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.     

Cooperative spectrum sharing of multiple primary users and multiple secondary users

This paper proposes a multiple-input multiple-output (MIMO) based cooperative dynamic spectrum access (DSA) framework that enables multiple primary users (PUs) and multiple secondary users (SUs) to cooperate in spectrum sharing. By exploiting MIMO in cooperative DSA, SUs can relay the primary traffic and send their own data at the same time, which greatly improves the performance of both PUs and SUs when compared to the non-MIMO time-division spectrum sharing schemes. Especially, we focus on the relay selection optimization problem among multiple PUs and multiple SUs. The network-wide cooperation and competition are formulated as a bargaining game, and an algorithm is developed to derive the optimal PU-SU relay assignment and resource allocation. Evaluation results show that both primary and secondary users achieve significant utility gains with the proposed framework, which gives all of them incentive for cooperation.     

Capacity and Energy Efficiency of Multi-User Spectrum Sharing Systems with Opportunistic Scheduling

This paper investigates the capacity and energy efficiency of spectrum sharing systems with opportunistic user selection where a secondary network utilizes spectrum bands licensed to a primary network under interference regulation. In spectrum sharing systems, secondary users consume a fraction of their resources in sensing the channels to the primary users to comply with the interference constraints. Although more resources for sensing improve reliability and performance, the throughput loss due to time overhead and energy loss due to power overhead should be properly incorporated in performance evaluation. In this context, we define and derive a new metric ? average capacity normalized by the total energy consumption ? reflecting time and power overhead for spectrum sensing. Based on the developed framework, the optimal normalizedcapacity is investigated. We also propose a simple and practical suboptimal best-n scheme motivated by the infeasibility and high computational complexity of the optimal strategy, where n denotes the number of sensing secondary users. Our analytical and simulation results show that the proposed best-1 scheme is an energy-efficient technique with near optimality in terms of the capacity normalized by the energy consumption.     

A Stackelberg game for relay selection and power allocation in an active cooperative model involving primary users and secondary users

In recent years, cooperative communications have been widely used to improve the spectrum efficiency in cognitive radio networks. In this paper, we propose a new cooperative model involving primary and secondary users, where a primary transmitter may select a number of the secondary users to act as relays in order to maximize its data rate and to transmit at lower energy level, thereby saving energy and reducing interference at the secondary base station. The cooperative transmission is a multiple two‐hop relaying scheme, which guarantees an achievable data rate exceeding that in the direct transmission. In the proposed approach, the problem of joint relay selection and power allocation is formulated as a Stackelberg game, which converges to a unique optimal Nash equilibrium. Performance evaluation shows that this model offers benefit to both sides, where the primary users achieve higher data rate at lower energy consumption and the signal to interference plus noise ratio at the secondary base station is increased significantly. In addition, the results show that the proposed solution outperforms the investigated models in terms of achievable data rate.     

Cross‐layer design of partial spectrum sharing for two licensed networks using cognitive radios

To utilize spectrum resources more efficiently, dynamic spectrum access attempts to allocate the spectrum to users in an intelligent manner. Uncoordinated sharing with cognitive radio (CR) users is a promising approach for dynamic spectrum access. In the uncoordinated sharing model, CR is an enabling technology that allows the unlicensed or secondary users to opportunistically access the licensed spectrum bands (belonging to the so‐called primary users), without any modifications or updates for the licensed systems. However, because of the limited resources for making spectrum observations, spectrum sensing for CR is bound to have errors and will degrade the grade‐of‐service performance of both primary and secondary users. In this paper, we first propose a new partial spectrum sharing policy, which achieves efficient spectrum sharing between two licensed networks. Then, a Markov chain model is devised to analyze the proposed policy considering the effects of sensing errors. We also construct a cross‐layer design framework, in which the parameters of spectrum sharing policy at the multiple‐access control layer and the spectrum sensing parameters at the physical layer are simultaneously coordinated to maximize the overall throughput of the networks, while satisfying the grade‐of‐service constraints of the users. Numerical results show that the proposed spectrum sharing policy and the cross‐layer design strategy achieve a much higher overall throughput for the two networks. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Cluster‐based adaptive multispectrum sensing and access in cognitive radio networks

Spectrum sensing and access have been widely investigated in cognitive radio network for the secondary users to efficiently utilize and share the spectrum licensed by the primary user. We propose a cluster‐based adaptive multispectrum sensing and access strategy, in which the secondary users seeking to access the channel can select a set of channels to sense and access with adaptive sensing time. Specifically, the spectrum sensing and access problem is formulated into an optimization problem, which maximizes the utility of the secondary users and ensures sufficient protection of the primary users and the transmitting secondary users from unacceptable interference. Moreover, we explicitly calculate the expected number of channels that are detected to be idle, or being occupied by the primary users, or being occupied by the transmitting secondary users. Spectrum sharing with the primary and transmitting secondary users is accomplished by adapting the transmission power to keep the interference to an acceptable level. Simulation results demonstrate the effectiveness of our proposed sensing and access strategy as well as its advantage over conventional sensing and access methods in terms of improving the achieved throughput and keeping the sensing overhead low. Copyright © 2012 John Wiley & Sons, Ltd.     

混合频谱共享方式下多用户动态频谱分配算法

为解决混合overlay/underlay频谱共享方式下多用户动态频谱分配问题,构建了混合频谱共享方式下动态频谱分配模型,提出了基于Q学习的多用户动态频谱分配算法. 该算法在不对主用户产生有害干扰的前提下,以最大化次用户总吞吐量为目标,构建了与次用户相对应的虚拟次用户作为智能体. 通过与环境交互学习,进行信道和共享方式初选;频谱分配系统根据冲突情况和各智能体的学习结果调整信道分配策略直至次用户间无冲突. 仿真结果表明,该算法在无信道检测和信道先验知识的条件下,能根据前一时隙信道状态和次用户传输速率需求,实现动态信道分配和频谱共享方式确定,避免次用户间冲突,减少主次用户间冲突,有效提升次用户总吞吐量.     

Economic Approaches for Cognitive Radio Networks: A Survey

Efficient resource allocation is one of the key concerns of implementing cognitive radio networks. Game theory has been extensively used to study the strategic interactions between primary and secondary users for effective resource allocation. The concept of spectrum trading has introduced a new direction for the coexistence of primary and secondary users through economic benefits to primary users. The use of price theory and market theory from economics has played a vital role to facilitate economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks. With this motivation, we present an extensive summary of the related work that use economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks.     

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.     

基于合约制的认知网络协作频谱共享模型

为了提高认知无线电网络中主用户的能效和谱效,提出了一种基于合约制的协作频谱共享新模型。在该模型中,当主用户信道质量差时,次用户为其提供中继服务;作为回报,在主用户信道质量好时,次用户可以在一定的干扰约束下以underlay的模式和主用户共享频谱。在此框架下引入经济学中的合约理论,将主次用户间的协作问题建模为合约设计问题,并建立了主次用户评价合约收益的效用函数,将提高主用户的能效和谱效问题转变为设计合约使主用户获得最大效用的优化问题,并利用差分进化算法对该问题求解。最后,在不同的环境下,将主用户协作与不协作获得的效用进行对比,结果表明,主用户在没有额外投入频谱资源的条件下,不仅节省了发送功率,而且有效地提高了数据传输速率,进而提高了能效和谱效。     

基于认知的协作系统中继分配算法

随着无线移动通信系统的飞速发展,无线通信网络能耗急剧增加,基于中继协作技术的绿色无线通信研究受到众多研究者的关注.针对基于认知的中继协作系统,提出了一种以最大主系统能效为目标的中继分配算法.该算法在不影响主系统性能基础上,对主系统请求次系统用户作为中继转发数据,且共享主用户频谱进行了简要介绍.算法中次系统通过最大权重匹配方法为主系统分配中继（次用户）,在满足主系统能效最大化的同时,实现了次系统与主系统的频谱共享.对算法进行仿真验证,提出的算法能获得较高的主系统能效,同时提高了整个系统的频谱利用率.     

Coopetive Spectrum Trading – Creating Endogenous Spectrum Holes

Dynamic spectrum access has been proposed to address the spectrum scarcity. Based on this access mode, secondary users are allowed to opportunistically operate when primary users are absent. Secondary Users are, however, required to relinquish the spectrum upon return of the incumbent spectrum holder. Although it improves spectrum utility, opportunistic spectrum access limits secondary users’ access to exogenous spectrum holes vacated by primary users. We argue that spectrum holes should be endogenous, enabled by incentives to incumbent users to increase spectrum availability, while mitigating risk. To this end, we take a different perspective on dynamic spectrum sharing and propose a coopetive framework, whereby primary and secondary users engage in a cooperative, yet competitive, auction-driven spectrum sharing to enhance spectrum usage. In this framework, the primary users’spectrum is organized in three bands, namely exclusive usage, usage right and management right bands. Based on this structure, spectrum is traded as financial options to increase trading flexibility and capture the value primary and secondary users attach to spectrum access and usage. Spectrum trading between primary and secondary users is formalized as a utility maximization problem. Approximate solutions to this problem are derived and their performance is analyzed. The results show that spectrum trading, which combines revocable and exclusive leasing, provides higher utilities for both primary and secondary users.     

Hybrid model of inter-stage spectrum trading in multistage game-theoretic framework

Dynamic spectrum access(DSA),consisting of spectrum sharing and spectrum trading stage,becomes a promising approach to increase the efficiency of spectrum usage and system performance.In this paper,from the perspective of individual interest optimization,we focus on strategy adaptation of network users and their interaction in spectrum trading process.Considering adverse effects on decision-making accuracy and the fairness among network users via local information acquirement,a hybrid game model based on global information of relevant spectrum is proposed to formulate intelligent behaviors of both primary and secondary users.Specifically,by using the evolutionary game theory,a spectrum-selection approach for the evolution process of secondary users is designed to converge to the evolutionary equilibrium gradually.Moreover,competition among primary users is modeled as a non-cooperative game and an iterative algorithm is employed to achieve the Nash equilibrium.The simulation results show that the proposed hybrid game model investigates network dynamics under different network parameter settings.     

Cooperative spectrum sensing for cognitive radio networks in the presence of smart malicious users

Cognitive radio (CR) signaling imposes some threats to the network. One of these common threats is commonly referred to as primary user emulation attack, where some malicious users try to mimic the primary signal and deceive secondary users to prevent them from accessing vacant frequency bands. In this paper, we introduce a smart primary user emulation attacker (PUEA) that sends fake signals similar to the primary signal. We assume a smart attacker, in the sense that it is aware of its radio environment and may choose different transmission strategies and then, we compare it to an always present attacker. In the proposed smart attacker strategy, the occurrence of fake signal is adjusted according to the primary user activity. First, we investigate the received signal at the CR users under such attackers. Then, we formulate and derive cooperative spectrum sensing (CSS) rules for a cognitive network operating in the presence of a PUEA and propose a new spectrum sensing scheme based on energy detection. Simulation results show that our proposed method can mitigate the destructive effect of PUEA in spectrum sensing, compared to conventional energy detection spectrum sensing.     

一种多用户协同频谱感知功率控制方案

分析和研究了多用户协同频谱感知原理,通过时分方式,实现了多用户之间的频谱共享。同时为避免对主用户产生有害的干扰,从用户通过一种算法控制它的发射功率,保证主用户的通信服务质量。最后对多用户协同频谱感知和单用户频谱感知的性能进行了仿真研究,结果表明多用户协同频谱感知可以明显提高频谱感知的性能,克服阴影/衰落作用的不利影响,提高频谱利用率。     

动态频谱接入综述

动态频谱户在授权的频谱带宽中获得丰富频谱空隙。DSA技术可以缓解频谱短缺问题并且提高频谱利用率。文中讨论了DSA所面临的挑战,旨在揭示其未来的走向。介绍了前沿的频谱感知和频谱分享。调查了阻碍DSA成为主要的商业部署的挑战。为了应对这些挑战,建立了一个新的DSA模型,在这种模式下,授权的用户可以在DSA中相互合作,而且可以获得更加灵活的频谱共享。     

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.     

Quality of service assurance-based auction for spectrum sharing systems

Spectrum sharing has emerged as a promising solution to address the radio frequency spectrum bottleneck. The FCC has recently proposed a spectrum sharing framework that introduces a spectrum access system as the governing entity that manages access to spectrum for primary and secondary users to coexist. An important aspect of dynamic spectrum management is the pricing of spectrum from the perspective of both the primary and secondary users. Existing auction-based spectrum sharing models do not take into consideration an important aspect of successful secondary user operation: the duration of the available spectrum opportunity. In this paper we propose an auction-based spectrum sharing framework that statistically accounts for the accuracy of the estimates of spectrum availability duration. The proposed auctioning process allows both the PU and the SU to iteratively adjust their evaluation about the available spectrum opportunities over time and to achieve a price combination that maximizes their objectives. A method is proposed to statistically assure spectrum availability, supplementing the reporting method. Hidden Markov models and non-stationary hidden Markov models are used to estimate the activity of the spectrum, with simulation results showing high prediction accuracy.     

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.