Performance Of Cognitive Radio Networks Research Articles

On cognitive processes in cognitive radio networks

In this article we model the cognitive processes and evaluate their impact on the performance of cognitive radio networks (CRN). Operation of the cognitive radio nodes, can be characterized by two types of processes: communication processes such as packets transmission, and cognitive processes such as estimation of the network state and decision-making for dynamic resource allocation. We propose a continuous time Markov chain model of CRN that couples these processes into unified queueing framework and analyze it by means of the matrix-geometric approach. From the obtained results, we derive the performance measures of CRN such as average delay and throughput, and establish their dependencies on the underlying cognitive processes. Additionally, we design an efficient policy for accessing the vacant channels and managing the transmission-sensing trade-off, which arises when transmissions and sensing are mutually exclusive. The policy search is carried out by the stochastic optimization method of cross-entropy. The optimized policy leads to significantly enhanced performance of CRN.

Improved Detection Performance of Cognitive Radio Networks in AWGN and Rayleigh Fading Environments

Cognitive radios (CRs) have been recently emerging as prime candidates to enhance spectral efficiency by exploitingspectrum-aware systems which can reliably monitor licensed users’ activities. CR users monitor such activities byperforming spectrum sensing to detect potential white spaces. However, this process of local sensing might be achallenging task in fading environments. The inefficiency of spectrum sensing might cause interference to licensees ifthey are miss-detected by CR users. Thus, cooperative spectrum sensing is proposed as a means to combat fading andimprove the detection performance. However, the detection performance does not improve by such cooperation whenlow-SNR environment is considered. In this paper, cooperative spectrum sensing with PSO-based threshold adaptationis presented to address the aforementioned problem. Simulation results show that the detection performance with PSObasedadaptive detection threshold is improved, particularly, in low-SNR environment.

On the performance of adaptive modulation in cognitive radio networks

We study the performance of cognitive radio networks (CRNs) when incorporating adaptive modulation at the physical layer. Three types of CRNs are considered, namely opportunistic spectrum access (OSA), spectrum sharing (SS) and sensing-based SS. We obtain closed-form expressions for the average spectral efficiency achieved at the secondary network and the optimal power allocation for both continuous and discrete rate types of adaptive modulation assuming perfect channel state information. The obtained numerical results show the achievable performance gain in terms of average spectral efficiency and the impact on power allocation when adaptive modulation is implemented at the physical layer that is due to the effect of the cut-off level that is determined from the received signal-to-noise ratio for each CRN type. The performance assessment is taking place for different target bit error rate values and fading regions, thereby providing useful performance insights for various possible implementations.

Performance Analysis of Cyclic Prefixed Single-Carrier Cognitive Amplify-and-Forward Relay Systems

A cyclic prefixed single-carrier (CP-SC) relaying system is considered for cognitive radio networks under spectrum sharing condition. The outage probability of secondary users employing a two-hop amplify-and-forward (AF) relay protocol is investigated under an interference constraint inflicted by the secondary user-source and the secondary user-relay on a primary user (PU). Assuming channel-state-information (CSI) is available, the end-to-end signal-to-noise-ratio (e2e-SNR) is first derived, and then an analytical expression for the cumulative distribution function (CDF) of this e2e-SNR is derived. Based on this derived CDF, analytical expressions for the exact outage probability, the approximate symbol error rate (SER), and approximate achievable rate can be obtained. In addition, to reveal further insights into the impact of channel lengths on the diversity and coding gains, the asymptotic outage probability and SER are provided. It is important to note that the performance of cognitive radio networks is degraded due to the limited power constraint inflicted on the primary network. As such, the optimal power allocation (OPA) is also derived to achieve a better asymptotic outage probability.

A Survey of Security Challenges in Cognitive Radio Networks: Solutions and Future Research Directions

In this survey, we present a comprehensive list of major known security threats within a cognitive radio network (CRN) framework. We classify attack techniques based on the type of attacker, namely exogenous (external) attackers, intruding malicious nodes and greedy cognitive radios (CRs). We further discuss threats related to infrastructure-based CRNs as well as infrastructure-less networks. Besides the short-term effects of attacks over CRN performance, we also discuss the often ignored longer term behavioral changes that are enforced by such attacks via the learning capability of CRN. After elaborating on various attack strategies, we discuss potential solutions to combat those attacks. An overview of robust CR communications is also presented. We finally elaborate on future research directions pertinent to CRN security. We hope this survey paper can provide the insight and the roadmap for future research efforts in the emerging field of CRN security.

Cooperative Transmission in Cognitive Radio Ad Hoc Networks

Cognitive radio technology is the key to realize dynamic spectrum access system and promote the spectrum utilization through exploiting the spectrum holes left by primary users. However, the spatial heterogeneity of spectrum availability imposes special challenges for efficient utilization of the spectrum resources for cognitive radio ad hoc networks (CRAHNs). The cross-layer cooperative transmission scheme is a promising approach to improve the efficiency of spectrum utilization and improve the performance of cognitive radio networks. Such an approach leverages relay-assisted discontiguous OFDM (DOFDM) for data transmission at physical and MAC layers in a basic three-node configuration. With this scheme, a relay node will be selected that can bridge the source and the destination using its common channels between those two nodes. In this paper, we investigate the application of such a cooperative transmission scheme to address the spectrum heterogeneity issue in CRAHNs. In particular, we describe several types of cooperative transmission and formulate a new resource allocation problem with joint relay selection and channel allocation. We propose a heuristic algorithm to solve the resource allocation problem, which is based on the metric of utility-spectrum ratio of transmission groups. Simulations demonstrate the performance improvement of the cooperative transmission over the direct transmission.

Spectrum Harvesting and Sharing in Multi-Hop CRNs Under Uncertain Spectrum Supply

The essential impediment to apply cognitive radio (CR) technology for efficient spectrum utilization lies in the uncertainty of licensed spectrum supply. In this paper, we propose a novel architecture for spectrum harvesting and sharing, and investigate the joint routing and frequency scheduling problem in multi-hop cognitive radio networks (CRNs) under uncertain spectrum supply. We introduce a new service provider, Secondary Service Provider (SSP), to facilitate the accessing for secondary users (SUs). We model the vacancy of available bands with a series of random variables, and mathematically describe the corresponding frequency scheduling and flow routing constraints. From the SSP's point of view, we characterize the CRN performance with a pair of parameters (α, β), and present an optimization problem to minimize the required network-wide spectrum resource at the (α,β) level. Given that (α, β) level is specified, we obtain a lower bound for the optimization problem and develop a threshold based coarse-grained fixing algorithm for a feasible solution. Simulation results show that (i) for any (α,β) level, the proposed algorithm provides a near-optimal solution to the formulated NP-hard problem, and (ii) the (α,β) based solution is better than the expected bandwidth based one in terms of blocking ratio and spectrum utilization in multi-hop CRNs.

Analysis on the Capacity of a Cognitive Radio Network under Delay Constraints

Cognitive radio has become a promising technology to increase spectrum utilization through spectrum sharing between licensed users (primary users) and unlicensed users (secondary users). Performance evaluation and analysis is of key importance to get more knowledge of this newly emerged technology.Queueing theory and Markov chain model have been applied to conduct the analysis, where some results are obtained. The existing research sheds light on the performance of cognitive radio networks. However, there are also some limitations. Poisson arrival and exponentially distributed service time are mostly assumed in existing analysis. With these assumptions, existing queueing theory results, particularly M/G/1 priority queue results, can be directly applied, and the Markov chain model can be established. However, these assumptions are too restrictive for modern wireless communication networks, where the traffic can be of different types and the channel capacity can vary over time. In addition, particular focus is made on average values (such as average delay) with little investigation on probabilistic distribution bounds.Therefore, new methodology is needed to make a breakthrough and to bring new insights regarding performance of cognitive radio networks. Network calculus, a newly developed theory, provides a possible solution. It was firstly proposed by R. L. Cruz in 1991, and has involuted into two branches now, i.e., deterministic network calculus and stochastic network calculus. There are two basic concepts in network calculus: (stochastic) arrival curve and (stochastic) service curve, which are used to describe the arrival process of input traffic and the service process of server, respectively. Probabilistic performance guarantees can be analyzed using stochastic network calculus. In addition, the independence between arrival process and service process can be exploited to obtain tighter probabilistic bounds, which is called as independent case analysis.This work is devoted to applying network calculus analysis, particularly stochastic network calculus, to performance evaluation of a cognitive radio network. Generally, this work contains two scenarios: a single-channel scenario and a multiple-channel scenario.In the single-channel scenario, several key factors are considered and discussed. Different traffic models, including Periodical source and (Compound) Poisson source, are considered. The sensing error process, which can be further divided into mis-detection process and false alarm process, is modeled, and the corresponding stochastic arrival process is analyzed. Both constant channel and Gilbert-Elliott ON-OFF fading channel are investigated, and the stochastic service curves are obtained. In addition, the influence of different re-transmission schemes is also studied. These schemes include no-re-transmission, re-transmission until success and maximum-Ntime re-transmission. Probabilistic delay distribution bound and probabilistic backlog distribution bound are obtained and discussed. Furthermore, delay-constrained capacity is defined and capacity regions for both primary users and secondary users are also studied. Independent case analysis is applied in some cases, and results are compared and discussed. In the multiple-channel scenario, the main concern is put on the guaranteed service of multiple parallel channels and delay-constrained capacity by assuming perfect sensing and constant channel.In validating the theoretical results, system configurations are specified mainly based on Long Term Evolution (LTE) networks, and numerical calculations executed in Matlab are made to visually depict the results. Simulation platform by C++ language is also constructed to obtain simulation results. Related results show the influence of different schemes or parameters on system performance and capacity region. Comparison between the numerical and simulation results is made, which further verifies the theoretical deductions.

Enhancement of Performance of Cognitive Radio Network with Incorporation of MRC Scheme at Secondary Receiver

The faithful detection of presence of a primary user (PU) is the most essential requirement of a cognitive radio network. Otherwise the PU will experience jamming from a secondary user (SU) which will eventually lead to reduction in throughput of the PU. Similarly, the false detection of a PU will abstain a SU from its transmission opportunity hence reduce the throughput of the SU. Under this situation we propose a cognitive receiver equipped with multiple antenna and maximal ratio combining scheme (MRC) to detect the presence of a PU. The rest of the communication links like PU to PU or SU to PU uses single antenna. In this paper the concept of test statistics of fusion center from a previous literature is applied in the derivation of the probability of false alarm, probability of detection, channel capacity and symbol error rate of the network. The performance of a cognitive radio network under MRC scheme at receiving mode of SU is found better than the case of a single antenna.

Improved soft fusion-based cooperative spectrum sensing using particle swarm optimization

In soft-decision fusion- (SDF-) based cooperative spectrum sensing, weighting the coefficients vector is the main factor affecting the detection performance of cognitive radio networks. In this paper, the use of particle swarm optimization (PSO) algorithm as a prominent technique is proposed to optimize the weighting coefficients vector. The proposed PSO-based scheme opts for the best weighting coefficients vector, leading to improved detection performance of the system. The performance of the proposed method is analyzed and compared with genetic algorithm- (GA-) based technique as well as other conventional SDF schemes through computer simulations. Simulation results validate the robustness of the proposed method over all other SDF techniques.

White Cloud or Black Cloud: Opportunity and Challenge of Spectrum Sharing on Cloud Computing

In order to fully utilize the spectrum resource, dynamic spectrum access becomes a promising approach to increase the opportunity of spectrum access with the rapid development of cognitive radio. However the performance of cognitive radio networks (CRN) is considerably constrained by its limited power, memory and computing ability. Fortunately cloud computing, which is the highlight of current research, has the potential to make up for the disadvantages because of its vast storage and computing capacity. In this paper we will discuss the convergence of spectrum sharing and cloud computing from several aspects including model, advantages and challenges. A spectrum sharing model based on cloud computing (SSC) will be introduced.

QoS provisioning wireless multimedia transmission over cognitive radio networks

The rapid growing of wireless multimedia applications increases the needs of spectrum resources, but today’s spectrum resources have become more and more scarce and large part of the assigned spectrum is in an inefficiency usage. Cognitive Radio (CR) technologies are proposed to solve current spectrum inefficiency problems and offer users a ubiquitous wireless accessing environment, relying on dynamic spectrum allocation. However, there are two unsolved problems in previous work: 1) based on the simplified Quality of Service (QoS) uniform assumption, specific requirements of different wireless multimedia applications cannot be satisfied; 2) aiming at single-objective optimization of spectrum utilization or handoff rate, the co-optimization of these two necessary objectives in CR networks has not been achieved. In this paper, we propose a Two-tier Cooperative Spectrum Allocation method (TCSA) to solve these two problems. TCSA consists of two functional parts: one is a Spectrum Adjacency Ranking algorithm implemented at the secondary users’ terminals to satisfy the QoS requirements for different wireless multimedia applications; and the other is a Max Hyper-weight Matching algorithm implemented at the cognitive engines of CR networks to co-optimize spectrum utilization and secondary users’ spectrum handoff rate. Simulation results show that, compared with the other Random matching algorithm and Cost minimized algorithm, TCSA can significantly improve the performance of CR networks in terms of secondary users’ throughput and spectrum handoff rate.

Probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks

Existing distributed opportunistic spectrum management schemes do not consider the inability of today's cognitive transceivers to measure interference at the primary receivers. Consequently, optimizing the constrained cognitive radio network performance based only on the local interference measurements at the cognitive senders does not lead to truly optimal performance due to the existence of hidden (or exposed) primary senders. In this paper, we present a probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks that optimizes the constrained cognitive user goodput while taking the unavoidable inaccuracy of spectrum sensing into account. The proposed framework (i) randomly explores individual spectrum bands as local interference measurements lead to inaccurate spectrum access decisions and (ii) adopts a non-greedy probabilistic spectrum access policy that prevents a single cognitive transmission from monopolizing an available spectral opportunity. In contrast to existing techniques, our approach allows multiple cognitive flows to fairly share the available opportunities without explicit inter-flow coordination. We analytically formulate the cognitive user performance optimization problem as a mixed-integer non-linear programming to derive the optimal parameter values. We use packet-level simulations to show that our approach achieves up to 138% higher goodput with significantly better fairness characteristics compared to greedy approaches.

Delay performance of cognitive radio networks for point-to-point and point-to-multipoint communications

In this article, we analyze the packet transmission time in spectrum sharing systems where a secondary user (SU) simultaneously accesses the spectrum licensed to primary users (PUs). In particular, under the assumption of an independent identical distributed Rayleigh block fading channel, we investigate the effect of the peak interference power constraint imposed by multiple PUs on the packet transmission time of the SU. Utilizing the concept of timeout, exact closed-form expressions of outage probability and average packet transmission time of the SU are derived. In addition, employing the characteristics of the M/G/1 queuing model, the impact of the number of PUs and their peak interference power constraint on the stable transmission condition and the average waiting time of packets at the SU are examined. Moreover, we then extend the analysis for point-to-point to point-to-multipoint communications allowing for multiple SUs and derive the related closed-form expressions for outage probability and successful transmission probability for the best channel condition. Numerical results are provided to corroborate our theoretical results and to illustrate applications of the derived closed-form expressions for performance evaluation of cognitive radio networks.

A Simple Distributed Power Control Algorithm for Cognitive Radio Networks

This paper studies the power control problem for spectrum sharing based cognitive radio (CR) networks with multiple secondary source-to-destination (SD) pairs. A simple distributed algorithm is proposed for the secondary users (SUs) to iteratively adjust their transmit powers to improve the performance of the network. The proposed algorithm does not require each SU (or PU) to negotiate with other SUs (or PUs) during the communication. It is proved that the proposed algorithm can obtain a time average performance as good as that achieved when the Nash equilibrium (NE) is chosen in hindsight. More specifically, the average performance of CR networks will converge to an ε-Nash equilibrium at a rate of T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ε</sub> = O (exp (1/ε)). A sub-optimal algorithm is also introduced to further improve the convergence rate to T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ε'</sub> /log T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ε'</sub> = O (1/ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ε'</sub> ). Numerical results are presented to show the performance of the proposed algorithms under different settings.

Joint Design of Spectrum Sensing and Channel Access in Cognitive Radio Networks

Spectrum sensing is an essential functionality of cognitive radio networks. However, the effect of errors in the spectrum sensing process on the performance of the multiple access layer of both primary and secondary networks has not gained much attention. This paper aims at bridging the gap between the study of spectrum sensing and the multiple access of cognitive radio networks. To achieve this goal we pose and answer the question how the spectrum sensing errors affects the performance of cognitive radio networks from a multiple access protocol design point of view. The negative effects of the spectrum sensing errors on the throughput of both primary and secondary networks are characterized through queuing theory analysis of both networks. To alleviate these negative effects a novel joint design of the spectrum sensing and channel access mechanisms is proposed. This design is based on the observation that, in a binary hypothesis testing problem, the value of the test statistics could be used as a confidence measure for the test outcome. Therefore, this value will be used to define different channel access probabilities for secondary users. Results reveal a significant performance improvement in the maximum stable throughput of both primary and secondary networks by virtue of the proposed technique.

A Recommendation System in Cognitive Radio Networks With Random Data Traffic

A recommendation system is proposed to enhance the efficiency of spectrum access in cognitive radio networks, in which secondary users broadcast the indices of channels that they have successfully accessed. The probabilities of different actions, i.e., taking a recommendation or probing an unrecommended channel, could be either fixed or adjustable. For the constant probability case with and without retransmission, the system is modeled as a Markov random process, and the corresponding state transition probabilities are obtained. For the adjustable probability case, the anytime multiarmed bandit technique is used to adopt the strategies to the uncertain environments, and a performance lower bound is obtained. Numerical simulation results demonstrate that the proposed recommendation system can effectively orient the channel selections and significantly improve the performance of cognitive radio networks.

Game Theoretic Analysis for Spectrum Sharing with Multi-Hop Relaying

This paper studies spatial spectrum sharing (SSS) based multi-user cognitive radio (CR) networks that allow secondary users (SU) to access the licensed spectrum as long as the interference powers of primary users (PU) to be lower than a certain threshold. Although recent results have shown that multi-hop relaying has a great potential on improving the performance of CR networks, finding effective methods to control and manage SUs to achieve the optimal performance is still a challenging problem. In this paper, we model CR networks as a non-cooperative game in which each SU obtains benefits through both spectrum sharing by paying prices to PUs and multi-hop relaying by paying price to nearby SUs. Optimal power allocation methods for SUs are investigated under different assumptions and pricing functions. The conditions under which the optimal Nash Equilibrium (NE) is obtained when all SUs use multi-hop relaying are discussed. Our results are extended into large multi-user CR networks with K source-to-destination pairs. Two distributed algorithms are proposed. The first one is a sub-gradient based power allocation algorithm in which SUs can iteratively adjust their transmit powers to approach the payoff of a NE. The other one is a Q-learning based relay selection algorithm which enables each SU to iteratively search for a NE-achieving relaying scheme.

CRP: A Routing Protocol for Cognitive Radio Ad Hoc Networks

Cognitive radio (CR) technology enables the opportunistic use of the vacant licensed frequency bands, thereby improving the spectrum utilization. However, the CR operation must not interfere with the transmissions of the licensed or primary users (PUs), and this is generally achieved by incurring a trade-off in the CR network performance. In order to evaluate this trade-off, a distributed CR routing protocol for ad hoc networks (CRP) is proposed that makes the following contributions: (i) explicit protection for PU receivers that are generally not detected during spectrum sensing, (ii) allowing multiple classes of routes based on service differentiation in CR networks, and (iii) scalable, joint route-spectrum selection. A key novelty of CRP is the mapping of spectrum selection metrics, and local PU interference observations to a packet forwarding delay over the control channel. This allows the route formation undertaken over a control channel to capture the environmental and spectrum information for all the intermediate nodes, thereby reducing the computational overhead at the destination. Results reveal the importance of formulating the routing problem from the viewpoint of safeguarding the PU communication, which is a unique feature in CR networks.

Exact outage probability of cognitive AF relaying with underlay spectrum sharing

The exact closed-form expression for the outage probability (OP) of cognitive radio dual-hop amplify-and-forward (AF) relay networks is derived. The tractable expression of the OP, given in the form of elementary functions, readily enables evaluating the effect of primary users on the secondary system performance. It has been shown that the use of AF relaying significantly improves the performance of cognitive radio networks compared to its direct transmission counterpart.