A Spectrum Occupancy Model for Primary Users in Cognitive Radio Systems

There are abundant research results related to cognitive radio systems (CR systems), but using queueing models to portray CR systems is a new research trend. In this paper, a single-server retrial cognitive radio system with a linear retrial rate has been considered. The system has two types of users: primary users and secondary users. Secondary users have no effect on primary users because primary users have preemptive precedence. As a result, our purpose is to examine some performance indicators such as the expected queue length for primary users, the probability of the system being idle or occupied by a secondary user, and the probability of the system being busy. This paper begins by deriving the expressions for the generating functions based on the balance equations, so that we can calculate our goal conveniently.

Coordinated Multi-User Spectrum Sharing in Distributed Antenna-Based Cognitive Radio Systems

Spectrum sharing for efficient reuse of licensed spectrum is an important concept for cognitive radio technologies.In a spectrum-sharing system(SSS),deploying the antennas in a distributed manner can offer a new spatial dimension for the efficient reuse of licensed frequency bands.To improve the whole performance of multiple secondary users(SUs),this paper addresses the problem of coordinated multi-SU spectrum sharing in a distributed antenna-based SSS.By adopting the Hungarian method,the primal decomposition method and pricing policy,we propose a coordinated multi-user transmission scheme,so as to maximize the sum-rate of SUs.Simulation results show that the proposed method can significantly enhance the system performance,and the computational complexity is low.

NOVEL SPECTRUM SENSING METHOD BASED ON THE SPATIAL SPECTRUM FOR COGNITIVE RADIO SYSTEMS

Spectrum sensing is the key problem for Cognitive Radio(CR) systems.A method based on the Peak-to-Average Amplitude-Ratio(PAAR) of the Spatial Spectrum(SS) of the received signals is proposed to sense the available spectrum for the cognitive users with the help of the multiple antennas at the receiver of the cognitive users.The greatest advantage of the new method is that it requires no information of the noise power and is free of the noise power uncertainty.Both the simulation and the analytical results show that the proposed method is robust to noise uncertainty,and greatly outperform the classical Energy Detector(ED) method.

MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

Optimal Spectrum Sensing in Energy Harvesting Cognitive Radio Systems

In this paper,we consider a cognitive radio system with energy harvesting,in which the secondary user operates in a saving-sensing-transmitting(SST) fashion.We investigate the tradeoff between energy harvesting,channel sensing and data transmission and focus on the optimal SST structure to maximize the SU's expected achievable throughput.We consider imperfect knowledge of energy harvesting rate,which cannot be exactly known and only its statistical information is available.By formulating the problem of expected achievable throughput optimization as a mixed-integer non-linear programming one,we derive the optimal saveratio and number of sensed channels with indepth analysis.Simulation results show that the optimal SST structure outperforms random one and performance gain can be enhanced by increasing the SU's energy harvesting rate.

Optimization of Cognitive Radio System Using Self-Learning Salp Swarm Algorithm

CognitiveRadio(CR)has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral efficiency.To improve the overall performance of the CR systemit is extremely important to adapt or reconfigure the systemparameters.The Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter adaptation.As meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches,the performance of these algorithms is investigated in order to design an efficient CR system that is able to adapt the transmitting parameters to effectively reduce power consumption,bit error rate and adjacent interference of the channel,while maximized secondary user throughput.Self-Learning Salp Swarm Algorithm(SLSSA)is a recent meta-heuristic algorithm that is the enhanced version of SSA inspired by the swarming behavior of salps.In this work,the parametric adaption of CR system is performed by SLSSA and the simulation results show that SLSSA has high accuracy,stability and outperforms other competitive algorithms formaximizing the throughput of secondary users.The results obtained with SLSSA are also shown to be extremely satisfactory and need fewer iterations to converge compared to the competitive methods.

The Novel Spectrum Allocation Algorithm in Cognitive Radio System

In order to reduce the disturbance on an authorizing user and lower the competition between cognitive users, assure the normal communication of a cognitive radio system, reliability theory is applied to describe if a channel can be used by a cognitive user or not and the probability that the channel is continually used for a period. Three aspects including space, time domain and frequency domain are united for the research on the distribution of frequency spectrum. The simulation result shows that, in the space domain, time domain, frequency domain algorithm, the transmitted data volume and the total throughput of the system are superior to those in greedy algorithm and time domain—frequency domain algorithm, the novel algorithm is helpful to reduce the disturbance caused by a cognitive user to an authorizing user and lower the competition between cognitive users, this simulation result shows that the proposed algorithm is effective.

Power Allocation for Sensing-Based Spectrum Sharing Cognitive Radio System with Primary Quantized Side Information

Spectrum access approach and power allocation scheme are important techniques in cognitive radio(CR) system,which not only affect communication performance of CR user(secondary user,SU) but also play decisive role for protection of primary user(PU).In this study,we propose a power allocation scheme for SU based on the status sensing of PU in a single-input single-output(SISO) CR network.Instead of the conventional binary primary transmit power strategy,namely the sensed PU has only present or absent status,we consider a more practical scenario when PU transmits with multiple levels of power and quantized side information known by SU in advance as a primary quantized codebook.The secondary power allocation scheme to maximize the average throughput under the rate loss constraint(RLC) of PU is parameterized by the sensing results for PU,the primary quantized codebook and the channel state information(CSI) of SU.Furthermore,Differential Evolution(DE) algorithm is used to solve this non-convex power allocation problem.Simulation results show the performance and effectiveness of our proposed scheme under more practical communication conditions.

A Robust Cooperative Spectrum Sensing Scheme in Cognitive Radio Systems

Performance of cluster-based cooperative spectrum sensing is more greatly improved than that of the traditional cooperative spectrum sensing. However, the style of clusters is not pointed out on traditional cluster-based method. In view of all the fading in the cooperative spectrum sensing, space diversity, and selective diversity, a robust cooperative spectrum sensing scheme based on clusters is proposed. Simulation results show that the detection performance of this new scheme is more close to that of the ideal cluster-based cooperative spectrum sensing scheme, and the excellent performance with higher reliability is gained relative to the actual cluster-based cooperative spectrum sensing scheme. Finally, the number of users in a cluster of the proposed scheme is discussed. The two users in a cluster are not the optimal solution to the overall implementation of cognitive radio.

Interference cancellation scheme for uplink cognitive radio systems

This paper investigates the interference cancellation （IC） scheme for uplink cognitive radio systems, using the spectrum underlay strategy where the primary users （PUs） and the secondary users （SUs） coexist and operate in the same spectrum. Joint MMSE-based parallel interference cancellation （PIC） and Turbo decoding scheme is proposed to reduce the interference to the PUs, as well as to the SUs, in which the minimum mean square estimation （MMSE） filter is only employed in the first iteration, regarded as the ＂weakest link＂ of the whole detection process, to improve the quality of the preliminary detections results before they are fed to the Turbo decoder. Simulation results show that the proposed scheme can efficiently eliminate the interference to the PUs, as well as to the SUs.

Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

The optimization of cognitive radio(CR)system using an enhanced firefly algorithm(EFA)is presented in this work.The Firefly algorithm(FA)is a nature-inspired algorithm based on the unique light-flashing behavior of fireflies.It has already proved its competence in various optimization prob-lems,but it suffers from slow convergence issues.To improve the convergence performance of FA,a new variant named EFA is proposed.The effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions,and simulation results show its superior performance compared to biogeography-based optimization(BBO),bat algorithm,artificial bee colony,and FA.As an application of this algorithm to real-world problems,EFA is also applied to optimize the CR system.CR is a revolutionary technique that uses a dynamic spectrum allocation strategy to solve the spectrum scarcity problem.However,it requires optimization to meet specific performance objectives.The results obtained by EFA in CR system optimization are compared with results in the literature of BBO,simulated annealing,and genetic algorithm.Statistical results further prove that the proposed algorithm is highly efficient and provides superior results.

Research on cooperative detection and multiple access for cognitive radio system

As cognitive radio (CR) needs to detect spectrum accurately and utilize the idle spectrum efficiently,a new model of CR is proposed.This model adopts energy detection with auto-adapted threshold and produces spectrum mark vector.The basis function is obtained through making IDFT to the inner product of spectrum and phase vectors,and it is variable with the spectrum states.Data are sent through modulation on the basis function,and it can be estimated by correlation in the receiving end.The cooperative detection and multiple access of this model are also researched in this paper,and the performance is finally analyzed.Simulations show the cooperative detection of this model can obtain higher detection probability,and the disaccord of the basis functions between sending and receiving ends can lower its performance.

A Static Spectrum Aggregation Algorithm in Cognitive Radio System

Cognitive radio ( CR) is known as an intelligent technology allowing a secondary user ( SU) to occupy a primary user's ( PU's) band when it is idle. Appearance of the idle band may be contiguous or non-contiguous. In other words,the PU's band and the idle band are distributed alternately over the spectrum. Apparently the non-contiguous idle band cannot be fully utilized in this context. This paper proposes an algorithm to solve the problem of low utilization of the non-contiguous idle band and to increase the number of the SU who needs access to the spectrum by a static spectrum aggregation ( SSA) method combined with non-contiguous orthogonal frequency division multiplexing ( NC-OFDM) . The simulation results show that the SSA algorithm realizes at least 70% utilization of the idle band which provides access to the spectrum for as many as 30 SUs as expected.

OPTIMIZATION OF SPECTRUM UTILIZATION IN COGNITIVE RADIO SYSTEM

In Cognitive Radio(CR) networks,CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users.Hence recent research has been focused on the interference avoidance problem.Quality of Service(QoS) requirement of CR user will affect the time of data transmission in each frame.In this paper,in order to solve the interference avoidance and spectrum utilization problems without cooperation among CR users,a new scheme to obtain the optimal duration of data transmission frame is proposed to maximize the spectrum utilization and guarantee the protection to the primary users.The main advantages of our proposed scheme include the followings:(1) QoS requirement of CR user is concerned;(2) p-persistent Media Access Control(MAC) random access is used to avoid the collisions among CR users;(3) CR network system capacity is considered.We develop a Markov chain of the primary spectrum channel states and an exponential distribution of the CR user's traffic model to analyze the performance of our proposed scheme.Computer simulation shows that there is an optimal data transmission time to maximize the spectrum utilization.However,the regulatory constraint of the collision rate to the primary users has to be satisfied at the expense of spectrum utilization.And also the tradeoff between the spectrum utilization and the capacity of the CR system is taken into account.

SINR-balancing based cooperative spectrum sharing scheme for MIMO cognitive radio systems

In order to improve the system capacity of the primary user （PU） and secondary user （SU） of multiple-input-multiple-output （MIMO） cognitive radio （CR） system, a signal to interference plus noise ratio balancing （SINR-balancing） posed, in which PU leases a fraction of based cooperative spectrum sharing （CSS） scheme is proits transmission time to SU in exchange for the SU relaying the PU＇ s data cooperatively. The SINR-balancing based corresponding beamforming vectors are designed and time-division is also optimized for the proposed scheme. Simulation results show that compared to conventional opportunistic spectrum sharing （OSS） scheme, the proposed CSS scheme can effectively enhance the system performance of both PU and SU and provide an effective cooperation mechanism for PU and SU to determine whether to request cooperation.

AN EFFECTIVE SUBOPTIMAL POWER LOADING SCHEME IN OFDM-BASED COGNITIVE RADIO SYSTEMS

Orthogonal frequency division multiplexing(OFDM) is an attractive modulation candidate for Cognitive Radio(CR) networks.Effective and reliable subcarrier power allocation in OFDM-based Cognitive Radio(CR) networks is a challenging problem.This paper focuses on the power allocation for OFDM-based Cognitive Radio(CR) networks.Our objective is to maximize the total transmission rates of Secondary Users(SU) by adjusting the power of subcarrier while the interference introduced to the Primary User(PU) is within a certain range and the total power of subcarrier is not beyond the total power constraint.We investigate the optimal power allocation algorithm for OFDM-based Cog-nitive Radio(CR) based on convex optimization theory.Then,because of high complexity of the op-timal power allocation algorithm,we propose an effective suboptimal power loading scheme.Theory analysis and simulation results show that the performance of the suboptimal power allocation algorithm is close to the performance of the optimal power allocation algorithm,while the complexity of the suboptimal power allocation algorithm is much lower.

On opportunistic spectrum efficiency in cognitive radio systems

The performance bound of cognitive radio systems is analyzed.We use opportunistic spectrum effi-ciency(OSE)as the performance metric,and point out that the maximum achievable OSE can be used toevaluate the maximum value that the introduction of secondary users can add to the conventional wirelesssystems.Based on assumptions of the PU s traffic model and some reasonable approximations,the ex-pression of OSE is obtained and the maximum achievable OSE is derived by solving an optimization prob-lem.The results are verified by computer simulation.

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.

Effective capacity of cognitive radio systems in asymmetric fading channels

As known that the effective capacity theory offers a methodology for exploring the performance limits in delay constrained wireless networks, this article considered a spectrum sharing cognitive radio （CR） system in which CR users may access the spectrum allocated to primary users （PUs）. Particularly, the channel between the CR transmitter （CR-T） and the primary receiver and the channel between the CR-T and the CR receiver （CR-R） may undergo different fading types and arbitrary link power gains. This is referred to as asymmetric fading. The authors investigated the capacity gains achievable under a given delay quality-of-service （QoS） constraint in asymmetric fading channels. The closed-form expression for the effective capacity under an average received interference power constraint is obtained. The main results indicate that the effective capacity is sensitive to the fading types and link power gains. The fading parameters of the interference channel play a vital role in effective capacity for the looser delay constraints. However, the fading parameters of the CR channel play a decisive role in effective capacity for the more stringent delay constraints. Also, the impact of multiple PUs on the capacity gains under delay constraints has also been explored.

Iterative optimization of detection threshold and throughput for secondary users in multiband cognitive radio systems

In cognitive radio （CR） systems, efficient spectrum sensing ensures the secondary user （SU） to successfully access the spectrum hole. Typically, the detection problem has been considered separately from the optimization of transmission strategy. However, in practice, due to non-zero probabilities of miss detection and false alarm, the sensing phase has an impact on the throughput of SUs as well as on the transmission of primary user （PU）. In this paper, using energy detection, we maximize the total throughput of SUs by jointly optimizing the detection threshold and transmission strategy in multiband CR systems. A set of iteration based algorithms are proposed to solve this mix-integer programming problem, which show better performance compared with uniform detection threshold selection algorithm suggested by IEEE 802.22 standard.