A game approach for cooperative spectrum sharing in cognitive radio networks

We consider the problem of cooperative spectrum sharing among primary users (PUs) and secondary users (SUs) in cognitive radio networks. In our system, each PU selects a proper set of SUs to serve as the cooperative relays for its transmission and in return, leases portion of channel access time to the selected SUs for their own transmission. PU decides how to select SUs and how much time it would lease to SUs, and the cooperative SUs decide their respective power levels in helping PU's transmission, which are proportional to their access times. We assume that both PUs and SUs are rational and selfish. In single‐PU scenario, we formulate the problem as a noncooperative game and prove that it converges to a unique Stackelberg equilibrium. We also propose an iterative algorithm to achieve the unique equilibrium point. We then extend the proposed cooperative mechanism to a multiple‐PU scenario and develop a heuristic algorithm to assign proper SUs to each PU considering both performance and fairness. The simulation results show that when the competition among SUs is fierce, the performance gap between our heuristic algorithm and the optimal one is smaller than 3%. Copyright © 2013 John Wiley & Sons, Ltd.     

改进的认知无线电频谱共享博弈模型

提出了一种改进的认知无线电频谱共享模型.该模型综合考虑了主用户的收益受到所有次用户请求带宽的影响,以及每个次用户的收益受到其他次用户请求带宽的影响;同时,与次用户竞争的主用户能够通过选择最佳带宽定价来获得最大的收益,相互竞争或合作的次用户通过从有限的频谱中改变请求频谱带宽来获得最大收益.对改进模型的静态博弈、动态博弈及其稳定性、帕累托最优等特性的仿真结果证明该模型适应实际情况.     

基于合作博弈的多信道认知无线网络中的频谱共享算法简

采用合作博弈对多信道认知无线网络中的频谱共享问题进行了建模分析,提出了次用户在各信道上的信干噪比乘积作为合作博弈的效用函数。次用户在各信道上保证对主用户的干扰小于一定门限的要求下,通过最大化各自效用函数的乘积来进行功率分配。由于最大化次用户效用函数的乘积问题是非凸的,通过变量替换将其转化为了一个等价的凸优化问题,利用该凸优化问题的对偶分解,提出了一种次用户间的频谱共享算法。仿真结果表明,所提算法在次用户和速率与公平性之间进行了有效折中。     

认知无线电网络子空间映射频谱共享

针对集中式多用户多天线认知无线电网络,分析了子空间映射能够为认知系统提供的通信机会以及理想信道条件下的空间子信道分配方案。在此基础上,提出了一种基于子空间映射的频谱共享策略。根据认知系统的感知结果,计算可以利用的空间子信道数,通过认知用户接入控制和子空间映射避免或抑制系统间干扰,从而在保证授权用户通信质量的前提下,为认知用户提供通信机会。仿真结果表明,与已有的子空间映射频谱共享方法相比,该策略不仅具有更高的认知系统可达和速率,而且能够为认知系统提供更多通信机会。     

OFDMA认知无线电网络中面向需求的频谱共享

从满足次网络通信需求的角度,设计一个两阶段模型,求解OFDMA 认知无线电网络中频谱租赁与分配问题。模型第1阶段,次基站收集次网络通信需求,向多个主基站租用频谱资源。运用Bertrand博弈对主、次基站的交易行为进行建模,并将纳什均衡作为最终定价方案。第2阶段,基于纳什议价方案,将次基站子载波和功率分配问题定义成非线性规划问题,并通过拉格朗日乘数法进行求解。仿真实验表明,相对于其他频谱共享方案,所提方案高效地满足每个次用户的通信需求。     

Spectrum sensing scheduling for group spectrum sharing in cognitive radio networks

This paper addresses the issues on spectrum sharing in a cognitive radio network consisting of a primary user and a group of cognitive users. Each cognitive user may occupy a non‐overlapped sub‐band of the primary spectrum, but it needs to perform spectrum sensing independently before accessing the sub‐band. To reduce the complexity of spectrum sensing and thus energy consumption, this paper proposes a scheduled spectrum sensing scheme. First, we consider a single spectrum sensing scenario where only one cognitive user is elected to perform spectrum sensing, and then it broadcasts its sensing results to the other cognitive users. The scheduled spectrum sensing scheme works in both network‐centric and user‐centric ways. Next, the scheduled spectrum sensing scheme is further generalized to work in a multiple spectrum sensing scenario. The results show the effectiveness of the proposed schemes compared with the traditional schemes where all cognitive users may perform spectrum sensing at the same time. Copyright © 2010 John Wiley & Sons, Ltd.     

多天线认知无线电网络自适应空间映射频谱共享

针对集中式多用户多天线认知无线电网络,提出一种基于自适应空间映射的频谱共享策略,根据授权用户接入的随机性所带来的频谱和空间资源占用情况的变化,认知系统将发射信号自适应地映射在认知基站与授权用户之间信道的子空间上,避免或抑制系统间干扰,从而在保证授权用户通信质量的前提下,为认知用户提供通信机会,并且在认知系统内部利用块对角化和奇异值分解方法分离不同认知用户的信号,消除系统内干扰。性能分析和仿真结果表明,与已有的频谱共享方法相比较,该策略不仅具有更高的认知系统可达和速率,并且对于由不同授权系统负载情况形成的不同场景具有更强的鲁棒性。     

Channel assignment schemes for cooperative spectrum sensing in multi‐channel cognitive radio networks

In this paper, channel assignment for spectrum sensing is studied in multi‐channel cognitive radio (CR) networks to maximize the number of channels satisfying sensing performance (called available channels). Beginning with a nonlinear integer programming problem, we derive the upper bound of optimal value through many‐to‐many assignment problem and then propose three algorithms for both centralized and distributed scenarios. In centralized case, a heuristic scheme is proposed based on the signal‐to‐noise ratios (SNRs) over all primary channels (PCs). Then, a greedy scheme is proposed to reduce the reported information from the CRs. In distributed case, a novel scheme with multi‐round operation is designed following the coalitional game theory. In each round, each CR selects some PCs based on SNRs. Then, the CRs selecting the same channel play coalitional game, and thereby, multiple games are played concurrently over multiple channels. Finally, the best coalition for each channel is chosen among the formed coalitions to perform the cooperative spectrum sensing. The simulation results show that the proposed schemes can significantly increase the number of available channels. Copyright © 2013 John Wiley & Sons, Ltd.     

Evolutionary non‐cooperative spectrum sharing game: long‐term coexistence for collocated cognitive radio networks

Collocated cognitive radio networks (CRNs) employ coexistence protocols to share the spectrum when it is not being used by the licensed primary users. These protocols work under the assumption that all spectrum bands provide the same level of quality of service, which is somewhat simplistic because channel conditions as well as the licensee's usage of allocated channels can vary significantly with time and space. These circumstances dictate that some channels may be considered better than others; therefore, CRNs are expected to have a preference over the choice of available channels. Because all CRNs are assumed to be rational and select the best available channels, it can lead to an imbalance in contention for disparate channels, degraded quality of service, and an overall inefficient utilization of spectrum resource. In this paper, we analyze this situation from a game theoretic perspective and model the coexistence of CRNs with heterogeneous spectrum as an evolutionary anti‐coordination spectrum‐sharing game. We derive the evolutionarily stable strategy (ESS) of the game by proving that it cannot be invaded by a greedy strategy. We also derive the replicator dynamics of the proposed evolutionary game, a mechanism with which players can learn from their payoff outcomes of strategic interactions and modify their strategies at every stage of the game and subsequently converge to ESS. Because all CRNs approach ESS based solely upon the common knowledge payoff observations, the evolutionary game can be implemented in a distributed manner. Finally, we analyze the game from the perspective of fairness using Jain's fairness index under selfish behavior from CRNs. Copyright © 2016 John Wiley & Sons, Ltd.     

认知车载网络中基于QoS保障的频谱共享新策略

构建了基于认知无线电的新型车载网络,并提出基于安全业务服务质量(QoS)保障的两步式频谱共享策略:多认知小区间的频谱分配和单认知小区内的频谱共享。仿真结果表明,提出的GNBS(generalized nash bargaining solution)分配方案综合考虑了系统的公平性和总效用,可获得明显大于最大化最小方案的系统和速率,以及明显优于最大化和速率方案的多认知小区间的公平性;GNBS方案可以根据多小区间频谱需求的差异性来动态调节资源分配的比例,有效地实现了需求非对称的多小区间频谱资源的最优化配置;此外,单小区内的协作频谱共享机制,使得协作双方均获得了优于非协作方案的系统效用,有效地提高了系统吞吐量以及认知OBU间的公平性。     

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.     

基于合作形成的认知无线网络频谱共享策略

当具备不同利益的多个主网络竞争为单个次级网络提供频谱接入机会时,它们可以通过基于重复博弈模型的频谱共享机制实现对授权通信频段的合作垄断,从而最大化它们的整体数据传输效用。然而当某个主网络对未来传输效用不够重视时,它会为了获得比垄断效用更高的传输效用而偏离当前的合作垄断,从而降低了其他主网络的当前和未来数据传输效用。为此,2种新的频谱共享策略被提出以促使所有主网络形成更为灵活和可靠的频谱共享合作垄断。数值仿真表明,相比现有的触发策略,这2种新策略能够为所有主网络获得更优的整体数据传输效用。     

认知自组网分布式频谱感知最优协作算法

认知无线电技术使得自组织网络节点能够充分利用空闲频谱资源,提高了传输性能。通过协作频谱感知,可有效解决由于无线信道存在阴影、噪声和衰落等情况导致的单节点感知准确性偏低。为了解决梯度算法随着协作节点数量增大后计算复杂度变高,文中提出部分梯度算法ψ-GBCS,该模型通过基于SNR的动态阈值保证了感知准确性,同时通过最佳协作节点数提高了感知效率。仿真结果表明,该模型下,综合评估系统效率和性能的J函数值提高37%,能耗降低50%,有效保证大规模认知自组网频谱感知的鲁棒性,降低了对主用户的干扰及设备功耗。     

Asymmetric active cooperation strategy in spectrum sharing game with imperfect information

In this paper, we study the spectrum sharing problem in the cognitive network where two secondary users coexist and interfere with each other in an unlicensed channel. Each user in our scenario is independent and is unaware of the characteristic of its rival but its statistics (imperfect information). An important issue is the interaction among selfish independent wireless communication systems (secondary users) who aim to maximize their own current utility. We provide a self‐enforcing spectrum sharing framework, which has the advantage of not requiring a control center or communicating between two users. The short‐term profits of users gained before cooperation being builded are asymmetrical. The long‐term profit is used as the user's utility. Users improve their long‐term profits by creating mutual cooperation actively. The historical action of the user is used by its rival to evaluate/update the current action. The action updating algorithm is provided. Moreover, we investigate the stability of the cooperation. As demonstrated, the proposed scheme can build mutual cooperation through extensive simulations. The existence of equilibrium is confirmed by the repeated game. And our scheme can achieve a good trade‐off between short‐term profits and long‐term profits. Copyright © 2013 John Wiley & Sons, Ltd.     

Centralized spectrum leasing via cooperative SU assignment in cognitive radio networks

As the increasing demand of the radio spectrum, the researchers pay more attention to the technology of cognitive radio networks to improve the use of the scarce spectrum resources. Recently, cooperative communications combining with cognitive radio have been proposed in many literatures to improve the channel capacity. The primary users with poor transmission environment transmit their packets with the assistance of the secondary users (SUs) by offering them spectrum resources. This paper first raises issues in existing works, such as non‐optimal selection, selection collision, and transmission interruption. Aiming at these issues, we design a centralized system model and a cooperative relaying protocol for multiple primary user pairs to dynamically lease spectrum in exchange for the transmission assistance of SUs. Then we define 2 problems of the cooperative SU assignment to maximize total rate and maximize number of assigned SUs. We prove they are NP‐hard and propose a local search algorithm for the objective of maximize total rate and a ‐approximation algorithm for another objective. Our simulation results show that our system and algorithms can effectively improve the performance of the wireless networks.     

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper,we present a non-transferable utility coalition graph game(NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing(OFDMA) based cognitive radio networks to maximize both system throughput and system fairness.In this algorithm,with the assistance of others SUs,SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs.So this scheme can effectively exploit both space and frequency diversity of the system.Performance results show that,NTU-CGG significantly improves system fairness level while not reducing the throughput comparing with other existing algorithms.     

认知网络中协作感知吞吐量的优化

为了提高集中式认知网络的吞吐量,提出了基于信任度的吞吐量优化算法.该算法在主用户充分保护的前提下,以认知用户的吞吐量为目标函数,融合中心采用双门限值对本地感知结果进行融合.从理论上证明了吞吐量是全局漏检概率的增函数,当全局漏检概率等于门限值时,吞吐量达到最大值.并利用牛顿迭代法求出单节点概率,然后采用遍历法可得到认知用户吞吐量最大值.仿真结果表明,当信噪比为-14 dB时认知用户融合优化算法相对"AND准则"OR准则"以及"HALF准则"归一化吞吐量分别提高了0.62、0.3和0.09.     

Non‐cooperative power control and spectrum allocation in cognitive radio networks: a game theoretic perspective

The invention of cognitive radio (CR) concept aims to overcome the spectral scarcity issues of emerging radio systems by exploiting under‐utilization of licensed spectrum. Determining how to allocate unused frequency bands among CR is one of the most important problems in CR networks. Because different CRs may have different quality‐of‐service requirements, they may have different objectives. In voice communication, high‐speed transmission is the most important factor; hence, voice radios always try to maximize their transmission rate. However, in data communication, the most important factor is the bit error rate. The data radios always try to maximize their signal‐to‐interference‐plus‐noise ratio (SINR). In this paper, two non‐cooperative games named interference minimization game and capacity maximization game, which reflect the target of data radios and voice radios, respectively, are proposed. From the simulations, after these games are applied, the average SINRs of all players at each channel are improved. The average SINR of players in each channel after applying the capacity maximization game is smaller than that after applying the interference minimization game. However, in comparison with that after applying the interference minimization game, the average capacity of players after applying capacity maximization approach is larger. Copyright © 2012 John Wiley & Sons, Ltd.     

Efficient secondary access with intelligent spectrum sensing in cognitive radio networks

In cognitive radio networks, cooperative sensing can significantly improve the performance in detection of a primary user via secondary users (SUs) sharing their detection results. However, a large number of cooperative SUs may induce great sensing delay, which degrades the performance of secondary transmissions. In this paper, we jointly consider cooperative sensing and cognitive transmission in cognitive radio networks, aiming to achieve efficient secondary access with low sensing overhead under both the sensing time and reporting power limitations, where primary users are guaranteed to be sufficiently protected. We first propose an adaptive sensing scheme to lower the detection time while not degrading the detection probability. Then, based on the proposed adaptive sensing scheme, an efficient cognitive transmission protocol is well designed, which improves the throughput of secondary transmissions while ensuring the QoS of primary transmissions. We analyze the performance for the proposed secondary access framework in terms of misdetection probability, average detection time and normalized secondary throughput, respectively, and derive their closed‐form expressions over Rayleigh fading channels with considering the reporting errors accordingly. We also study the problems of optimizing the number of cooperative SUs to minimize the misdetection probability and average detection time, and maximize the normalized secondary throughput for proposed framework. Simulation results reveal that the proposed framework outperforms the traditional case significantly. Copyright © 2013 John Wiley & Sons, Ltd.     

Distributed power control for multiuser cognitive radio networks with quality of service and interference temperature constraints

One of the most challenging problems in dynamic resource allocation for cognitive radio networks is to adjust transmission power of secondary users (SUs) while quality of service needs of both SUs and primary users (PUs) are guaranteed. Most power control algorithms only consider interference temperature constraint in single user scenario while ignoring the interference from PUs to SUs and minimum signal to interference plus noise ratio (SINR) requirement of SUs. In this paper, a distributed power control algorithm without user cooperation is proposed for multiuser underlay CNRs. Specifically, we focus on maximizing total throughput of SUs subject to both maximum allowable transmission power constraint and SINR constraint, as well as interference temperature constraint. To reduce the burden of information exchange and computational complexity, an average interference constraint is proposed. Parameter range and convergence analysis are given for feasible solutions. The resource allocation is transformed into a convex optimization problem, which is solved by using Lagrange dual method. In computer simulations, the effectiveness of our proposed scheme is shown by comparing with distributed constrained power control algorithm and Nash bargaining power control game algorithm. Copyright © 2014 John Wiley & Sons, Ltd.