Throughput analysis for cognitive radio networks with multiple primary users and imperfect spectrum sensing

In cognitive radio networks, the licensed frequency bands of the primary users (PUs) are available to the secondary user (SU) provided that they do not cause significant interference to the PUs. In this study, the authors analysed the normalised throughput of the SU with multiple PUs coexisting under any frequency division multiple access communication protocol. The authors consider a cognitive radio transmission where the frame structure consists of sensing and data transmission slots. In order to achieve the maximum normalised throughput of the SU and control the interference level to the legal PUs, the optimal frame length of the SU is found via simulation. In this context, a new analytical formula has been expressed for the achievable normalised throughput of SU with multiple PUs under prefect and imperfect spectrum sensing scenarios. Moreover, the impact of imperfect sensing, variable frame length of SU and the variable PU traffic loads, on the normalised throughput has been critically investigated. It has been shown that the analytical and simulation results are in perfect agreement. The authors analytical results are much useful to determine how to select the frame duration length subject to the parameters of cognitive radio network, such as network traffic load, achievable sensing accuracy and number of coexisting PUs

Spectral and Energy Efficiency in Cognitive Radio Systems with Unslotted Primary Users and Sensing Uncertainty

This paper studies energy efficiency (EE) and average throughput maximization for cognitive radio systems in the presence of unslotted primary users. It is assumed that primary user activity follows an ON-OFF alternating renewal process. Secondary users first sense the channel possibly with errors in the form of miss detections and false alarms, and then start the data transmission only if no primary user activity is detected. The secondary user transmission is subject to constraints on collision duration ratio, which is defined as the ratio of average collision duration to transmission duration. In this setting, the optimal power control policy which maximizes the EE of the secondary users or maximizes the average throughput while satisfying a minimum required EE under average/peak transmit power and average interference power constraints are derived. Subsequently, low-complexity algorithms for jointly determining the optimal power level and frame duration are proposed. The impact of probabilities of detection and false alarm, transmit and interference power constraints on the EE, average throughput of the secondary users, optimal transmission power, and the collisions with primary user transmissions are evaluated. In addition, some important properties of the collision duration ratio are investigated. The tradeoff between the EE and average throughput under imperfect sensing decisions and different primary user traffic are further analyzed.Comment: This paper is accepted for publication in IEEE Transactions on Communication

Non-convex distributed power allocation games in cognitive radio networks

In this thesis, we explore interweave communication systems in cognitive radio networks where the overall objective is to maximize the sum-rate of each cognitive radio user by optimizing jointly both the detection operation based on sensing and the power allocation across channels, taking into account the influence of the sensing accuracy and the interference limitation to the primary users. The optimization problem is addressed in single and multiuser cognitive radio networks for both single-input single-output and multi-input multi-output channels. Firstly, we study the resource allocation optimization problem for single-input single-output single user cognitive radio networks, wherein the cognitive radio aims at maximizing its own sum-rate by jointly optimizing the sensing information and power allocation over all the channels. In this framework, we consider an opportunistic spectrum access model under interweave systems, where a cognitive radio user detects active primary user transmissions over all the channels, and decides to transmit if the sensing results indicate that the primary user is inactive at this channel. However, due to the sensing errors, the cognitive users might access the channel when it is still occupied by active primary users, which causes harmful interference to both cognitive radio users and primary users. This motivates the introduction of a novel interference constraint, denoted as rate-loss gap constraint, which is proposed to design the power allocation, ensuring that the performance degradation of the primary user is bounded. The resulting problem is non-convex, thus, an exhaustive optimization algorithm and an alternating direction optimization algorithm are proposed to solve the problem efficiently. Secondly, the resource allocation problem for a single-input single-output multiuser cognitive radio network under a sensing-based spectrum sharing scheme is analyzed as a strategic non-cooperative game, where each cognitive radio user is selfish and strives to use the available spectrum in order to maximize its own sum-rate by considering the effect of imperfect sensing information. The resulting game-theoretical formulations belong to the class of non-convex games. A distributed cooperative sensing scheme based on a consensus algorithm is considered in the proposed game, where all the cognitive radio users can share their sensing information locally. We start with the alternating direction optimization algorithm, and prove that the local Nash equilibrium is achieved by the alternating direction optimization algorithm. In the next step, we use a new relaxed equilibrium concept, namely, quasi-Nash equilibrium for the non-convex game. The analysis of the sufficient conditions for the existence of the quasi-Nash equilibrium for the proposed game is provided. Furthermore, an iterative primal-dual interior point algorithm that converges to a quasi-Nash equilibrium of the proposed game is also proposed. From the simulation results, the proposed algorithm is shown to yield a considerable performance improvement in terms of the sum-rate of each cognitive radio user, with respect to previous state-of-the-art algorithms. Finally, we investigate a multiple-input multiple-output multiuser cognitive radio network under the opportunistic spectrum access scheme. We focus on the throughput of each cognitive radio user under correct sensing information, and exclude the throughput due to the erroneous decision of the cognitive radio users to transmit over occupied channels. The optimization problem is analyzed as a strategic non-cooperative game, where the transmit covariance matrix, sensing time, and detection threshold are considered as multidimensional variables to be optimized jointly. We also use the new relaxed equilibrium concept quasi-Nash equilibrium and prove that the proposed game can achieve a quasi-Nash equilibrium under certain conditions, by making use of the variational inequality method. In particular, we prove theoretically the sufficient condition of the existence and the uniqueness of the quasi-Nash equilibrium for this game. Furthermore, a possible extension of this work considering equal sensing time is also discussed. Simulation results show that the iterative primal-dual interior point algorithm is an efficient solution that converges to the quasi-Nash equilibrium of the proposed game

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference