Equation Chapter 1 Section 1基于中继的协作频谱感知性能分析及优化

提出了一种基于目标的中继协作频谱感知方案,证明了SU到SR链路上的信道条件对系统性能有较大的影响;鉴于此,提出了一种优化的最佳中继协作频谱感知(optimized BRCSS)方案,通过联合考虑目标SU到SR链路上的信道条件和 SR 到 FC 链路上的信道条件选择最佳认知中继;最后,从更实际的应用场景考虑,为了节约系统开销,进一步提出了一种自适应的最佳中继协作频谱感知方案（A-BRCSS）,即 SU 根据其信道条件,自适应地选择是否需要认知中继的协作传输。分析和仿真结果均表明,相比传统最佳中继协作频谱感知方案, Optimized BRCSS方案可以实现更高的感知性能;所提A-BRCSS方案可以实现几乎最佳的感知性能。     

基于最佳中继选择的协作频谱感知方案研究

 本文提出了一种基于最佳中继的多用户协作频谱感知方案,通过认知无线电网络中多用户间的相互协作,可以获得明显的空间分集增益,从而改善认知用户的检测性能．针对所提出的多用户协作感知方案,在瑞利衰落环境下分析了相应的系统检测概率,同时也理论推导了传统非协作方案的感知性能．根据检测概率的解析式,对非协作方案和多用户协作方案,进行了相应的数值实验和性能比较．与非协作感知方案相比,多用户协作方案能够显著提高主用户的检测概率．此外,随着候选中继用户数目增加,多用户协作方案对主用户检测概率的改善量越加明显．     

基于中继协作的认知无线电性能研究

频谱感知是认知无线电技术的关键。协作频谱感知能够充分利用网络资源,提高网络中认知用户的检测概率,降低认知用户的虚警概率。基于两个认知用户之间的中继协作,研究了协作频谱感知的感知性能与吞吐量的折衷。仿真结果表明：中继协作的频谱感知方法能够使得在充分保证对授权用户不造成干扰即检测概率一定时,能够有效地降低认知用户感知授权用户的虚警概率,缩短＂弱＂认知用户获得最大吞吐量的最优感知时间,提高其最大吞吐量,并提高认知系统的最大吞吐量。     

全双工中继协作下的认知MIMO系统吞吐量最大化研究

本文研究了全双工中继协作下的认知MIMO系统的平均吞吐量最大化问题。与传统的中继协作认知无线电系统不同的是,该系统模型中的双工中继节点既能协助认知用户源节点进行多天线频谱感知以提高频谱检测性能,也能解码转发认知用户源节点的发送信号以获得更大的系统吞吐量。为使系统平均吞吐量最大,首先,本文以认知用户能获得的最大平均频谱空洞被发现的概率为目标,对系统的帧结构进行优化以获得最佳的感知时间,接着对多个发送天线进行优化以选择出最佳的发送天线,并推导出了在总的发送功率和对主用户干扰受限条件下的认知用户源节点和双工中继节点的最佳功率分配方案。最后的仿真结果表明本文提出的系统模型和优化方案相比传统的双工等功率分配方案以及单工功率分配方案能够获得更大的系统平均吞吐量。      

n-out-of-K融合规则下增量式协作感知算法

该算法把协作中继分为前N个与后K?N个两部分,首先在前N个中继中感知,若不多于mL个中继检测到主用户或不少于mH个中继检测到主用户,则全局判定为存在或不存在频谱空洞;否则继续在后K?N个中继中感知,只有当前后两次感知不少于n个中继检测到主用户时则才全局判定不存在频谱空洞。在满足虚警概率与检测概率的前提下,构建最小化时隙消耗的目标函数,优化参数mL、mH与N。模拟表明,通过合理设置这些参数,在保证感知性能的前提下,所提增量协作算法的平均时隙消耗明显低于传统协作感知。     

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.     

基于可靠次用户信息的协作频谱感知算法研究

对认知无线电系统最基本要求之一就是次用户必须有能力以高的精确率来确定主用户是否存在。而以前对认知无线电频谱感知的研究表明:在实际认知网络中次用户之间的相互协作可以提高其频谱检测性能。然而,对于协作频谱感知而言,随着协作次用户数目的增加,势必会增大用于传输本地检测结果到融合中心的专用控制信道带宽,从而增加系统开销。该文在控制信道带宽有限的约束条件下,提出一种通过考虑可靠次用户信息的协作频谱感知算法来进一步改善频谱检测的性能。该算法的基本思想:只有具有可靠的本地检测结果的次用户才发送自己的检测结果到融合中心,否则,该次用户不发送任何信息。同时,对提出的该算法在理论上进行了推导,通过仿真结果表明:在控制信道带宽受限的约束下,相比于传统的或门协作频谱感知算法,提出的算法能够大大改善对主用户的检测性能。     

基于最优中继的自适应协作频谱感知算法

针对认知系统中感知信道存在衰落和中继能耗较大问题,提出一种兼顾感知性能和感知能耗的中继协作频谱感知算法。该算法通过机会中继协作、基于效益函数的最优中继协作和系统参数自适应调整机制,能够获得性能与能耗的优化折中。文章对所提算法进行了详细的理论推导和性能分析,并对非中继协作感知算法和最优中继固定的协作感知算法以及本算法在不同系统参数下的感知性能进行了仿真比较。结果表明本算法具有一定的优越性。     

认知无线网络中一种基于放大转发的协作传输策略

在不干扰主用户数据传输的条件下,通过次用户间的彼此协作传输,可以使认知无线网络获得明显的空间和时间分集增益,从而改善次用户传输性能。该文针对主次用户共存,主用户交替转移信道忙闲状态的网络环境下,提出了一种基于放大转发的协作传输方案,当主用户存在时机会的使用中继节点转发数据,并且对所提方案的无冲突传输时间进行了理论分析,给出了非协作传输和协作传输模式下的无冲突传输时间的解析表达式,理论分析和仿真结果表明,协作传输方案的无冲突传输时间明显优于非协作传输方案,次用户协作为认知无线网络带来可观的性能增益。     

认知无线电MAC层多用户协同感知机制优化

为了有效快速的寻找到频谱空洞并不对主用户造成干扰,频谱感知是认知无线电系统中具有重要意义的一环.而多用户协作感知可以进一步提高系统性能.本文关注认知无线电MAC层两种频谱感知机制主动感知和被动感知机制.在多用户协作的场景下,分析主用户活跃度对感知性能造成的影响.并提出了一种低复杂度的折衷接入延时和功率消耗的优化策略.通过理论分析和仿真结果可以看出,主动和被动感知机制下多用户协作感知可以有效的减小信道搜索时间,优化算法帮助动态地选取感知机制减小系统开销.     

Optimization of Time-Domain Combining Cooperative Spectrum Sensing in Cognitive Radio Networks

In cognitive radio networks, the secondary users take chances to access the spectrum without causing interference to the primary users so that the spectrum access is dynamic and somewhat opportunistic. Therefore, spectrum sensing is of significant importance. In this paper, we propose a novel time-domain combining cooperative spectrum sensing framework, in which the time consumed by reporting for one secondary user is also utilized for other secondary users’ sensing. We focus on the optimal sensing settings of the proposed sensing scheme to maximize the secondary users’ throughput and minimize the average sensing error probability under the constraint that the primary users are sufficiently protected. Some simple algorithms are also derived to calculate the optimal solutions. Simulation results show that fundamental improvement of the achievable throughput and sensing performance can be obtained by optimal sensing settings. In addition, our proposed scheme outperforms the general frame structure on either achievable throughput or the performance of average sensing error probability.     

基于部分感知用户协作的多天线频谱检测方案

In this paper, a cooperative spectrum sensing scheme, which is based on cooperation of a certain number of secondary users and cooperative diversity under multi-antenna scenario, is proposed. Under multiantenna scenario, we set a targeted detection probability and optimize the false alarm probability of the network by choosing a certain number of secondary users with the highest primary user’s signal to noise ratio. The detection performance of the network is also evaluated when all the secondary users are cooperating to illustrate the benefits of the proposed scheme as a contrast. In addition, how to choose the detection threshold of the secondary user is analyzed for the purpose of decreasing the average risk. Theory analysis and simulation results show that the optimum false alarm probability can be derived by cooperating a certain number of secondary users rather than all the secondary users and the detection performance of the network can be further improved if secondary users are equipped with multiple antennas. Also, a minimum average risk can be obtained by optimizing the detection threshold.     

Study the effect of PAPR on wideband cognitive OFDM radio networks

Cognitive radio (CR) technology is viewed as a novel approach for maximizing the utilization of the radio electromagnetic spectrum. Spectrum sensing methods are often used for finding free channels to be used by CR. Recently, Orthogonal Frequency Division Multiplexing system (OFDM) has been suggested as a candidate technology for multicarrier-based CR systems. However, one problem that appears in OFDM systems is the high Peak to Average Power Ratio (PAPR). In this paper, the effect of PAPR reduction of the primary signal on the performance of the multiband joint detection for wideband spectrum sensing and the profit of the primary user will be investigated. Moreover, the optimal solutions for the multi-band joint detection for the non-cooperative and cooperative schemes will be analyzed by considering the primary user’s PAPR reduction. Also, the wideband cooperative spectrum sensing to improve the signal detection with high reduction in the PAPR will be suggested. Simulation results show that the PAPR reduction decreases the total price of the primary user and the aggregate opportunistic throughput of the secondary user. The cooperative scheme is effective in improving the performance in terms of the aggregate opportunistic throughput with PAPR reduction.     

Cooperative spectrum sensing using amplify-and-forward relaying with partial relay selection in cognitive radio networks

Cooperative spectrum sensing has been shown to be an effective approach to improve the detection performance by exploiting the spatial diversity among multiple cognitive nodes. By using the amplify-and-forward relaying with partial relay selection, this paper proposes a novel cooperative spectrum sensing scheme, which provides higher detection performance and is interesting in distributed cognitive radio networks. In the proposed sensing scheme, the “best” cognitive relay by means of partial relay selection technique amplifies and forwards the signals transmitted from the primary user (PU) to the cognitive user (CU). Then the CU detects PU’s states (i.e., presence or absence) via an energy detector. Moreover, the average missed-detection probability of proposed sensing scheme is studied over Nakagami-m fading channels, where m is a positive integer. In particular, the tight closed-form lower bounds of the average missed-detection probability are presented for the convenience of performance evaluation in practice. Finally, numerical results are provided to validate the derived closed-form lower bounds and the influence of the number of cognitive relays on the detection performance is also discussed.     

频谱协作认知检测算法研究

为实现对低信噪比主用户信号进行可靠的检测,论文结合基于循环平稳的主用户信号具有不同循环频率的特性,以及次用户间的协作检测能有效地克服无线环境中多径衰减和阴影效应等不利因素影响的特点,提出了基于循环平稳特性的协作频谱检测算法。算法利用次用户对主用户信号的多个不同循环频率进行协作检测,并对各个次用户独立的检测结果进行权值数据融合,从而实现最终全局判决。同时,为进一步改善检测性能,论文研究了基于最大比合并的权值优化方法。仿真实验表明即使信号在较低信噪比情况下,论文研究的算法亦具有较好的检测性能。      

Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

Analysis of secondary throughput and optimization in cooperative spectrum sensing

In cooperative spectrum sensing,more secondary user makes more opportunity for detecting the vacant spectrums,which resulting the spectrum utilization improved,however much bandwidth would be occupied for sending the local observation results,inducing the reduced secondary throughput.In this paper,an adaptive algorithm for selecting detection threshold was proposed,where the maximized secondary throughput can always be achieved while assuring sufficient protection to primary user,regardless of the number of...     

Optimization of sensing time in multichannel sequential sensing for cognitive radio

This paper studies the design of sensing time in multichannel sequential sensing for cognitive radio under the multichannel sensing slots and one transmission slot scheme. Firstly, we consider the case where the channel idle probability is known. In this case, when the channels’ signal‐to‐noise ratios (SNRs) are equal, we prove that there exist optimal sensing times that maximize the achievable throughput for secondary user, while primary user is sufficiently protected. When the channels’ SNRs are different, brute‐force search is used to find the optimal sensing order that maximizes the achievable throughput of secondary user, and the corresponding optimal sensing times will be obtained. Then, a suboptimal and low‐complexity approach of one‐slot sensing time without knowing the channel idle probability is proposed. The proposed approach solves the problem of sensing order by selecting the channel with the minimum sensing time in the next sensing slot when the channels’ SNRs are different. Numerical results show that the proposed approach achieves a performance close to that of the optimal sensing time under different conditions and has significant performance improvement over the approach of fixed sensing time. Copyright © 2011 John Wiley & Sons, Ltd.     

Throughput Maximization in Cognitive Radio System with Transmission Probability Scheduling and Traffic Pattern Prediction

In this paper, we propose a novel transmission probability scheduling (TPS) scheme for the opportunistic spectrum access based cognitive radio system (OSA-based CRS), in which the secondary user (SU) optimally schedules its transmission probabilities in the idle period of the primary user (PU), to maximize the throughput of the SU over a single channel when the collision probability perceived by the PU is constrained under a required threshold. Particularly, we first study the maximum achievable throughput of the SU when the proposed TPS scheme is employed under the assumption that the distribution of the PU idle period is known and the spectrum sensing is perfect. When the spectrum sensing at the SU is imperfect, we thoroughly quantify the impact of sensing errors on the SU performance with the proposed TPS scheme. Furthermore, in the situation that the traffic pattern of the PU and its parameters are unknown and the spectrum sensing is imperfect, we propose a predictor based on hidden Markov model (HMM) for the proposed TPS scheme to predict the future PU state. Extensive simulations are conducted and show that the proposed TPS scheme with the HMM-based predictor can achieve a reasonably high SU throughput under the PU collision probability constraint even when the sensing errors are severe.