Cognitive Jammers Assisted Covert Communication in Cognitive Radio Networks

In this work,we investigate the covert communication in cognitive radio(CR)networks with the existence of multiple cognitive jammers(CJs).Specifically,the secondary transmitter(ST)helps the primary transmitter(PT)to relay information to primary receiver(PR),as a reward,the ST can use PT's spectrum to transmit private information against the eavesdropper(Eve)under the help of one selected cognitive jammer(CJ).Meanwhile,we propose three jammer-selection schemes,namely,link-oriented jammer selection(LJS),min-max jammer selection(MMJS)and random jammer selection(RJS).For each scheme,we analyze the average covert throughput(ACT)and covert outage probability(COP).Our simulation results show that CJ is helpful to ST's covert communication,the expected minimum detection error probability and ACT can be significantly improved with the increase of false alarm of CJ.Moreover,the LJS scheme achieves best performance in ACT and COP,followed by RJS scheme,and MMJS scheme shows the worst performance.

Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio network.The threshold identification method is implemented in the received signal at the secondary user based on the square law.The proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division multiplexing.Additionally,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio systems.In the dynamic threshold,the signal ratio-based threshold is fixed.The threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and MBWO.The general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user signal.These limitations undermine the sensing accuracy of the energy identification technique.Hence,the ETBED technique is developed to enhance the energy efficiency of cognitive radio networks.The projected approach is executed and analyzed with performance and comparison analysis.The proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.

Radio resource management in energy harvesting cooperative cognitive UAV assisted IoT networks:A multi-objective approach

Cooperative communication through energy harvested relays in Cognitive Internet of Things(CIoT)has been envisioned as a promising solution to support massive connectivity of Cognitive Radio(CR)based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems.In this work,a cooperative CIoT system is contemplated,in which a source acts as a satellite,communicating with multiple CIoT devices over numerous relays.Unmanned Aerial Vehicles(UAVs)are used as relays,which are equipped with onboard Energy Harvesting(EH)facility.We adopted a Power Splitting(PS)method for EH at relays,which are harvested from the Radio frequency(RF)signals.In conjunction with this,the Decode and Forward(DF)relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices.We developed a Multi-Objective Optimization(MOO)framework for joint optimization of source power allocation,CIoT device selection,UAV relay assignment,and PS ratio determination.We formulated three objectives:maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission.The MOO formulation is a Mixed-Integer Non-Linear Programming(MINLP)problem,which is challenging to solve.To address the joint optimization problem for an epsilon optimal solution,an Outer Approximation Algorithm(OAA)is proposed with reduced complexity.The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search(NOMAD)algorithm.

Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios

Spectrum sensing is a key technology for cognitive radios.We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classification.We normalize the received signal power to overcome the effects of noise power uncertainty.We train the model with as many types of signals as possible as well as noise data to enable the trained network model to adapt to untrained new signals.We also use transfer learning strategies to improve the performance for real-world signals.Extensive experiments are conducted to evaluate the performance of this method.The simulation results show that the proposed method performs better than two traditional spectrum sensing methods,i.e.,maximum-minimum eigenvalue ratio-based method and frequency domain entropy-based method.In addition,the experimental results of the new untrained signal types show that our method can adapt to the detection of these new signals.Furthermore,the real-world signal detection experiment results show that the detection performance can be further improved by transfer learning.Finally,experiments under colored noise show that our proposed method has superior detection performance under colored noise,while the traditional methods have a significant performance degradation,which further validate the superiority of our method.

Cooperative Spectrum Sensing Exploiting a Certain Number of CR Users Based on Multi- Antennas in Cognitive Radio Networks

In this paper,a cooperative spectrum sensing scheme,which is based on cooperation of a certain number of secondary users and cooperative diversity under multi-antenna scenario,is proposed.Under multi-antenna scenario,we set a targeted detection probability and optimize the false alarm probability of the network by choosing a certain number of secondary users with the highest primary user’s signal to noise ratio.The detection performance of the network is also evaluated when all the secondary users are cooperating to illustrate the benefits of the proposed scheme as a contrast.In addition,how to choose the detection threshold of the secondary user is analyzed for the purpose of decreasing the average risk.Theory analysis and simulation results show that the optimum false alarm probability can be derived by cooperating a certain number of secondary users rather than all the secondary users and the detection performance of the network can be further improved if secondary users are equipped with multiple antennas.Also,a minimum average risk can be obtained by optimizing the detection threshold.

NOVEL POWER CONTROL GAME VIA PRICING ALGORITHM FOR COGNITIVE RADIOS

To compensate the service providers who have paid billions of dollars to use spectrum and to satisfy secondary users' requirements in cognitive radios, a Non-cooperative Power Control Game and Pricing algorithm (NPGP) is proposed. Simulation results show that the proposed algorithm can regulate the secondary users' transmitter powers, optimally allocate radio resource and increase the total throughput effectively.

Impacts of feedback delay and estimation error on secrecy performance of MISO single eavesdropper cognitive radio networks

Due to the broadcast nature of wireless transmission medium,security threats may hinder propagation of cognitive radio systems for commercial and military data application. This paper sets a channel error analytical framework and studies the joint impact of estimation errors and feedback delay on secrecy performance in cognitive radio networks. Under the assumption that system applies beamforming and jamming scheme,a multi-antenna cognitive base station( CBS) sends confidential signals to a secondary user( SU) in the presence of M primary users( PUs) and an eavesdropper. Assuming only imperfect channel state information( CSI) about the receivers is available,secrecy rate,outage probability,secrecy throughput are deduced to obtain a closed-form expression. It is shown that while the transmit power increases,secrecy throughput would reach to a constant. Simulation results show that feedback delay adversely impacts on secrecy rate,connection outage probability and secrecy throughput,while estimation error causes more impact on secrecy outage probability. Furthermore,the secrecy rate could increase progressively with the transmit power only if there exists no feedback delay.

Multi-criteria user selection scheme for learning-based multiuser MIMO cognitive radio networks

For multiuser multiple-input-multiple-output （MIMO） cognitive radio （CR） networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information （ CSI ） between primary （PR） terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.

A novel mechanism based on Nash bargaining for primary system game in cognitive radios

According to the utility function and spectrum demand of the cognitive users,a novel mechanism based on Nash bargaining for primary system game was proposed under the wireless environment of Rayleigh fading.On the basis of this mechanism,we proposed a new distributed bargaining algorithm based on Nash product;then the spectrum prices and system utilities were obtained.Theoretical analysis results showed that with a close total utility to the optimal,the Nash bargaining mechanism cannot only improve the fairness between primary systems remarkably,but also reach to the stable equilibrium in finitely repeated games.Finally,simulation results were given to demonstrate the correctness of these conclusions and the efficiency of the algorithm.

Weighted Sum Rate Maximization in OFDM Based Cooperative Cognitive Radios: A Joint Optimization Approach

Improving utilization of the radio spectrum is the main goal of Cognitive Radio Networks (CRN). Recent studies made use of cooperative relay technology in cognitive networks, to increase transmission diversity gain. In this paper we consider an OFDM based cooperative cognitive network with a pair of Source-Destination nodes as the primary user (PU), and a pair of Source-Destination nodes—which is assisted with a relay—as the secondary (cognitive) user (SU). Both primary and secondary users share a same spectrum. In a two hop transmission, the source transmits in the first hop, and the half-duplex relay decodes the message, re-encodes and forwards it to the destination in the second hop on a different subcarrier. The cognitive network obeys an underlay paradigm where the SU is allowed to transmit simultaneously with PU, while its power is limited such that the interference caused for PU does not exceed a defined temperature. Under this constraint, a joint subcarrier pairing and power allocation is proposed for SU to maximize its weighted sum rate. The problem is transformed to a convex optimization problem and solved in the dual domain. Then an algorithm to achieve feasible solutions is used based on the optimization results. Through extensive simulations, we compare the spectrum utilization of the proposed approach with the existing ones, and show that interestingly the proposed method improves the weighted sum rate of SU.

A parallel algorithm for statistical-fairness-based spectrum allocation of cognitive radios

A parallel algorithm for statistical-fairness-based spectrum allocation of cognitive radios is proposedin this paper. The key idea of the algorithm is to pursue the maximum total spectrum utilization of thesystem by adopting a parallel technique in every spectrum allocation, and to ensure the statistical fairnessrule by deploying a particular scheme during a series of allocations. The simulation results show that theproposed algorithm not only achieves a fairer and more efficient allocation of spectrum resources, but alsohas much shorter allocation duration than the color sensitive graph coloring (CSGC) algorithm.

Improving the Reliability of Unmanned Aircraft System Wireless Communications through Cognitive Radio Technology

Unmanned Aircraft System networks are a special type of networks where high speeds of the nodes, long distances and radio spectrum scarcity pose a number of challenges. In these networks, the strength of the transmitted/received signals varies due to jamming, multipath propagation, and the changing distance among nodes. High speeds cause another problem, Doppler Effect, which produces a shifting of the central frequency of the signal at the receiver. In this paper we discuss a modular system based on cognitive to enhance the reliability of UAS networks.

A Novel Scheme with Adaptive Sampling for Better Spectrum Utilization in Cognitive Radios

In cognitive radio (CR) networks, cognitive users need continuously monitor spectrum to decrease or avoid interference to primary users, yet attain a reasonable throughput. In this paper, we exploit a scheme to dynamically change the detection time duration to gain maximum throughput. Meanwhile the average de-tection time is kept as small as possible. The advantages of our approaches are approved by the deductions. Also the simulation results enable us to recognize the improved performance of our scheme over those ones with fixed detection time assignment.

SPECTRUM SHARING IN ITERATED PRISONER'S DILEMMA GAME BASED ON EVOLUTIONARY STRATEGIES FOR COGNITIVE RADIOS

We study a spectrum sharing problem where multiple systems coexist and interfere with each other. First, an analysis is proposed for distributed spectrum sharing based on Prisoners' Dilemma (PD) in Cognitive Radios (CRs). In one-shot game, selfish and rational CRs greedily full spread their own spectrum space in order to maximize their own rates, which leads to Nash Equilibrium (N.E.). But with long term interaction, i.e., Iterated Prisoner's Dilemma (IPD), CRs can come to cooperate and acquire the social optimal point by using different evolutionary strategies such as Tit For Tat (TFT), Generous TFT (GTFT), etc. Also we compare the performances of the different evolutionary strategies in noise-free and noisy environments for two-player games. Finally, N-player IPD (N-IPD) is simulated to verify our conclusions that TFT is a good strategy for spectrum sharing in CRs.

User-Based Discrete-Time Queuing Analysis for Opportunistic Spectrum Access in Cognitive Radio Networks

In cognitive radio networks, the spectrum utilization can be improved by cognitive users opportunistically using the idle channels licensed to the primary users. However, the new arrived cognitive users may not be able to use the channel immediately since the channel usage state is random. This will impose additional time delay for the cognitive users. Excessive waiting delay can make cognitive users miss the spectrum access chances. In this paper, a discrete-time Markov queuing model from a macro point of view is provided. Through the matrix-geometric solution theory, the average sojourn time for cognitive users in the steady state before accessing the spectrum is obtained. Given the tolerant delay of cognitive users, the macro-based throughput is derived and an access control mechanism is proposed. The numerical results show the effects of service completion probability on average sojourn time and throughput. It is confirmed that the throughput can be obviously improved by using the proposed access control mechanism. Finally, the performance evaluations based on users are compared to that based on data packets.

ADAPTIVE MODULATION AND POWER CONTROL FOR THROUGHPUT ENHANCEMENT IN COGNITIVE RADIOS

To regulate the transmit-power and enhance the total throughput, a novel Transmit Power Control Game (TPCG) algorithm and an adaptive Modulation TPCG (M-TPCG) algorithm which combine bandwidth allocation, adaptive modulation and transmit-power control based on Space Time Block Coding (STBC) OFDM-CDMA system are designed and a cross-layer framework of database sharing is proposed. Simulation results show that the TPCG algorithm can regulate their transmitter powers and enhance the total throughput effectively, M-TPCG algorithm can achieve maximal system throughput. The performance of the cognitive radio system is improved obviously.

Downlink/Uplink Identification of Time-Division Duplexing-OFDMA Systems for Cognitive Radios

When coexisting with dual-link primary systems,secondary systems in cognitive radios should first distinguish between the primary downlinks and uplinks in order to efficiently explore their respective spectrum opportunities.Because of the assumptive prior knowledge about the time-frequency locations of primary downlinks and uplinks,this procedure is usually not considered in the design of cognitive radios.In this paper,a cooperative method is proposed for the downlink/uplink identification of time-division duplex-based orthogonal frequency-division multiple access systems.In this method,the power level of the primary link is extracted as the key feature,which also contributes to the subsequent cognitive behaviours.The effects of the primary and secondary systems and the effects of the detection parameters on the identification accuracy are all analysed in detail.The simulation results show that the proposed method can identify the primary links precisely and quickly with low complexity.

Optimization of QoS Parameters in Cognitive Radio Using Combination of Two Crossover Methods in Genetic Algorithm

Radio Cognitive (RC) is the new concept introduced to improve spectrum utilization in wireless communication and present important research field to resolve the spectrum scarcity problem. The powerful ability of CR to change and adapt its transmit parameters according to environmental sensed parameters, makes CR as the leading technology to manage spectrum allocation and respond to QoS provisioning. In this paper, we assume that the radio environment has been sensed and that the SU specifies QoS requirements of the wireless application. We use genetic algorithm (GA) and propose crossover method called Combined Single-Heuristic Crossover. The weighted sum multi-objective approach is used to combine performance objectives functions discussed in this paper and BER approximate formula is considered.

QoS-based MAC protocol for cognitive radio networks

In order to improve the throughput performance of the secondary users （SUs） in the cognitive radio （CR） environment, a quality of service （QoS） based media access control （MAC） protocol is proposed. In this protocol, the CR node maps the channel state as a vector, and the transmitter and the receiver obtain the final channel map through an AND operation to prepare for an optional channel set. Data from the upper application layer are classified into two priority levels according to the QoS requirement. The data of each level relate to different contention windows so that the priority of real time data can be guaranteed. A two-dimensional discrete-time Markov chain is utilized to evaluate the system performance, and mathematical expressions of the system throughput are derived. Simulation results show that compared with the IEEE 802. 11 distributed coordination function （DCF）, the proposed MAC protocol can achieve higher throughput.

Narrowband interference suppression in TR-UWB system based on cognitive radio theory

A cognitive radio transmitted reference ultra-wideband（CR-TR-UWB） system is proposed to improve the performance of TR-UWB systems with narrowband interference（NBI） from primary users（PU）.The transmitter of the CR-TR-UWB system detects the band of PU,and then sends prolate spheroidal wave functions（PSWF） pulses with the same limited band as PU＇s to reduce interference with PU.The receiver uses a notch filter before autocorrelation to eliminate NBI from PU.The simulation results show that the bit error rate（BER） performance of the CR-TR-UWB system is close to that of TR-UWB systems without NBI when the system is interfered by single or double NBIs with a signal to interference ratio（SIR） of 0 dB,and if the signal to noise ratio（SNR） is 10 dB and the SIR varies from-20 to 10 dB,BER performance varies no more than an order of magnitude.The system has excellent resistance to NBI,strong robustness BER performance at different SNRs,and smaller interference with the same frequency band PU.