A Survey of Cooperative Games for Cognitive Radio Networks

Cooperative cognitive radio networks are new cognitive radio paradigm. Cooperative communication approaches, such as cooperative spectrum sensing and cooperative spectrum sharing, are playing key roles in the development of cognitive radio networks. To achieve the high performance, a cooperative cognitive communication framework is often used to model various cooperative spectrum sensing or sharing scenarios. However, its implementation faces numerous challenges due to the complexity of mobility and traffic models, the needs of dynamic spectrum access, the heterogeneous requirements from different users, and the distributed structure of the network. Fortunately, cooperative game theory can be used to formulate and model the interactions among licensed and unlicensed users for spectrum sensing and spectrum sharing to efficiently allocate spectrum resource in the highly dynamic and distributed radio environment. In this paper, we first present the cooperative communication technologies and describe their existing challenges, then introduce different game solutions, after that, we discuss several cooperative game strategies, and analyze the associated their applications in cognitive radio networks, at final, some open directions for future research on economic strategies in cooperative communication in cognitive radio networks are proposed.     

Game-theoretic spectrum sharing for cognitive radio based on the expectation of primary users

Cognitive radio is a new intelligent wireless communication technique for remedying the shortage of spectrum resource in recent years. Secondary users have to pay when they share available spectrum with primary users while price is an important factor in the spectrum allocation. Based on the game theory, an improved pricing function is proposed by considering the expectation of primary users. In this article, expectation represents the positivity of sharing spectrum with primary users. By introducing the positivity, price not only becomes different for different secondary users, but also can be adjusted according to the positivity. It is proved that the Nash Equilibrium of the new utility function exists. The simulation results show that spectrum sharing can not only be determined by the channel quality of secondary users, but also can be adapted according to the expectation of primary users. Besides, the proposed algorithm improves the fairness of sharing.     

A game theoretic approach for energy‐efficient communications in multi‐hop cognitive radio networks

In multi‐hop cognitive radio networks, it is a challenge to improve the energy efficiency of the radio nodes. To address this challenge, in this paper, we propose a two‐level Stackelberg game model, where the primary users and the secondary users act as the leaders and the followers, respectively. Based on the game model, our proposed scheme not only considers the power allocation problem for secondary users but also takes into account the price of spectrum. First, we give the cognitive radio network model, and show how to set up the game theoretic model in multi‐hop cognitive radio networks. We then analyze this problem and show the existence and uniqueness of the Nash equilibrium point for the game. We also study the impact of the spectrum price of the primary users in the cognitive radio network and study how to select the best price for the primary users to maximize their own profit. Finally, we implement simulations to show the performance of our schemes. Our work gives an insight on how to improve the energy efficiency and allocate spectrum resources in multi‐hop cognitive radio networks. Copyright © 2016 John Wiley & Sons, Ltd.     

认知无线电中基于Stackelberg博弈的分布式功率分配算法

在underlay认知无线电场景中,为了让认知用户能随机地接入主用户正在使用的授权频段,且对主用户产生的干扰不高于主用户能够容忍的干扰温度门限,该文采用Stackelberg博弈机制进行认知用户的发射功率分配。将主用户作为模型中的leader,认知用户作为follower,认知用户使用主用户的授权频段时需以干扰功率为单位支付给主用户相应的费用,而主用户则可以通过调整价格,限制认知用户产生的总干扰功率不高于其所能容忍的干扰温度门限,以便获得最大收益。同时,不同认知用户间根据主用户制定的价格,进行非协作博弈。仿真结果表明,与集中式的最优功率分配算法相比,该文可通过简单的分布式功率分配算法获得与其相近的系统性能,且主用户与认知用户间只需进行少量的信息交互,这与需进行大量信息交互的集中式最优算法相比,具有较大的优势。     

Resource allocation based on dynamic hybrid overlay/underlay for heterogeneous services of cognitive radio networks

In cognitive radio networks (CRNs), hybrid overlay and underlay sharing transmission mode is an effective technique to improve the efficiency of radio spectrum. Unlike existing works in literatures where only one secondary user (SU) uses both overlay and underlay mode, the different transmission modes should dynamically be allocated to different SUs according to their different quality of services (QoS) to achieve the maximal efficiency of radio spectrum. However, dynamic sharing mode allocation for heterogeneous services is still a great challenge in CNRs. In this paper, we propose a new resource allocation method based on dynamic allocation hybrid sharing transmission mode of overlay and underlay (Dy-HySOU) to obtain extra spectrum resource for SUs without interfering with the primary users. We formulate the Dy-HySOU resource allocation problem as a mixed-integer programming to optimize the total system throughput with simultaneous heterogeneous QoS guarantee. To decrease the algorithm complexity, we divide the problem into two sub-problems: subchannel allocation and power allocation. Cutset is used to achieve the optimal subchannel allocation, and the optimal power allocation is obtained by Lagrangian dual function decomposition and subgradient algorithm. Simulation results show that the proposed algorithm further improves spectrum utilization with simultaneous fairness guarantee, and the achieved Dy-HySOU diversity gain is satisfying.     

An auction‐based MAC protocol for cognitive radio networks

Cognitive radio and dynamic spectrum sharing systems use innovative spectrum management techniques that allow different systems to share the same frequency band to utilize the radio spectrum in an efficient way. In this paper, we propose a novel cognitive media access control protocol for cognitive radio networks under the property‐rights model, in which secondary users are divided into several nonoverlapping groups, and each group uses the proposed auction algorithm to bid for required channels from the auctioneer appointed by primary users. Simulations indicate that our proposed media access control protocol can effectively utilize spectrum resources, achieve high system efficiency, and guarantee the fairness of channel allocation among groups. Copyright © 2011 John Wiley & Sons, Ltd.     

基于强化学习的合作频谱分配算法

为了解决认知无线电网络中的频谱分配问题,提出了一种基于用户体验质量的合作强化学习频谱分配算法,将认知网络中的次用户模拟为强化学习中的智能体,并在次用户间引入合作机制,新加入用户可以吸收借鉴其他用户的强化学习经验,能够以更快的速度获得最佳的频谱分配方案;并且在频谱分配过程中引入了主用户和次用户之间的价格博弈因素,允许主用...     

Study on optimization strategy for hybrid underlay/overlay spectrum sharing based on queuing model

In order to improve the licensed spectrum utilization in cognitive radio networks,and provide higher experience quality to system users,the optimizing strategies of the hybrid underlay/overlay spectrum sharing mode was studied.For secondary users,a queuing model with service time following two phase order exponential distribution was constructed,and a method to obtain the steady state distribution was presented for the system model.Based on reward-cost structure,individual optimization strategy with observable case and the Nash equilibrium strategy with unobservable case were discussed.With purpose of optimal social benefit and maximal spectrum incomes,the pricing policies for secondary users to use licensed spectrum were formulated.Using the system experiment,the relations among the different optimal strategies were investigated,and the rationality of the price mechanism was verified.By contrasting the optimal social benefits gained by hybrid underlay/overlay spectrum sharing mode,overlay spectrum sharing mode and underlay spectrum sharing mode,it is further shown that the social optimization strategy of hybrid overlay/underlay sharing mode is more effective and stable to fully use the spectrum resource.     

Optimal distributed power allocation for a new spectrum sharing paradigm in cognitive radio networks

The problem of power allocation in cognitive radio networks plays an important role to improve the efficiency of spectrum utilization. However, most of previous works focus on the power allocation for secondary users in spectrum sharing overlay or spectrum sharing underlay, which needs to frequently handoff between the idle spectrum bands or considers the interference constraints in all spectrum bands respectively. In order to reduce the handoff and fully utilize the spectrum resource, we propose a new spectrum sharing paradigm which not only can just need to adjust the transmit power in spectrum bands instead of frequently handoff between idle spectrum bands, but can fully utilize the spectrum resource as we only consider the interference power constraints in active spectrum bands rather than in all spectrum bands. Then based on this new spectrum sharing paradigm and the constraint conditions, we study the distributed power allocation for secondary users and formulate the optimization problem as a non-cooperative game problem, after that the variational inequality approach is used to solve this game problem and a Nash equilibria solution is got, finally simulation results are illustrated to demonstrate the performance of the proposed scheme.     

Novel pricing model for spectrum leasing in secondary spectrum market

According to the property rights model of cognitive radio,primary users who own the spectral resource have the right to lease or trade part of it to secondary users in exchange for appropriate profit. In this paper,an implementation of this framework is investigated,where a primary link can lease the owned spectrum to secondary nodes in exchange for cooperation (relaying). A novel pricing model is proposed that enables the trading between spectrum and cooperation. Based on the demand of secondary nodes,the primary link attempts to maximize its quality of service (QoS) by setting the price of spectrum. Taking the price asked by primary link,the secondary nodes aim to obtain most profits by deciding the amount of spectrum to buy and then pay for it by cooperative transmission. The investigated model is conveniently cast in the framework of seller/buyer (Stackelberg) games. Analysis and numerical results show that our pricing model is effective and practical for spectrum leasing based on trading spectral resource for cooperation.     

Spectrum leasing based on Nash Bargaining Solution in cognitive radio networks

Cognitive radio is becoming an emerging technology that has the potential of dealing with the stringent requirement and scarcity of the radio spectrum resource. In this paper, we focus on the dynamic spectrum access of cognitive radio networks, in which the primary user (PU) and secondary users (SUs) coexist. In property-rights model, the PU has property of the bandwidth and may decide to lease it to secondary network for a fraction of time in exchange for appropriate remuneration. We propose a cooperative communication-aware spectrum leasing framework, in which, PU selects SUs as cooperative relays to help transmit information, while the selected SUs have the right to decide their payment made for PU in order to obtain a proportional access time to the spectrum. Then, the spectrum leasing scheme is cast into a Nash Bargaining Problem, and the Nash Bargaining Solution (NBS) can be used to fairly and efficiently address the resource allocation between PU and secondary network, enhancing both the utility of PU and secondary network. Numerical results show that spectrum leasing based on NBS is an effective method to improve performance for cognitive radio networks.     

Opportunistic Scheduling with Reliability Guarantees in Cognitive Radio Networks

We develop opportunistic scheduling policies for cognitive radio networks that maximize the throughput utility of the secondary (unlicensed) users subject to maximum collision constraints with the primary (licensed) users. We consider a cognitive network with static primary users and potentially mobile secondary users. We use the technique of Lyapunov optimization to design an online flow control, scheduling, and resource allocation algorithm that meets the desired objectives and provides explicit performance guarantees.     

Accurate Bluetooth Positioning Using Weighting and Large Number of Devices Measurements

One of the most efficient methods to reduce the dropping and blocking probabilities of the secondary users (SUs) in cognitive radio networks is channel sub-banding strategy. This means that when all the channels are occupied by the primary and secondary users, then the SUs’ channels can be divided into two sub-bands, and two SUs can use a sub-band, simultaneously. In this paper, we propose an opportunistic spectrum sharing system in cognitive radio networks in which, the channel sub-banding strategy is implemented. Furthermore, we describe the problem of channel sub-banding considering the spectrum sensing errors such as false alarm and miss-detection events for both initial and on-going SUs’ calls. Due to unreliable spectrum sensing by the SUs and subsequently possible interference with the primary users, we assume that both primary and secondary users may lose the channel due to the collision. The proposed model is analyzed by a two-dimensional Markov chain model and for performance evaluation, metrics such as blocking and dropping probabilities and channel utilization are derived. Numerical and simulation results show the accuracy of the proposed model which can be used in the evaluation of future cognitive radio networks’ performance.     

Cybersecurity Issues in Wireless Sensor Networks: Current Challenges and Solutions

The spectrum is a scarce resource and shall be used efficiently. It is observed that fixed spectrum allocation techniques, currently in use, may not be able to accommodate increased number of users trying simultaneously to access the network. Researches suggest that this problem of spectrum scarcity can be addressed by cognitive radio networks; which permits the dynamic use of spectrum. One of the basic requirements of dynamic spectrum access in cognitive radio network is spectrum handoff. There is an associated issue with frequent spectrum handoffs and that is of the ping-pong ect. The ping-pong ect is caused due to the motion of mobile users between the adjacent cells, thus, initiating unnecessary spectrum handoffs. The purpose of this study is to develop and analyse a system that has the ability to perform cient decision about the execution of spectrum handoffs and in turn reduce the chances of ping-pong ect. Therefore, a fuzzy logic based system has been developed in a cognitive radio WLAN and UMTS environment and handoff is investigated between primary and secondary users. Our proposed hybrid system uses a two-stage fuzzy logic controller to reduce the number of ping-pong handoffs. In the rst stage, the system is designed to control the power of SU and to avoid any interference to PU. In the second stage, the system is designed to take the decision to execute handoff.

     

认知无线电网络中基于动态信誉机制的频谱分配策略研究

认知无线电技术作为一种新型频谱共享技术而成为近年来研究的热点。如何确保频谱共享中资源分配的合理性和可靠性是认知无线电技术所面临的一个新的挑战。通过对认知用户不同情况下可能采取行为的分析和研究,提出一种结合VCG机制和主观逻辑理论的基于动态信誉机制的频谱分配策略。该策略能保证认知用户在理性的情况下提供真实的申请资源信息而对用户的非理性行为采取有效地控制。同时根据策略设计相应算法。仿真结果表明该算法能够有效地防止用户在申请资源时的欺骗行为以提高频谱利用率,并且能够减轻用户的非理性行为对系统造成的影响。      

Optimal Resource Allocation for Spectrum Sensing Based Cognitive Radio Networks with Statistical QoS Guarantees

Resource allocation under spectrum sensing based dynamic spectrum sharing strategy is a critically important issue for cognitive radio networks (CRNs), because they need to not only satisfy the interference constraint caused to the primary users (PUs), but also meet the quality-of-service (QoS) requirements for the secondary users (SUs). In this paper, we develop the optimal spectrum sensing based resource allocation scheme for the delay QoS constrained CRNs. Specifically, we aim at maximizing the maximum constant arrival rate of the SU that can be supported by the time-varying service process subject to the given statistical delay QoS constraint. In our derived power allocation scheme, not only the average transmit and interference power constraints are considered, but also the impact of the PUs?? transmission to the CRNs and the PUs?? spectrum-occupancy probability are taken into consideration. Moreover, the spectrum sensing errors are also taken into consideration. Simulation results show that, (1) the effective capacity of the secondary link decreases when the statistical delay QoS constraint becomes stringent; (2) given the QoS constraint, the effective capacity of the secondary link varies with the interference power constraint and the SNR of the primary link.     

喷泉码在认知无线电网络中的应用

认知无线电网络被认为是实现动态频谱共享、缓解频谱资源紧缺的重要途径。喷泉码能有效抵抗认知无线电网络中来自主用户的突发干扰,且无需反馈重传,从而为认知无线电网络提供了一种有效的信道编码方案。首先简介了数字喷泉码以及认知无线电网络基础知识,然后综述了数字喷泉码在认知无线电网络的链路建立、认知通信以及在资源分配中的应用现状,最后指出了在这一研究领域中需要解决的问题,并展望了发展前景。     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.     

Joint power allocation and beamforming with users selection for cognitive radio networks via discrete stochastic optimization

Cognitive radio is a promising technique to dynamic utilize the spectrum resource and improve spectrum efficiency. In this paper, we study the problem of mutual interference cancellation among secondary users (SUs) and interference control to primary users (PUs) in spectrum sharing underlay cognitive radio networks. Multiple antennas are used at the secondary base station to form multiple beams towards individual SUs, and a set of SUs are selected to adapt to the beams. For the interference control to PUs, we study power allocation among SUs to guarantee the interference to PUs below a tolerable level while maximizing SUs?? QoS. Based on these conditions, the problem of joint power allocation and beamforming with SUs selection is studied. Specifically, we emphasize on the condition of imperfect channel sensing due to hardware limitation, short sensing time and network connectivity issues, which means that only the noisy estimate of channel information for SUs can be obtained. We formulate the optimization problem to maximize the sum rate as a discrete stochastic optimization problem, then an efficient algorithm based on a discrete stochastic optimization method is proposed to solve the joint power allocation and beamforming with SUs selection problem. We verify that the proposed algorithm has fast convergence rate, low computation complexity and good tracking capability in time-varying radio environment. Finally, extensive simulation results are presented to demonstrate the performance of the proposed scheme.