … Compounding the confusion is the use of the broad term cognitive radio as a synonym for dynamic spectrum access. As an initial attempt at unifying the terminology, the taxonomy of dynamic spectrum access is provided. In this article, an overview of challenges and recent developments in both technological and regulatory aspects of opportunistic spectrum access (OSA). The three basic components of OSA are discussed. Spectrum opportunity identification is crucial to OSA in order to achieve nonintrusive communication. The basic functions of the opportunity identification module are identified
Radio spectrum resource is of fundamental importance for wireless communication. Recent reports show that most available spectrum has been allocated. While some of the spectrum bands (e.g., unlicensed band, GSM … Radio spectrum resource is of fundamental importance for wireless communication. Recent reports show that most available spectrum has been allocated. While some of the spectrum bands (e.g., unlicensed band, GSM band) have seen increasingly crowded usage, most of the other spectrum resources are underutilized. This drives the emergence of open spectrum and dynamic spectrum access concepts, which allow unlicensed users equipped with cognitive radios to opportunistically access the spectrum not used by primary users. Cognitive radio has many advanced features, such as agilely sensing the existence of primary users and utilizing multiple spectrum bands simultaneously. However, in practice such capabilities are constrained by hardware cost. In this paper, we discuss how to conduct efficient spectrum management in ad hoc cognitive radio networks while taking the hardware constraints (e.g., single radio, partial spectrum sensing and spectrum aggregation limit) into consideration. A hardware-constrained cognitive MAC, HCMAC, is proposed to conduct efficient spectrum sensing and spectrum access decision. We identify the issue of optimal spectrum sensing decision for a single secondary transmission pair, and formulate it as an optimal stopping problem. A decentralized MAC protocol is then proposed for the ad hoc cognitive radio networks. Simulation results are presented to demonstrate the effectiveness of our proposed protocol.
In cognitive networks, cognitive (unlicensed) users need to continuously monitor spectrum to detect the presence of primary (licensed) users. In part I, we have illustrated the benefits of cooperation in … In cognitive networks, cognitive (unlicensed) users need to continuously monitor spectrum to detect the presence of primary (licensed) users. In part I, we have illustrated the benefits of cooperation in cognitive radio by considering a simple two-user network and showing improvement in agility. In part II, we investigate multiple cognitive user networks. We first consider multiuser single carrier networks and develop sufficient conditions for agility gain when the cognitive population is arbitrarily large. We then propose a practical algorithm which allows cooperation between cognitive users in random networks. Finally, we provide an example to illustrate the concepts developed in this paper.
This article presents a high-level overview of the IEEE 802.22 standard for cognitive wireless regional area networks (WRANs) that is under development in the IEEE 802 LAN/MAN Standards Committee. This article presents a high-level overview of the IEEE 802.22 standard for cognitive wireless regional area networks (WRANs) that is under development in the IEEE 802 LAN/MAN Standards Committee.
The concept of cognitive radio (or secondary spectrum access) is currently under investigation as a promising paradigm to achieve efficient use of the frequency resource by allowing the coexistence of … The concept of cognitive radio (or secondary spectrum access) is currently under investigation as a promising paradigm to achieve efficient use of the frequency resource by allowing the coexistence of licensed (primary) and unlicensed (secondary) users in the same bandwidth. According to the property-rights model of cognitive radio, the primary terminals own a given bandwidth and may decide to lease it for a fraction of time to secondary nodes in exchange for appropriate remuneration. In this paper, we propose and analyze an implementation of this framework, whereby a primary link has the possibility to lease the owned spectrum to an ad hoc network of secondary nodes in exchange for cooperation in the form of distributed space-time coding. On one hand, the primary link attempts to maximize its quality of service in terms of either rate or probability of outage, accounting for the possible contribution from cooperation. On the other hand, nodes in the secondary ad hoc network compete among themselves for transmission within the leased time-slot following a distributed power control mechanism. The investigated model is conveniently cast in the framework of Stackelberg games. We consider both a baseline scenario with full channel state information and information-theoretic transmission strategies, and a more practical model with long-term channel state information and randomized distributed space-time coding. Analysis and numerical results show that spectrum leasing based on trading secondary spectrum access for cooperation is a promising framework for cognitive radio.
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Cognitive radio technology has been proposed to improve spectrum efficiency by having the cognitive radios act as secondary users to opportunistically access under-utilized frequency bands. Spectrum sensing, … <para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Cognitive radio technology has been proposed to improve spectrum efficiency by having the cognitive radios act as secondary users to opportunistically access under-utilized frequency bands. Spectrum sensing, as a key enabling functionality in cognitive radio networks, needs to reliably detect signals from licensed primary radios to avoid harmful interference. However, due to the effects of channel fading/shadowing, individual cognitive radios may not be able to reliably detect the existence of a primary radio. In this paper, we propose an optimal linear cooperation framework for spectrum sensing in order to accurately detect the weak primary signal. Within this framework, spectrum sensing is based on the linear combination of local statistics from individual cognitive radios. Our objective is to minimize the interference to the primary radio while meeting the requirement of opportunistic spectrum utilization. We formulate the sensing problem as a nonlinear optimization problem. By exploiting the inherent structures in the problem formulation, we develop efficient algorithms to solve for the optimal solutions. To further reduce the computational complexity and obtain solutions for more general cases, we finally propose a heuristic approach, where we instead optimize a modified <emphasis emphasistype="italic">deflection</emphasis> coefficient that characterizes the probability distribution function of the global test statistics at the fusion center. Simulation results illustrate significant cooperative gain achieved by the proposed strategies. The insights obtained in this paper are useful for the design of optimal spectrum sensing in cognitive radio networks. </para>
With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a … With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing demand for wireless radio spectrum. However, the fixed spectrum assignment policy becomes a bottleneck for more efficient spectrum utilization, under which a great portion of the licensed spectrum is severely under-utilized. The inefficient usage of the limited spectrum resources urges the spectrum regulatory bodies to review their policy and start to seek for innovative communication technology that can exploit the wireless spectrum in a more intelligent and flexible way. The concept of cognitive radio is proposed to address the issue of spectrum efficiency and has been receiving an increasing attention in recent years, since it equips wireless users the capability to optimally adapt their operating parameters according to the interactions with the surrounding radio environment. There have been many significant developments in the past few years on cognitive radios. This paper surveys recent advances in research related to cognitive radios. The fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications are first introduced. The existing works in spectrum sensing are reviewed, and important issues in dynamic spectrum allocation and sharing are investigated in detail.
Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering … Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Hence, recent research has been focused on the interference avoidance problem. Moreover, current radio frequency (RF) front-ends cannot perform sensing and transmission at the same time, which inevitably decreases their transmission opportunities, leading to the so-called sensing efficiency problem. In this paper, in order to solve both the interference avoidance and the spectrum efficiency problem, an optimal spectrum sensing framework is developed. More specifically, first a theoretical framework is developed to optimize the sensing parameters in such a way as to maximize the sensing efficiency subject to interference avoidance constraints. Second, in order to exploit multiple spectrum bands, spectrum selection and scheduling methods are proposed where the best spectrum bands for sensing are selected to maximize the sensing capacity. Finally, an adaptive and cooperative spectrum sensing method is proposed where the sensing parameters are optimized adaptively to the number of cooperating users. Simulation results show that the proposed sensing framework can achieve maximum sensing efficiency and opportunities in multi-user/multi-spectrum environments, satisfying interference constraints.
A cognitive radio network (CRN) is formed by either allowing the secondary users (SUs) in a secondary communication network (SCN) to opportunistically operate in the frequency bands originally allocated to … A cognitive radio network (CRN) is formed by either allowing the secondary users (SUs) in a secondary communication network (SCN) to opportunistically operate in the frequency bands originally allocated to a primary communication network (PCN) or by allowing SCN to coexist with the primary users (PUs) in PCN as long as the interference caused by SCN to each PU is properly regulated. In this paper, we consider the latter case, known as spectrum sharing, and study the optimal power allocation strategies to achieve the ergodic capacity and the outage capacity of the SU fading channel under different types of power constraints and fading channel models. In particular, besides the interference power constraint at PU, the transmit power constraint of SU is also considered. Since the transmit power and the interference power can be limited either by a peak or an average constraint, various combinations of power constraints are studied. It is shown that there is a capacity gain for SU under the average over the peak transmit/interference power constraint. It is also shown that fading for the channel between SU transmitter and PU receiver is usually a beneficial factor for enhancing the SU channel capacities.
This paper considers the detection of the presence/absence of signals in uncertain low SNR environments. Small modeling uncertainties are unavoidable in any practical system and so robustness to them is … This paper considers the detection of the presence/absence of signals in uncertain low SNR environments. Small modeling uncertainties are unavoidable in any practical system and so robustness to them is a fundamental performance metric. The impact of these modeling uncertainties can be quantified by the position of the "SNR wall" below which a detector will fail to be robust, no matter how long it can observe the channel. We propose simple mathematical models for the uncertainty in the noise and fading processes. These are used to show what aspects of the model lead to SNR walls for differing levels of knowledge of the signal to be detected. These results have implications for wireless spectrum regulators. The context is opportunistically sharing spectrum with primary users that must be detected in order to avoid causing harmful interference on a channel. Ideally, a secondary system would be able to detect primaries robustly without having to know much about their signaling strategies. We argue that the tension between primary and secondary users is captured by the technical question of computing the optimal tradeoff between the primary user's capacity and the secondary user's sensing robustness as quantified by the SNR wall. This is an open problem, but we compute this tradeoff for some simple detectors.
Next-generation wireless networks are expected to support extremely high data rates and radically new applications, which require a new wireless radio technology paradigm. The challenge is that of assisting the … Next-generation wireless networks are expected to support extremely high data rates and radically new applications, which require a new wireless radio technology paradigm. The challenge is that of assisting the radio in intelligent adaptive learning and decision making, so that the diverse requirements of next-generation wireless networks can be satisfied. Machine learning is one of the most promising artificial intelligence tools, conceived to support smart radio terminals. Future smart 5G mobile terminals are expected to autonomously access the most meritorious spectral bands with the aid of sophisticated spectral efficiency learning and inference, in order to control the transmission power, while relying on energy efficiency learning/inference and simultaneously adjusting the transmission protocols with the aid of quality of service learning/inference. Hence we briefly review the rudimentary concepts of machine learning and propose their employment in the compelling applications of 5G networks, including cognitive radios, massive MIMOs, femto/small cells, heterogeneous networks, smart grid, energy harvesting, device-todevice communications, and so on. Our goal is to assist the readers in refining the motivation, problem formulation, and methodology of powerful machine learning algorithms in the context of future networks in order to tap into hitherto unexplored applications and services.
In cognitive radio networks, cognitive (unlicensed) users need to continuously monitor spectrum for the presence of primary (licensed) users. In this paper, we illustrate the benefits of cooperation in cognitive … In cognitive radio networks, cognitive (unlicensed) users need to continuously monitor spectrum for the presence of primary (licensed) users. In this paper, we illustrate the benefits of cooperation in cognitive radio. We show that by allowing the cognitive users operating in the same band to cooperate we can reduce the detection time and thus increase the overall agility. We first consider a two-user cognitive radio network and show how the inherent asymmetry in the network can be exploited to increase the agility. We show that our cooperation scheme increases the agility of the cognitive users by as much as 35%. We then extend our cooperation scheme to multicarrier networks with two users per carrier and analyze asymptotic agility gain. In Part II of our paper [1], we investigate multiuser single carrier networks. We develop a decentralized cooperation protocol which ensures agility gain for arbitrarily large cognitive network population.
Spectrum sensing is a key technology to detect unused frequency bands, and is widely applied in spectrum sharing and dynamic channel allocation. However, it is a challenge to provide high … Spectrum sensing is a key technology to detect unused frequency bands, and is widely applied in spectrum sharing and dynamic channel allocation. However, it is a challenge to provide high sensing accuracy under low signal-to-noise-ratio (SNR) environments. To address this issue, this paper proposes a novel method based on feature extraction and fusion clustering. First, the sampling matrix of the received signal is decomposed into two orthogonal components I and Q, and Cholesky decomposition is performed on the covariance matrices of I and Q components to extract their two-dimensional feature vectors. Then, the fusion clustering algorithm is proposed, where the GMM clustering algorithm is performed to classify the feature vectors, and the initial parameters of GMM, such as centroids, weights and covariance matrices, are generated by K-means clustering. Simulation results show that the proposed method accelerates the convergence speed of GMM and improves the classification accuracy. It effectively enhances the performance of spectrum sensing compared to other mainstream methods.
The rapid development of sixth-generation mobile communication systems has brought about significant advancements in both Quality of Service (QoS) and Quality of Experience (QoE) for users, largely due to the … The rapid development of sixth-generation mobile communication systems has brought about significant advancements in both Quality of Service (QoS) and Quality of Experience (QoE) for users, largely due to the extremely high data rates and a diverse range of service offerings. However, these advancements have also introduced challenges, especially concerning the growing demand for a wireless spectrum and the limited availability of resources. Various efforts have been made and research has attempted to tackle this issue such as the use of Cognitive Radio Networks (CRNs), which allows opportunistic spectrum access and intelligent resource management. This work demonstrate a new method in the optimization of allocation resource in CRNs based on the Snake Optimizer (SO) along with reinforcement learning (RL), which is an effective meta-heuristic algorithm that simulates snake cloning behavior. SO is tested over three different scenarios with varying numbers of secondary users (SUs), primary users (PUs), and frequency bands available. The obtained results reveal that the proposed approach is able to largely satisfy the aforementioned requirements and ensures high spectrum utilization efficiency and low collision rates, which eventually lead to the maximum possible spectral capacity. The study also demonstrates that SO is versatile and resilient and thus indicates its capability of serving as an effective method for augmenting resource management in next-generation wireless communication systems.
This paper presents a survey of performance metrics applicable to spectrum sensing and spectrum hole geolocation within the context of dynamic spectrum access (DSA) in cognitive radio networks. While grounded … This paper presents a survey of performance metrics applicable to spectrum sensing and spectrum hole geolocation within the context of dynamic spectrum access (DSA) in cognitive radio networks. While grounded in binary hypothesis testing, the review emphasizes metrics specialized for sensing reliability, interference risk, spatial accuracy, and network efficiency. The work also highlights trade-offs among metrics and provides guidelines for their practical application. A key contribution of this work is to provide researchers and practitioners with a comprehensive set of evaluation tools, extending well beyond the applicability of the conventional probabilities of detection and false alarm.
Abstract Nowadays, the use of the radio spectrum has suffered an increase in demand. For this reason, new alternatives are needed so that many more users can employ this exhaustible … Abstract Nowadays, the use of the radio spectrum has suffered an increase in demand. For this reason, new alternatives are needed so that many more users can employ this exhaustible natural resource. One is cognitive radio (CR), a system that has shown favorable results in telecommunications. The CR cycle consists of several main functions, one of which is spectrum sensing (SS). SS aims to detect if the primary user is occupying his frequency band. This work is focused on spectrum sensing for cognitive radio applications, which was performed using filter banks and energy detectors for narrowband and wideband. Filter banks divide the bandwidth into small frequency sub-bands to measure the energy in each channel using energy detectors. Filter banks are designed from a prototype filter modulated to repeat over the bandwidth. The detectors measure the energy in time intervals in each filter bank channel and compare the result with a threshold value to determine whether a signal exists in the sub-band. The work was done using MATLAB, with simulations that involved varying the parameters, generating Quadrature Amplitude Modulation (QAM) signals at different frequencies, and adding Additive White Gaussian Noise (AWGN) in a controlled way by varying the Signal-to-Noise Ratio (SNR) between the signals and the noise. These simulations were crucial in validating the effectiveness of our approach. The advantages and disadvantages of this approach are also presented.
Nowadays, wireless communication plays an indispensable role in people's lives. To enhance communication efficiency, accurate and timely spectrum sensing is crucial. However, the existing models were ineffective due to the … Nowadays, wireless communication plays an indispensable role in people's lives. To enhance communication efficiency, accurate and timely spectrum sensing is crucial. However, the existing models were ineffective due to the dynamic characteristics of the wireless channel. Therefore, this article proposes a spectrum heterogeneity-based efficient spectrum sensing in 6G wireless communication using ATRC-LSNN and F-ExpoTIS. The RF signals are primarily gathered and then subjected to L(D) 2 TSO-based optimal beamforming. Subsequently, the maximum ratio combiner and level differencing are done, followed by signal pre-processing. Thereafter, the HKSLC is established to group the signal regarding frequency. Also, the frequency bands are extracted from the grouped signal via F-ExpoTIS. Similarly, the features are extracted from the grouped signal. Now, the features and frequency bands are inputted to the ATRC-LSNN, where the spectrum is sensed. Lastly, the WT is introduced to detect the signal interferences. Thus, the experimental outcomes showed that the proposed approach had higher prominence with 97.06% accuracy.
<title>Abstract</title> Ensuring higher packet delivery is a challenge in Cognitive radio ad-hoc network (CRAN) due to augmentation of channel unavailability based routing disruptions along with movement triggered path failures. This … <title>Abstract</title> Ensuring higher packet delivery is a challenge in Cognitive radio ad-hoc network (CRAN) due to augmentation of channel unavailability based routing disruptions along with movement triggered path failures. This work proposes a integrated solution combining stable routing path selection based on channel availability predictions, minimizing congestion through source rate control and adaptive caching based packet loss recovery. Channel availability prediction based route path reduces the probability of path failures during routing. Source rate control reduces the probability of packet failures arising from congestion. Adaptive caching based packet loss recovery, attempts to make best use of cache for retransmission with least hop length for packet retransmissions. This combined strategy is able to reduce the overall packet loss in CRAN and increase the packet reliability.
The exponential growth in wireless communication demand, driven by the proliferation of mobile devices and data-intensive applications such as the Internet of Things (IoT), has intensified pressure on the finite … The exponential growth in wireless communication demand, driven by the proliferation of mobile devices and data-intensive applications such as the Internet of Things (IoT), has intensified pressure on the finite radio frequency spectrum. Traditional static spectrum allocation policies have led to inefficient spectrum utilization, with some frequency bands experiencing scarcity while others remain underused. Cognitive Radio Networking (CRN) has emerged as a transformative solution to this challenge, enabling intelligent wireless devices to dynamically sense, access, and manage spectrum resources in real time. By allowing secondary (unlicensed) users to opportunistically utilize underutilized spectrum without causing harmful interference to primary (licensed) users, CRN significantly enhances spectrum efficiency and supports the deployment of innovative wireless services. This paper provides a comprehensive overview of cognitive radio networking, detailing its foundational principles-including spectrum sensing, spectrum management, spectrum mobility, spectrum sharing, and power control. It examines the core techniques and protocols that enable dynamic spectrum access (DSA), such as opportunistic, underlay, and overlay paradigms, and discusses the key technical challenges of interference management, spectrum handoff, and regulatory compliance. The analysis highlights the critical role of advanced sensing and management protocols, cooperative strategies, and standardization efforts in realizing the full potential of CRN. By synthesizing current research and identifying open issues, the paper underscores the significance of cognitive radio networks in addressing spectrum scarcity and shaping the future landscape of wireless communication.
Cognitive sensors are embedded in home appliances and other surrounding devices to create a connected, intelligent environment for providing pervasive and ubiquitous services. These sensors frequently create massive amounts of … Cognitive sensors are embedded in home appliances and other surrounding devices to create a connected, intelligent environment for providing pervasive and ubiquitous services. These sensors frequently create massive amounts of data with many redundant and repeating bit values. Cognitive sensors are always restricted in resources, and if careful strategy is not applied at the time of deployment, the sensors become disconnected, degrading the system’s performance in terms of energy, reconfiguration, delay, latency, and packet loss. To address these challenges and to establish a connected network, there is always a need for a system to evaluate the contents of detected data values and dynamically switch sensor states based on their function. Here in this article, we propose a reinforcement learning-based mechanism called “Adaptive Scheduling in Cognitive IoT Sensors for Optimizing Network Performance using Reinforcement Learning (ASC-RL)”. For reinforcement learning, the proposed scheme uses three types of parameters: internal parameters (states), environmental parameters (sensing values), and history parameters (energy levels, roles, number of switching states) and derives a function for the state-changing policy. Based on this policy, sensors adjust and adapt to different energy states. These states minimize extensive sensing, reduce costly processing, and lessen frequent communication. The proposed scheme reduces network traffic and optimizes network performance in terms of network energy. The main factors evaluated are joint Gaussian distributions and event correlations, with derived results of signal strengths, noise, prediction accuracy, and energy efficiency with a combined reward score. Through comparative analysis, ASC-RL enhances the overall system’s performance by 3.5% in detection and transition probabilities. The false alarm probabilities are reduced to 25.7%, the transmission success rate is increased by 6.25%, and the energy efficiency and reliability threshold are increased by 35%.
The purpose of the research is to develop a method for restoring clock synchronization for signals demodulators with square amplitude manipulation. Methods are based on the foundations of quasi -optimal … The purpose of the research is to develop a method for restoring clock synchronization for signals demodulators with square amplitude manipulation. Methods are based on the foundations of quasi -optimal receipt of multi -position signals, the theory of constructing radio -receiving systems of digital communication lines, methods of mathematical modeling of signals, probability theory and mathematical statistics. The well -known algorithms for assessing the phase of clusion of clusion in the presence of manipulation interference, due to a multi -level signal modulation, were used. The assumption was assumed that the channel satisfies the conditions of Naquvist, and the distorting hindrance signal is an additive white Gaussian noise. Results. The development of a method for restoring clock synchronization is implemented, which consists in using solutions and reducing each pair of adjacent symbols to a binary signal by centering them relative to the zero point and weighting by level. Analytical dependences of the phase estimate for the clock synchronization device are presented, as well as structural and functional diagrams of the implementation of various options for constructing this device as part of demodulators of multi-position signals with quadrature-amplitude manipulation. The obtained graphs of the components of the fluctuation characteristic of the discriminator of the clock synchronization device indicate that the developed algorithm allows resolving the contradiction between the reduction of the manipulation component and the growth of the noise component of the fluctuation characteristic. Conclusion. From the point of view of the noise immunity of the optimal, coherent demodulation of signals is, however, a clock (phase) synchronization of the reference generator of the demodulator with the received signal, namely ensuring the coincidence of clock impulses in the decisive device with the ends of the end of information symbols. The use of the developed method, as shown by the results of theoretical and experimental studies, allowed about 0.5 to 0.7 dB to increase the noise resistance of the demodulator of radio -receiver systems of digital communication lines.
Increasing demand for spectrum causes the emergence of technologies like Cognitive Radio (CR). Resources like bandwidth and energy are primarily shared by the primary and secondary users in the CR … Increasing demand for spectrum causes the emergence of technologies like Cognitive Radio (CR). Resources like bandwidth and energy are primarily shared by the primary and secondary users in the CR network. Resource utilization depends on the number of nodes, topology dimension, packet generation rate, and time of channel utilization. Therefore, optimizing resources in CR is a need of the hour. In the presented paper, a PSO-based resource allocation scheme is implemented. The input parameters like the number of secondary user nodes, packet generation rate, dimension of the network, and simulation time are targeted to get optimum results of packet delivery ratio, average throughput, average delay, and energy consumption. To implement CR, NS-2 is used. The fitness equations are obtained by varying the input parameters in a given range. Curve-fitting software is used to get fitness equations. These fitness equations are then used in the PSO algorithm, which is implemented in MATLAB. With implementing a PSO-based resource allocation scheme, the performance of packet delivery ratio, throughput, delay, and energy consumption increased by 22.15 %, 22.15 %, 67.83 %, and 32.18 %, respectively.
ABSTRACT This paper proposes a new method for unit commitment (UC) with Quantum Predator Prey Brain Storm Optimization (QPPBSO). The UC problems may be expressed as a mixed integer nonlinear … ABSTRACT This paper proposes a new method for unit commitment (UC) with Quantum Predator Prey Brain Storm Optimization (QPPBSO). The UC problems may be expressed as a mixed integer nonlinear programming problem in which binary variables mean on/off conditions of units and continuous ones imply their output. Recently, Evolutionary Computation (EC) has been applied to the UC problems due to the existence of indifferentiable cost functions such as large‐scale steam turbine units, etc. However, there is still room for improvement in EC because the UC problems have high nonlinear features. This paper focuses on the integration of EC with Quantum Computing (QC) that is promising in power systems. Specifically, this paper combines QC with Predator Prey Brain Storm Optimization (PPBSO) of high‐performance EC. The effectiveness of the proposed method is demonstrated in the New England 39‐node system.
Introduction: The objective of this research is to develop an economical, real-time attendance system based on face detection on a Raspberry Pi, driven by Edge AI and IoT technologies for … Introduction: The objective of this research is to develop an economical, real-time attendance system based on face detection on a Raspberry Pi, driven by Edge AI and IoT technologies for rapid and secure processing. To make the system accessible even to non-programmers, it includes easy-to-use tools such as Node-RED for simple visual programming. With in-device image processing, hybrid storage (local and cloud), and auto-alerts, the system provides a secure, scalable, and dependable solution perfect for smart campuses, new-age workplaces, and industrial settings. Methods: To test different connectivity and automation requirements, the system is tested in four different configurations: Case 1 is entirely offline with a Raspberry Pi and local database to identify faces. Case 2 incorporates real-time cloud access through the inclusion of Firebase. Case 3 adds Node-RED to the local environment to provide automation options such as dashboards and email notifications. Case 4 uses MariaDB, Node-RED, and the Pi Camera for an entirely automated, scalable application with real-time notification—perfect for institutional or enterprise applications. Results: All four implementation scenarios validate that the real-time face recognition-based attendance system operates efficiently and with minimal latency. With edge processing using Raspberry Pi, it minimizes reliance on external servers. Node-RED streamlines workflow automation, allowing seamless attendance tracking, real-time monitoring, and instant email notifications through a simple-to-use dashboard. With support for both on-premises (MariaDB) and cloud (Firebase) storage, the system provides scalable deployment options on a per-scalability and connectivity basis. Generally, it provides a secure, efficient alternative to legacy biometric and RFID-based systems and is appropriate for various environments. Conclusions: The method provides a scalable, automatic, and cost-effective face recognition attendance system. The solution perfectly integrates hardware, software, and cloud services to deliver a real-time, smart attendance tracking system with Raspberry Pi and Node-RED.
A new field called Vehicular Adhoc Networks (VANETs) uses wireless local area networks (WLANs) with an ad-hoc topology. Routing complexity and high control overhead are two frequent challenges faced by … A new field called Vehicular Adhoc Networks (VANETs) uses wireless local area networks (WLANs) with an ad-hoc topology. Routing complexity and high control overhead are two frequent challenges faced by vehicular ad hoc networks (VANETs). However, most of these initiatives failed to provide a comprehensive solution to the problems associated with routing and control overhead minimization. In order to lower the augmented control overhead, the current work presents an Improved Deep Reinforcement Learning (IDRL) method for routing. As 5G cells arrive, emerging automotive networks could make driving safer, more environmentally friendly, and more efficient. They should also pave the road for autonomous driving. High sequence factors in vehicle settings give rise to a variety of new irritants, which is why remote design approaches are being reconsidered. Future smart cars, which constitute the foundation of high-performance multipurpose networks, are steadily receiving increasingly sophisticated sensors and are still generating vast amounts of data.
Abstract A multitude of methodologies, based on the detection of cyclostationary features (CFD), are available to researchers seeking to identify unoccupied spectrum channels within cognitive radio (CR) networks. Notwithstanding the … Abstract A multitude of methodologies, based on the detection of cyclostationary features (CFD), are available to researchers seeking to identify unoccupied spectrum channels within cognitive radio (CR) networks. Notwithstanding the inherent difficulties of wireless environments, such as those involving a low signal-to-noise ratio, CFD has demonstrated considerable potential. However, addressing signal variation and system complexity remains a primary area of research. This paper introduces a novel CFD algorithm that employs the autocorrelation function as a preprocessing step to enhance the received signal characteristics and distinguish noisy signals from noise. Subsequently, a straightforward cyclostationary detection approach is applied. The objective of this blind cyclostationary spectrum detection technique was to reduce the algorithmic complexity and enhance the detection efficiency. This paper presents optimized parameters for a blind cyclostationary detector and offers an evaluation of its performance in simulation environments. The results demonstrate a minimum 3.5 dB enhancement in detection performance relative to the benchmarking techniques. Furthermore, the SDR implementation of the proposed method in the receiving part of a transmitter/receiver FM broadcasting system, using two USRPs cards connected to two laptops running the GNU Radio platform, serves to validate its effectiveness in real-time scenarios.