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Cognitive Radio (CR) is a promising technology to solve the challenging spectrum scarcity problem. However, to implement CR, spectrum sensing is the groundwork and the precondition. In this paper, a collaborative spectrum sensing scheme using fuzzy comprehensive evaluation is proposed. The final sensing decision of the proposed scheme is based on the combination of distributed sensing results of different Secondary Users (SUs). To improve the reliability of the sensing decision, the combination procedure takes into account the credibility of each SU, which is evaluated using fuzzy comprehensive evaluation. The effect of the presence of malicious SUs and malfunctioning SUs on the performance of the proposed scheme is also investigated. The efficiency of the scheme is validated through analysis and simulation. [ABSTRACT FROM AUTHOR]

In this paper, a systematic approach and their corresponding metrics for concurrent anti-jamming (AJ) and low probability of detection (LPD) performance evaluations of a secure communications system are investigated. In general, it is necessary to deal simultaneously with adversary threats of both active jamming and passive detection for a secure communications system concern. For independent or concurrent AJ and LPD performance evaluations, a single varying paired and multiple paired fixed collocated jammers/interceptors scenario is explored with real sinc type ( sin( x)/ x) antenna patterns being considered for the communicators. The error probability with both AJ and LPD being considered simultaneously can be derived as system- and geometry-dependent factors and categorized as system metrics related to jammers, interceptors, and communicators themselves only. Whenever multiple collocated jammers/interceptors are considered, we can observe interesting “smoothed” effects for bit energy to jamming density ratio ( E b/ J o), when one of these varying jammers/interceptors is approaching or receding. In addition, by means of these system metrics, it is intuitive and straightforward to enhance system performance for the victim or to deteriorate system performance for the adversary, respectively. Moreover, the proposed approach and metrics have also paved one practical way for the developments of the latest emphasized cognitive radio (CR) communications systems, if all the collocated jammers/interceptors on the proposed scenario are replaced with “cooperative” communicators. [ABSTRACT FROM AUTHOR]

Fast and accurate spectrum sensing is one of the most important functions in a cognitive radio (CR) seeking to use the licensed but unoccupied spectrum segments. In this paper, we present a fully integrated CMOS receiver with a CR spectrum sensing capability in the UHF band. We propose multi-resolution spectrum sensing (MRSS), which is a digitally-assisted analog energy detection technique. Without using bulky analog filters, detection bandwidth can be flexibly controlled by correlating the received analog signals with window signal generated by built-in digital window generator. The integrated chip has been fabricated in a standard 0.18-μmm CMOS technology, and has achieved 32 dB of detection dynamic range with minimum detection sensitivity of -74 dBm by using a 100-kHz cos4 window. [ABSTRACT FROM AUTHOR]

Cognitive Radio (CR) capitalizes advances in signal processing and radio technology and is capable of reconfiguring RF and switching to desired frequency bands. It is a frequency-agile data communication device that is vastly more powerful than recently proposed multi-channel multi-radio (MC-MR) technology. In this paper, we investigate the important problem of multi-hop networking with CR nodes. For such a network, each node has a pool of frequency bands (typically of unequal size) that can be used for communication. The potential difference in the bandwidth among the available frequency bands prompts the need to further divide these bands into sub-bands for optimal spectrum sharing. We characterize the behavior and constraints for such a multi-hop CR network from multiple layers, including modeling of spectrum sharing and sub-band division, scheduling and interference constraints, and flow routing. We develop a mathematical formulation with the objective of minimizing the required network-wide radio spectrum resource for a set of user sessions. Since the formulated model is a mixed-integer non-linear program (MINLP), which is NP-hard in general, we develop a lower bound for the objective by relaxing the integer variables and using a linearization technique. Subsequently, we design a near-optimal algorithm to solve this MINLP problem. This algorithm is based on a novel sequential fixing procedure, where the integer variables are determined iteratively via a sequence of linear programs. Simulation results show that solutions obtained by this algorithm are very close to the lower bounds obtained via the proposed relaxation, thus suggesting that the solution produced by the algorithm is near-optimal. [ABSTRACT FROM AUTHOR]

This paper presents the development of the wideband power amplifier (PA) for application to intelligent cognitive radios. The load-tracking based on the frequency-varied load-pull technique is proposed for the PA design. The load impedance tracking is realized by filter network synthesis. A 3-7.5-GHz broadband PA is demonstrated in 0.15-μm InGaAs pseudomorphic HEMT technology. Operated at 3.5 V, the P1 dB and power-added efficiency of the PA are better than 21.4 dBm and 20%, respectively. [ABSTRACT FROM AUTHOR]

In this paper, a collaborative energy-harvesting cognitive radio (CR) network is considered such that the transmitter of the secondary user (SU) is allowed to harvest signal energy of the primary user (PU) when the presence of the PU is detected. The harvested energy is converted to electrical power in order to supply the sensing and transmission energy of SUs. The time frame (time slot) is divided into two phases allocated to sensing (divided into two durations: spectrum sensing and results reporting) and transmission, respectively. The time spanned by the results reporting duration depends on the number of collaborative sensing users, while the time spent on spectrum sensing duration controls the number of sensing samples. A constrained convex optimization problem of the overall probability of error is formulated incorporating constraints on time and energy resources along with PU interference protection presented as a threshold on probability of collision. We use a soft decision rule scheme while considering two energy harvesting scenarios namely, energy surplus and energy deficit. In each scenario, the convexity of the optimization problem is established analytically and the global optimal solution is obtained. Simulation results are provided to demonstrate the impact of the different parameters on the overall system performance as well as to verify the deduced analytical results. [ABSTRACT FROM PUBLISHER]

A mobile device with embedded cognitive radios (CRs) is integrated into a novel low-cost massive antenna configuration multihop or device-to-device (D2D) wireless network that temporarily uses any portion of the spectrum for transmissions. However, the number of spectral bands (SBs) that a CR can sense within a specific time is limited. Furthermore, CR node transmissions interfere with one another. This paper proposes a method both for cooperative sensing and transmission with preallocated disjoining of spectrum sections (SSs) from neighboring links to increase the likelihood of matching available SBs. This minimizes sensing and negotiating overheads and reduces interference from a viewpoint of high-level graph model and mathematical formulation. The multiple-constraint routing with the resource allocation for cooperative sensing problem is proven to be NP-hard. The resource allocation method is compared with existing SB postallocation methods (i.e., random SB allocation and fixed SB allocation) and preallocation methods (i.e., link-based SS allocation and multiple parallel SB allocation). The proposed methods handle the resource preallocation mechanism with a centralized solution but handle the sensed results with a decentralized solution to reduce the negotiating and selecting time. We evaluate the performance of the system capacity, end-to-end transmission delay, fairness index, and standard deviation, thereby verifying the quality of the proposed method in terms of interferences, the fading effect, and other environment-dependent conditions. The results of the proposed method are more favorable than those of other methods. [ABSTRACT FROM PUBLISHER]

The fast development in wireless communications and frequency bands assignments for every communication system limits the spectrum resources. Various techniques, for example, cognitive radio have occurred to tackle this issue by allowing unlicensed users to utilize the licensed bands. The most important component for establishing a reliable cognitive radio system is spectrum sensing. One of the ordinarily used spectrum sensing techniques is energy detection. It has low computational and usage complexities. But, for low signal-to-noise ratio (SNR) values it has a poor performance as it will not be able to differentiate the interference from noise and primary users. In this paper, a new energy detection technique for spectrum sensing is introduced. The proposed technique is based on utilization of de-noising filters such as recursive least square (RLS), 1-D wavelet de-noising filter, and 2-D wavelet de-noising filter. This technique is intended to achieve SNR gain, noise variance reduction, and enhance the detection threshold estimation. Furthermore, it exhibits noticeable increase in the throughput rather than that of the traditional detector. Simulation results revealed that the RLS de-noising filter exhibits much better performance than wavelet de-noising filters. [ABSTRACT FROM AUTHOR]

Cognitive Radio has been the key technology for dynamic spectrum access in wireless networks. Cognitive Radio seems to be a promising solution to the radio spectrum overcrowding problem as well. Cognitive Radio Network allows opportunistic usage of the spectrum holes by enabling the coexistence of licensed (primary) users and unlicensed (secondary) users. The existing wireless legacy network protocols limit the productive utilization of spectrum holes by the secondary users. The contribution of this paper is a cross-layer based location-aware forwarding protocol, using a distributed TDMA MAC, for ad-hoc Cognitive Radio Networks. The distributed TDMA based MAC protocol constructs TDMA schedules by exchanging three rounds of control messages with collision avoidance among secondary users as a fundamental goal. Exchange of control messages takes place over a common control channel in a distributed fashion. The MAC protocol also uses the service of network layer, which classifies the available channels and selects the best ranked channel and passes this information to the MAC sub-layer for effective communication. The proposed location-aware forwarding protocol constructs request zone for making decisions regarding data packet forwarding with highest packet delivery ratio, by confining the flooding of packets, as a key objective. Simulation results show the efficacy of the proposed cross-layer scheme. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) in conjunction with multiple-input multiple-output (MIMO) orthogonal frequency-division multiple access is a candidate technology for future mobile radio networks. The short communication range of underlay CR systems is commonly a major limiting factor. In this paper, we propose a computationally and spectrally efficient resource allocation scheme for multiuser MIMO orthogonal-frequency-division-multiplexing-based underlay CR networks to provide good spectral efficiency gain and, therefore, increased communication range. Since the formulated optimization problem defines a mixed-integer programming (combinatorial task) that is hard to solve, we propose a two-phase scheme to produce efficient solutions for both the downlink and the uplink. Particularly, the first procedure elaborates on an adaptive precoding that is characterized by spectral efficiency due to the degrees of freedom it can provide. The second procedure develops a fast subcarrier mapping algorithm, which can be worked out through optimal power distribution among the CR users. The proposed scheme is optimal for the downlink but, however, near-optimal for the uplink. Simulation results demonstrate the bandwidth and computational efficiencies of the proposed scheme compared with the state of the art. [ABSTRACT FROM AUTHOR]

The ever-increasing demand for mobile Internet and high-data-rate applications poses unique challenging requirements for 5G mobile networks, including spectrum limitations and massive connectivity. Cognitive radio and carrier aggregation (CA) have recently been proposed as promising technologies to overcome these challenges. In this paper, we investigate joint relay selection and optimal power allocation in an underlay cooperative cognitive radio with CA, taking into account the availability of multiple carrier components in two frequency bands, subject to outage probability requirements for primary users (PUs). The secondary user network employs relay selection, where the relay that maximizes the end-to-end sum rate is selected, assuming both decode-and-forward and amplify-and-forward relaying. The resulting optimization problems are optimally solved using convex optimization tools, i.e., dual decomposition and an efficient iterative method, allowing their application in practical implementations. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom efficiently to maximize the SU rate, while meeting the PU average outage probability constraints. [ABSTRACT FROM PUBLISHER]

Cognitive radio technologies permit the sharing of spectrums between unlicensed as well as licensed customers, based on the principle of non-interference. Spectrum sensing, in this field, is hence a vital tool that assists in the ascertainment of availability of a particular channel within the licensed spectrum, for unlicensed customers. But this function uses significant power that could be lessened through the employment of predictive mechanisms to discover spectrum holes. The traffic features of licensed customer systems in the real world are not known beforehand. In this paper, a spectrum predictor based on Neural Networks model Multi-Layer Perceptron and Back Propagation that do not need prior information regarding traffic features of licensed customers is designed. Binary Shuffled Frog Leaping Algorithm is proposed for structure optimization, the binary structure is suggested to show the memes with the purpose of developing a sub-collection with lesser dimensions than that of the original collection where detecting sensitivity and accuracy would be scalable with that of the primary status. Spectrum Predictor's performance is examined through exhaustive experiments. [ABSTRACT FROM AUTHOR]

In this paper, a new cooperative two-way cognitive relaying scheme is proposed. In this model, a primary user (PU) network consisting of two PU sources communicate with each other via a single amplify-and-forward (AF) relay. In addition, a secondary user (SU) source transmits its data to an SU destination via the same PU relay node. To mitigate the SU interference caused to the PU network, the PU network considers the SU network pairs as two additional relay nodes helping the original PU relay node in improving the PU network performance. As a reward for its cooperation, the PU network allows the SU network to communicate simultaneously via the PU relay node by using the decode-and-forward protocol. The proposed system allows the transmission of four PU symbols and one SU symbol in four/three time slots resulting in a bandwidth efficiency of $1.25/1.67$ based on the cooperative scheme, respectively. Two power allocation optimization problems are formulated: the first problem minimizes the weighted sum of the average symbol error probability of both PU and SU systems, whereas the second problem maximizes the total achievable sum rate of the PU and SU networks. Lagrangian multiplier method is used to find the optimal solutions for both problems under the constraint of maximum allowable power budget. In addition, the paper investigates how the proposed model improves the PU physical layer security performance against a single passive eavesdropper. The results show that the error performance of the proposed relay selection model outperforms the conventional two-way relaying networks with AF protocol. Moreover, findings illustrate that the total achievable sum rate of the proposed relay elimination model is higher than the total achievable rate of the conventional two-way relaying model. From secrecy point of view, the proposed model is shown to achieve a nonzero secrecy rate that improves the PU system security against eavesdropping attacks. [ABSTRACT FROM AUTHOR]

In this paper, we consider the power-allocation problem in orthogonal frequency-division multiplexing (OFDM)-based bidirectional cognitive radio (CR) relay networks. A joint optimization under the amplify-and-forward (AF) relaying protocol is formulated to maximize the throughput of secondary users (SUs) via power loading over different subcarriers at the three (two transceivers and a relay) nodes. For compatibility with practical systems, separate power constraints are considered at each transmitting node. Furthermore, to provide high-level protection to primary users (PUs) in underlay CR transmission, per-subcarrier-based interference constraints are assumed. For tractability of the solution, we adopt a decomposition framework where the joint power optimization (JPO) is split into two subproblems. Later, each subproblem is solved by exploiting the convex optimization techniques. Moreover, a low-complexity suboptimal solution of the joint power allocation at all nodes is also proposed. Simulation results are presented to validate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

Transmit antenna selection (TAS) is most popular technique in underlay cognitive radio (CR) networks as they increase the capacity of secondary users with less hardware requirements. In this paper, a new scenario of CR ad-hoc network topology is proposed in which apart from primary users, there are multiple number of secondary users which are assumed to be distributed as homogeneous spatial Poisson point process (PPP) and are trying to use the primary spectrum in underlay mode. These multiple secondary transmitters generate the aggregate interference and can degrade the performance of secondary receiver. Here this aggregate interference is estimated and its impact on performance of secondary receiver under unconstrained mode of operation is presented. Further, to enhance the performance of secondary receivers in this scenario, single TAS technique based on maximizing the received signal to interference noise ratio by using optimum combining (OC) method is proposed. Furthermore, in this work the design of end to end Simulink based environment for secondary trans-receiver system with advancements in channel design and estimation is proposed. The bit error rate (BER) analysis is presented and verified for image data for single TAS-OC technique for unconstrained mode in underlay CR network in Rician fading channel. The BER performance is also presented for different number of secondary interference sources which are located at fixed distance in one case and they are assumed to be distributed as PPP in another case. [ABSTRACT FROM AUTHOR]

In a cognitive radio (CR) framework, the channel state information (CSI) feedback to the secondary transmitter (SU_Tx) can be limited or unavailable. Thus, the statistical model is adopted to determine system performance using the outage concept. In this paper, we adopt a new approach using multilayer-coding (MLC) strategy, i.e., broadcast approach, to enhance spectrum sharing over fading channels. First, we consider a scenario where the SU_Tx has no CSI of both the link between the SU_Tx and the primary receiver (cross link) and its own link. We show that using MLC improves the cognitive rate compared with the rate provided by a single-layer coding (SLC). In addition, we observe numerically that two-layer coding achieves most of the gain for Rayleigh fading. Second, we analyze a scenario where SU_Tx is provided by partial CSI about its link through quantized CSI. We compute its achievable rate, adopting the MLC and highlight the improvement over SLC. Finally, we study the case in which the cross link is perfect, i.e., a cooperative primary user setting, and compare the performance with the previous cases. We present asymptotic analysis at the high-power regime and show that the cooperation considerably enhances the cognitive rate at high values of the secondary power budget. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the bit error rate (BER) analysis of the scheduled transmit antenna selection (TAS) with maximal ratio combining (MRC) for the cognitive radio multiple-input multiple-output (CR-MIMO) systems. As a first step, this paper derives approximate probability density functions (PDFs) of the effective signal to noise ratio (SNR) of the proposed scheduled TAS with MRC in CR-MIMO systems. Next, the tight closed-form expressions of the BER for the M -ary QAM and M -ary PSK modulations are presented, respectively. Using asymptotic analysis, we approximate the BER for the scheduled system, and quantify the diversity order and SNR gain, respectively. Analytical results show that the diversity order of the scheduled system is the product of spatial diversity (SD) and multiuser diversity (MUD). Thus, BER performance of the proposed system is improved as the number of users increases by MUD regardless of modulation types. Also, the SNR gain is getting worse as the number of received antennas at the primary system increases regardless of modulation types. [ABSTRACT FROM AUTHOR]

In cooperative spectrum sensing (CSS), a multibit combination rule shows better sensing performance than one-bit hard combination rules at the sacrifice of the reporting overhead. To overcome the tradeoff between the sensing performance and the reporting overhead, we propose a novel group-based multibit CSS scheme with a limited reporting overhead. The proposed scheme adopts contention-based reporting to restrain the reporting overhead while achieving multiuser diversity with an increased number of secondary users (SUs). Moreover, SUs report one-bit sensing results to a fusion center instead of sending multibit quantization information, and the rest of the information is embedded in the time slot. The simulation results demonstrate that, as the number of SUs increases, the proposed scheme improves the sensing performance and the average throughput of SUs, whereas the conventional one-bit or multibit combination schemes show a tradeoff between the sensing performance and the throughput of SUs. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an on/off reporting mechanism for cooperative sensing of cognitive radio so that reporting overhead from secondary sensing users to a fusion center can be significantly reduced. A key advantage of our scheme is robust and energy-efficient cooperative sensing over imperfect reporting channels. Furthermore, ON/OFF reporting enables graceful degradation when sensing nodes fail during operation. We focus on hard decision of cooperative sensing with many energy detectors based on the Neyman–Pearson criterion. Instead of using the conventional and rule, we propose an iNOR rule that can achieve O(1) reporting overhead in total, irrespective of the number of sensing nodes. The asymptotic overhead value is given by P(\mathcal {H_{\mathrm{1}}})\mbox{log}(\frac{1}{\overline{P_{d}}}), where P(\mathcal {H_{\mathrm{1}}}) is the probability of primary user's presence and \overlinePd is the target detection probability. In addition, we show that the or rule also has its asymptotically negligible reporting overhead given by P(\mathcal {H\mathrm{1}})\mbox{log}(\frac{1}{1-\overlinePd}). Significant reduction in reporting overhead of ON/OFF reporting contributes to power saving, which in turn realizes robust reporting to fusion center by overcoming channel fading. Our simulation results show that with the proposed technique fusion center can make a reliable decision to avoid harmful interference to the primary user. [ABSTRACT FROM PUBLISHER]

Abstract Cognitive radio (CR) systems have emerged as effective tools for improving spectrum efficiency and meeting the growing demands of communication. This study focuses on a flexible CR system based on opportunistic spectrum access technology, which enables secondary networks to efficiently utilize unoccupied spectrum resources for information transmission by actively sensing the spectrum utilization of primary networks. Specifically, we introduce unmanned aerial vehicles (UAV) technology into the CR system to further enhance its flexibility and adaptability, which enables the transmission efficiency of low-altitude UAV networks. In this CR system, UAVs are employed for more flexible spectrum management. The objective of this research is to maximize the average achievable rate of SUs by jointly optimizing the trajectories of secondary UAV, the trajectories of primary UAV, the beamforming of secondary UAV, subchannel allocation and sensing time. To achieve this goal, we employ deep reinforcement learning (DRL) algorithms to optimize these variables. Compared to traditional optimization algorithms, DRL algorithms not only have lower computational complexity but also achieve faster convergence. To address the mixed-action space problem, we propose a Dueling DQN-Soft Actor Critic algorithm. Simulation results demonstrate that the proposed approach in this paper significantly enhances the performance of the CR system compared to traditional baseline schemes. This is manifested in higher spectrum efficiency and data transmission rates, while minimizing interference with the primary network. This innovative research combines drone technology and DRL algorithms, bringing new opportunities and challenges to the future development of cognitive communication systems.

Intelligent reflecting surface (IRS) technology has found extensive application in the wireless communication domain, offering significant enhancements in communication performance by manipulating the reflection of electromagnetic waves. This research article delves into the domain of UAV-assisted wideband cognitive radio networks augmented by IRS and underpinned by sensing-based spectrum sharing techniques. We introduce UAVs as alternative solutions for both primary and secondary base stations to optimize the management of spectral resources. Our primary objective centers around the joint optimization of both the trajectories of the primary and secondary UAVs, power allocation at the secondary UAVs, reflection coefficients of intelligent reflecting surfaces, sensing time, and subcarrier allocation, all aimed at maximizing the achievable rate of secondary users. Given that the problem at hand is non-convex, we employ deep reinforcement learning algorithms for resolution. To address the challenge of mixed-action spaces, we implement a novel Dueling DQN-Twin Delayed Deep Deterministic policy gradient (DDQN-TD3) algorithm. The simulation outcomes illustrate that the methodology introduced in this paper substantially amplifies the performance of CR system when contrasted with benchmark methods. This is evident in the improved spectrum efficiency, elevated data transmission rates, and the minimization of interference with the primary network. [ABSTRACT FROM AUTHOR]

We study the application of spatial modulation (SM) in overlay cognitive radio (CR) networks, in which the primary and secondary networks work concurrently over the same spectrum band. We assume that the direct link between the primary transmitter and receiver is not available, i.e. broken, and that the CR transmitter assists the primary network as a relay to amplify-and-forward the transmitted symbols of the primary. SM is used in the secondary to split the transmission space into two amplitude-phase modulation (APM) and spatial domains. In the proposed scheme, the secondary transmitter retransmits the primary symbols in APM domain, while its own information is transmitted by the index of transmitting antenna, similar to space shift keying, without causing any interference to the primary receiver. We analyze the performance of the optimal detectors at both the primary and secondary receivers for the case of phase shift keying modulation in terms of the average symbol error rate (ASER). We also study the asymptotic behavior of the ASER at both the primary and secondary at high signal-to-noise ratios. Simulation results show that the SM can be effectively used in overlay CR systems. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is a promising technology to alleviate spectrum shortage and satisfy the huge demand of bandwidth for multimedia streaming in future mobile computing systems. The inherent features of CR pose tough challenges in provisioning quality of service (QoS) for acceptable user experience and minimizing energy consumption for multimedia transmissions. In this paper, scalable video coding and transmission rate adaptation are jointly considered in an energy-efficient scheme for transmissions of streaming media over CR with QoS guarantee. An event-driven discrete-time Markov control process model is introduced to formulate the QoS-guaranteed energy-efficient transmission problem as a constrained stochastic optimization problem. Based on estimations of potentials and the difference between performance measurement and QoS requirement, an online policy iteration algorithm is proposed to optimize energy consumption under QoS constraints directly. By exploiting the system dynamics, this algorithm does not depend on any prior knowledge of channel availability or fading statistics, and it can converge to a near optimum with a low computational burden. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Cognitive Radio (CR) is a promising and potential technique to enable secondary users (SUs) or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs) or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS). In this paper, a distributed dynamic load balanced clustering (DDLBC) algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH) through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP) model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm. [ABSTRACT FROM AUTHOR]

In hardware-constrained cognitive radio (CR) ad hoc networks, secondary users (SUs) with limited sensing capabilities strive to discover and share available spectrum resources without impairing primary-user (PU) transmission. Sensing strategy design objectives include high CR network throughput, resolved SU competition, distributed implementation, and reliable performance under node mobility. However, these objectives have not been realized by previously investigated sensing strategies. A novel sensing strategy is analyzed, where the reward is adapted to the SU-link channel state information (CSI) prior to sensing, thus randomizing sensing decisions and boosting the network throughput. Moreover, CSI-aided sensing is combined with a novel first-come-first-served (FCFS) medium access control (MAC) scheme that resolves SU competition prior to sensing. Finally, a pilot-based CSI prediction method is developed to enable the proposed CSI-aided sensing strategies for mobile scenarios. Analytical and numerical results demonstrate that the proposed sensing and access methods significantly outperform nonadaptive sensing strategies for practical mobile CR scenarios with CSI mismatch and pilot overhead. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) is introduced to improve spectrum efficiency by unlicensed usage when a licensed band is idle. These devices monitor licensed users to find spectral opportunities for transmission. A cognitive radio network (CRN) is defined as a structure, which is constructed by both licensed users and unlicensed CR users. In an effort to improve spectrum efficiency, CR users' spectrum issues have been widely studied over the last few years. However, the existing solutions are not capable of dealing with the following scenario: multiple CRNs operating simultaneously without a centralized coordinator. This issue is often referred to as a coexistence problem of heterogeneous CRNs. This problem is caused in a distributed framework of CRNs without a centralized component to negotiate spectrum usages with one another. The system characteristics of these heterogeneous networks are different; thus, the fairness issue between CR users must be considered. In this paper, a decentralized solution that does not limit the hardware capacity of a CR device is proposed as an added fairness feature. Several Markov chain models are proposed to study these unfairness conditions, and a medium access control layer approach is introduced. Numerical and simulation results are presented to verify the proposed solution. [ABSTRACT FROM PUBLISHER]

In this paper, we develop a cognitive radio (CR)-based architecture for fourth generation (4G) users that provides real-time delivery of service to its applications through the intelligent assignment of the CR spectrum. CRs work in an unlicensed network setting, so it is important that cognitive users utilize the spectrum opportunistically, i.e., without interrupting the licensed user's activity. To provide the opportunistic access for a cognitive 4G user, we propose an architecture that delivers the desired solution by following a novel five-step process. First, the cognitive (or secondary) user relays its throughput requirements from the application layer down to the media access layer by way of cross-layering. Second, the media access layer at its end senses the licensed spectrum and, based on the sensed parameters, characterizes the licensed (or primary) user's amount of spectrum occupancy into three different occupancy level types. Third, the licensed user's spectrum occupancy, categorized into three levels, is statistically represented by setting up a Markov model that evaluates the probability that the licensed channel could be found in a particular state at a given time instant for each level. Fourth, to provide opportunistic spectrum access to the secondary user, an optimization strategy is devised in the media access control layer that will bring face to face the throughput requirements obtained from the application layer and the steady-state probabilities for the licensed channel from the physical layer. Fifth, optimal performance metrics concerning the 4G user throughput and power are attained by solving the optimization problem. Results obtained are simulated against a variety of network parameters, and performance improvement through the proposed scheme is assessed by simulations conducted for a long-term evolution (LTE) system. [ABSTRACT FROM PUBLISHER]

This paper presents an experimental quantitative analysis of the dynamic behavior of very high frequency (VHF) III at 174-230 MHz band for opportunistic access in Malaysia. In order to investigate the variations of the VHF channels with respect to all operating stations in the country, measurements were conducted at two locations, namely, Malaysian Institute of Microelectronic Systems and University of Tenaga Nasional, Malaysia. The experimental result shows that the overall spectrum utilization for the two locations is just about 32 and 7 % respectively. These experimental results reflect a low utilization of the VHF spectrum band which consequentially indicates the ample availability of TV white space which can be utilized via opportunistic access for services like the Internet and other services. Primarily, this work is an attempt to obtain a set of generic reference values for evaluation of spectrum usage, which can be used for other potential bands for the future deployment of secondary user applications in Malaysia. It also provides useful information to the regulator in considering the deployment of opportunistic spectrum access, which can significantly impact both economic and social communication in the country. [ABSTRACT FROM AUTHOR]

Sensitivity and sensing time are the key features for spectrum sensing in a cognitive radio (CR) which detects empty bands within VHF/UHF television broadcast bands and uses them as a secondary user. In this paper, an integrated CMOS CR spectrum sensor for a CR receiver in the 54–862 MHz band is presented. A quasi-cyclostationary feature (QCF) detector is proposed based on both energy and feature detection methods and can take advantage of both methods to reach a fast and accurate decision without the need for an analog-to-digital converter for decision making. The integrated chip has been fabricated in a standard 0.18\mathchar"702D\mu\ m CMOS IBM technology and has achieved minimum detection signal-to-noise ratio of as low as -24~\ dB and dynamic range (DR) of 39 dB. [ABSTRACT FROM PUBLISHER]

The cognitive ability of Cognitive Radio (CR) can adjust appropriate transmission parameters according to different channel conditions and adapt to dynamic communication environments. Channel quality evaluation is a key technology of adaptive communication systems, and its real-time evaluation results provide a direct basis for adaptive communication transmission scheme switching. So it is necessary to study the estimation algorithms of signal-to-noise ratio (SNR). Several SNR estimation algorithms based on additive white Gaussian noise channel (AWGN) are studied in this paper, analyze and compare through theoretical derivation and computer simulation. The simulation results of the computer MATLAB software show that the algorithm introduced in the article has a high estimation accuracy in the entire range of the SNR simulation interval of 0 to 15dB, and can accurately reflect the current channel conditions to facilitate the CR system adjusts the communication strategy in time, provides a certain reference basis for CR channel estimation decision-making. [ABSTRACT FROM AUTHOR]

Abstract With the birth of the IoT era, it is evident that the existing number of devices is going to rise exponentially. Any two devices will communicate with each other using the same frequency band with limited availability. Therefore, it is of vital importance that this frequency band used for communication be used efficiently to accommodate the maximum number of devices with the available radio resources. Cognitive radio (CR) technology serves this exact purpose. The stated one is an intelligent radio that is made to automatically identify the optimal wireless channel in the available wireless spectrum at a given instant. An important functionality of CR is spectrum sensing. Energy detection is a very popular algorithm used for spectrum sensing in CR technology for efficient allocation of radio resources to the devices intended to communicate with each other. Energy detection detects the presence of a primary user (PU) signal by continuously monitoring a selected frequency bandwidth. The conventional energy detection technique is known to perform poorly in lower SNR ranges. This paper works towards the improvement of the energy detection algorithm with the help of machine learning (ML). The ML model uses the general properties of the signal as training data and classifies between a PU signal and noise at very low SNR ranges (− 25 to − 10 dB). In this research, a K-nearest neighbours (KNN) model is selected for its versatility and simplicity. Upon testing the model with an out-of-sample dataset, the KNN model produced a detection accuracy of 94.5%.

A new ultra-wideband (UWB) dielectric resonator antenna (DRA) integrated with a reconfigurable narrowband (NB) antenna is designed and analyzed for cognitive radio (CR) applications. The UWB antenna consists of a rectangular dielectric resonator which is fed by a microstrip line. The NB antenna composes of a rectangular ring patch and three stubs which is fed by a microstrip line. The UWB and reconfigurable NB antennas provide 2:1 VSWR bandwidth from 3 to 11 GHz and from (3.25 to 3.7 GHz, 5.5 to 6.5 GHz, and 8 to 8.4 GHz), respectively. There is a reasonable isolation between the antennas. The narrowband reconfigurability is achieved by two p-i-n diode switches within the antenna structure. A prototype of the integrated antenna was fabricated and its performance was verified. The dimensions of the antenna are 65 mm × 40 mm × 6.5 mm. The antenna represents good radiation characteristics. Also, in order to reduce mutual coupling, the space between the ground planes is 10 mm. [ABSTRACT FROM AUTHOR]

The sudden outbreak of the novel coronavirus disease in 2019, known as COVID-19 has impacted the entire globe and has forced governments of various countries to a partial or full lockdown in the fear of the rapid spread of this disease. The major lesson learned from this pandemic is that there is a need to implement a robust system by using non-pharmaceutical interventions for the prevention and control of new contagious viruses. This goal can be achieved using the platform of the Internet of Things (IoT) because of its seamless connectivity and ubiquitous sensing ability. This technology-enabled healthcare sector is helpful to monitor COVID-19 patients properly by adopting an interconnected network. IoT is useful for improving patient satisfaction by reducing the rate of readmission in the hospital. The presented work discusses the applications and technologies of IoT like smart and wearable devices, drones, and robots which are used in healthcare systems to tackle the Coronavirus pandemic This paper focuses on applications of cognitive radio-based IoT for medical applications, which is referred to as "Cognitive Internet of Medical Things" (CIoMT). CIoMT is a disruptive and promising technology for dynamic monitoring, tracking, rapid diagnosis, and control of pandemics and to stop the spread of the virus. This paper explores the role of the CIoMT in the health domain, especially during pandemics, and also discusses the associated challenges and research directions. [ABSTRACT FROM AUTHOR]

The development in wireless communication, along with various applications, has put so many limitations on the use of radio spectrum. When we look at spectrum utilization, most of the times, the radio spectrum is not used properly. Some of the frequency bands in the spectrum are unoccupied, some frequency bands are less occupied, and a few bands are heavily occupied. Cognitive radio is the novel concept which can successfully deal with the growing demand and scarcity of wireless spectrum by effectively utilizing the unoccupied frequency bands. Cognitive radio is an intelligent wireless architecture which searches the spectrum holes and allows unlicensed users to access licensed spectrum bands. Spectrum sensing is used to detect the spectrum holes, providing high spectrum resolution capability. We have generated an experimental model of cognitive radio system using MATLAB. In this paper, we delve into the idea of simulating cognitive radio system for effective utilization of vacant frequency bands. The performance of cognitive radio has been tested using MATLAB R2012a. [ABSTRACT FROM AUTHOR]

A robust and secure database for spectrum sharing in cognitive radio networks that is obscured from the viewpoint of secondary users is presented. The database allocations secure features of white space resource usage from being learned. The design of non-inferable database is based on two cases. In the first case, the primary or spectrum lender has no knowledge of secondary users or potential jammers among them. In this case, the problem is modeled as a Markov decision process. In the second case, the primary system has some knowledge about spectrum borrowers and the problem is modeled as a Bayesian Stackelberg game. Mutual information interpretation of the Bayesian Stackelberg game is also presented. The solutions facilitate releasing more bandwidth as required by US National Broadband Plan. Applications of this scheme are manifold. This design can be used for securing spectrum resources, for example radar white spaces, while being shared with LTE and commercial communication systems. Further, it provides jammer-proof spectrum sharing among various communication, detection, and navigation systems. Simulation results verify this scheme improves system throughput while maintaining desired obfuscation level or entropy. [ABSTRACT FROM PUBLISHER]

The problem of joint precoder design for the source and relay nodes of a cooperative cognitive radio (CR) system is investigated. We consider a non-regenerative relaying secondary CR system with underlay spectrum sharing methodology with the primary users. Based on an expression for the achievable throughput of secondary system, we develop an optimization problem to maximize the throughput subject to power constraints at the secondary source and relay, and an interference power constraint at the primary due to secondary source and relay transmission. First, we derive the structure of each of the relay and source precoding matrices separately assuming the other is known. Then, we propose an iterative technique to jointly design the source and relay precoding matrices. The results are also extended to the case where the direct source-destination link is available. Through simulation, we demonstrate the effectiveness of our proposed approach in improving the achievable throughput, and compare its performance with that of numerical optimization, source only precoding, relay only precoding, and a naive amplify-and-forward method. [ABSTRACT FROM PUBLISHER]

This paper presents a design of linear-phase, low-complexity, reconfigurable digital filter bank that offers independent and complete control over the bandwidth as well as the center frequency of all subbands. The proposed filter bank is designed by integrating spectral parameter approximation (SPA) technique with the modified coefficient decimation method (MCDM), referred to as SPA-MCDM-FB. The architectural details, design examples and complexity comparisons show that the SPA-MCDM-FB is easy to design and offers substantial savings in gate count, number of variable multipliers and group delay over other filter banks. Moreover, these savings increase further with the increase in the filter-bank resolution (i.e., number of subbands). The SPA-MCDM-FB is then combined with the upper confidence bound (UCB)-based decision-making algorithm to search the vacant band(s) of any desired bandwidth for spectrum-sensing application in cognitive radio (CR). The simulations results verify that the proposed scheme offers superior performance [i.e., improved utilization of vacant subband(s)] and needs fewer gate counts compared to uniform filter bank and UCB-algorithm-based schemes. Furthermore, the functionality and advantages of the SPA-MCDM-FB are also verified for the channelization operation in CR supporting multiple communication standards. [ABSTRACT FROM AUTHOR]

The most commonly used spectrum sensing techniques in cognitive radio (CR) networks, such as the energy detector (ED), matched filter (MF), and others, suffer from the noise uncertainty and signal-to-noise ratio (SNR) wall phenomenon. These detectors cannot achieve the required signal detection performance regardless of the sensing time. In this paper, we explore a signal processing scheme, namely, the generalized detector (GD) constructed based on the generalized approach to signal processing (GASP) in noise, in spectrum sensing of CR network based on antenna array with the purpose to alleviate the SNR wall problem and improve the signal detection robustness under the low SNR. The simulation results confirm our theoretical issues and effectiveness of GD implementation in CR networks based on antenna array. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) system is able to exploit the bands allocated to licensed or primary users when they are not being used. Spectrum sensing is a key element of a working CR system. In this paper, enhanced algorithms are proposed for semi-blind spectrum sensing in CR networks using fourth-order statistics of the received primary user's signal. The proposed statistic will have a value equal or close to 3 when only Gaussian noise samples exist in the received signal. This estimate is used to differentiate between the presence or absence of the primary user by comparing with a predefined threshold. Using the Neyman-Pearson criterion, an optimized threshold is established and an analytical expression for the upper bound on the average probability of miss-detection $$(P_{m,avg})$$ is also derived. The proposed algorithm clearly outperforms the energy detection (ED) method over the low-SNR range of $$-15$$ to $$12$$ dB. For $$P_{m,avg} = 10^{-2}$$ , e.g., the proposed scheme outperforms the ED method by 1.5 dB for the case of a single user. Moreover, the proposed algorithm has been extended to the cooperative spectrum sensing model. Simulation results show that the proposed scheme significantly outperforms the ED method in cooperative spectrum sensing scenarios. [ABSTRACT FROM AUTHOR]

In this paper, several data fusion and soft decision fusion methods are proposed for cooperative automatic modulation classification (AMC) by using multiple sensors. A well-known AMC using fourth-order cumulant is considered. Also, a novel joint cumulant estimate correction is proposed. The AMC performance of proposed fusion methods with and without joint estimate correction is evaluated through the extensive Monte Carlo trials for different multipath fading channels, sensor spatial distributions, and application scenarios, and compared to those of the existing methods. Numerical results have confirmed huge performance improvement achievable with here proposed methods, especially in the non-idealized application scenarios. [ABSTRACT FROM AUTHOR]

Non-Orthogonal multiple access (NOMA) and Cognitive radio (Cr) are seen as one of the most promising techniques, which improves the utilization of the spectrum in 5G. The expanding number of wireless applications like new gadgets, IOT brought about developing a block in the ISM groups. The FCC requested to permit unlicensed clients to work in the void area without obstruction to an authorized guest. Cr gives an answer for an extra range prerequisite issue for productive spectrum usage. The foremost condition for permitting CRs to utilize spectrum is not causing obstruction to licensed users. Spectrum sensing permit secondary users (Su) to separately recognize the idle portions of the spectrum, and thus evade obstruction to licensed users. In existing spectrum sensing techniques, SU can only utilize the unused spectrum when PU is not present. Therefore, spectrum exploitation of the conventional system is very low. In recent times NOMA has been projected to utilize the spectrum in an efficient manner. The proposed work permits the SU to utilize a spectrum of PU, both at its absence. Spectrum sensing in NOMA is not explored so far. Hence, in this paper, NOMA based matched filter detection is designed for QAM-64 and QAM-256. Matlab simulation is applied to study the operation of the proposed detection technique in NOMA in respect of several parameters like bit error rate (BER) Vs signal to noise ratio (SNR), the probability of detection (Pd), and probability of false alarm (Pfa). [ABSTRACT FROM AUTHOR]

The main goals of all new technologies nowadays are utilizing the available spectrum, increasing spectrum efficiency, and increasing the throughput. Cognitive radio (CR) technology can provide efficient spectrum utilization and maximize the throughput using dynamic spectrum access technique. A new medium access control (MAC) protocol is needed for CR users to access the spectrum dynamically and to maintain fairness between users. In this paper, our objective is to enhance the overall network throughput, by enhancing SMART-V MAC protocol to support D-OFDM technology. A new channel assignment scheme called SMART-O based on these two technologies is proposed. The proposed algorithm greatly increased the overall throughput of the network and solved the channel assignment and rate optimization problems. Simulation results exposed the improvement of our work compared to previous algorithms. [ABSTRACT FROM AUTHOR]

Radio spectrum is a scarce and precious natural resource that is significantly underutilized with current spectrum licensing policies. Out of the 7 GHz of spectrum from 57 to 64 GHz, only little is used and the rest is underused. To address this problem, Cognitive Radio (CR) has emerged as a big possibility. It accesses the unused frequency bands (white spaces) for data transfer without interfering with the Primary User (PU). The CR users can access the spectrum when the PU is not using the spectrum. Thus spectrum sensing is of major importance in CR networks. When a PU is transmitting inside the sensing range of a CR, the CR cannot use the primary channel. But when the PU is outside the sensing range of the Secondary User (SU), it still senses and does not transmit signals, even when the channel is free. This leads to false alarm. In this paper, the false alarm probability is calculated. The negative error rate and the symbol error probability are also calculated. [ABSTRACT FROM AUTHOR]

Cognitive radio (CR) and energy-efficient design have emerged as two promising techniques to achieve high spectrum efficiency (SE) and energy efficiency (EE), respectively. In this paper, we study energy-efficient opportunistic spectrum access strategies for an orthogonal frequency division multiplexing (OFDM)-based CR network with multiple secondary users (SUs). Both worst EE and average EE are considered and optimized for different emphases and application scenarios. Since the original optimization issues belong to nonconvex integer combinatorial fractional program and are essentially NP-hard for an optimal solution, we use continuous and convex relaxation to modify the problems for somewhat better mathematical tractability. For the relaxed worst-EE-based spectrum access problem, we first demonstrate the joint quasiconcavity of EE on subchannel and power allocation matrices and then develop a framework to find the optimal solution based on efficient root finding and convex optimization. We also develop a low-complexity alternative for suboptimal solution. The relaxed average-EE-based spectrum access problem is still NP-hard and may have many local optima. We first transform the problem into an equivalent form and introduce a general concave envelope based branch-and-bound (B&B) approach to find the global optimal solution. We then exploit the underlying properties of the energy-efficient transmission to speed up the convergence of the B&B approach. Besides, we develop a low-complexity heuristic approach to find a suboptimal solution. Simulation results show that the energy-efficient spectrum access strategies significantly boost EE compared with the conventional spectral-efficient spectrum access ones while the low-complexity suboptimal approaches can well balance the performance and complexity. [ABSTRACT FROM AUTHOR]

Spectrum sensing is an important issue of cognitive radio(CR), the complexity of which can be efficiently reduced by introducing spectrum pooling strategy. Because of the intrinsic sparsity of specrum pool the payoff of spectrum sensing can be increasingly decreased by employing compressed sensing technique. In this paper a wideband compressed spectrum sensing(CSS) method based on spectrum pooling edge detection is derived. The mathematic connection of the compressed sampling signal and the spectrum pooling edge was firstly analyzed, based on which the CSS model of wideband spectrum sensing was established in this paper. At last, analysis and simulation results show that this method achieves better detection performance and costs lower computing resource than edge detection based CS spectrum sensing method. [ABSTRACT FROM AUTHOR]