认知无线电网络基于F范数的频谱共享

针对多用户多输入多输出认知无线电网络的频谱共享问题,提出一种在保证授权用户服务质量要求的前提下,以认知网络容量最大化为目标的基于F范数的频谱共享方法.该方法利用信道矩阵的F范数选择认知用户以获得认知网络的多用户分集增益,并采用两次选择的方式降低算法的复杂度,通过将认知用户的发射信号投射到干扰信道的零空间来避免认知用户对...     

认知无线电的合作频谱检测分析

认知用户需要持续快速地检测主用户的出现,对基于认知无线电的合作频谱检测机制进行了分析。在理想的两用户网络中,认知用户采用合作机制可以提高系统的平均侦测时间。在多认知用户网络中,参与合作的用户越多,单个认知用户对主用户的侦测概率越高。对于多用户网络,还考虑了整体的实现。     

可任意阶扩展的认知无线Ad Hoc网络频谱共享模型

目前认知无线Ad Hoc网络(CRAHNs)频谱共享模型的研究大多忽视了未被授权频谱被占用过程对授权频谱被一、二级用户占用过程的影响,也有研究同时考虑了一、二级信道被占用的情况,提出了简化的排队模型,但是在进行性能分析时存在较大误差.主要挑战来自于高维马尔可夫状态转移图归纳的复杂性和计算的复杂性.本文研究提出一种新的分...     

认知无线电中的频谱共享技术

由于认知无线电网络的一些独有的特性,比如,可用频谱资源的动态变化以及与第一类用户的共存,使得认知无线电网络中的频谱共享技术面临着许多新的挑战。当前关于频谱共享技术的研究旨在应对这些挑战,并且主要从以下四个方面着手：网络架构,频谱分配行为,频谱接入技术和共享频谱的范围。     

认知无线电频谱共享中的博弈论算法

首先介绍了认知无线电技术和博弈论思想,然后按照不同的分类准则,考虑无线网络资源分配的实际情况,描述了两种常用的博弈论类型：非合作型博弈模型和合作型博弈模型。重点研究了两种博弈模型在认知无线电频谱共享技术中的资源分配问题。     

认知无线电中的频谱共享技术

认知无线电（cognitive radio,CR）具有动态重用空闲频谱资源的能力,可以有效提高频谱利用率,是一种智能的频谱共享技术。文章给出了一种频谱共享的过程,阐述了频谱共享各个步骤包括频谱感知、频谱分配、频谱接入和频谱移动的概念、功能和研究现状,分析了频谱共享的关键技术,重点介绍了其中的频谱池策略、频谱分配算法和功率控制算法。     

Soft Combination Schemes for Cooperative Spectrum Sensing in Cognitive Radio Networks

This paper investigates linear soft combination schemes for cooperative spectrum sensing in cognitive radio networks. We propose two weight-setting strategies under different basic optimality criteria to improve the overall sensing performance in the network. The corresponding optimal weights are derived, which are determined by the noise power levels and the received primary user signal energies of multiple cooperative secondary users in the network. However, to obtain the instantaneous measurement of these noise power levels and primary user signal energies with high accuracy is extremely challenging. It can even be infeasible in practical implementations under a low signal-to-noise ratio regime. We therefore propose reference data matrices to scavenge the indispensable information of primary user signal energies and noise power levels for setting the proposed combining weights adaptively by keeping records of the most recent spectrum observations. Analyses and simulation results demonstrate that the proposed linear soft combination schemes outperform the conventional maximal ratio combination and equal gain combination schemes and yield significant performance improvements in spectrum sensing.     

协作频谱感知在认知网络中的应用

认知无线电能够灵敏感知周围环境的变化,通过频谱感知功能发现频谱空洞,使得认知无线电能够与周围通信环境相适应。在认知无线电网络中,认知用户（次用户）必须连续地监控频谱,检测主用户是否存在。如果主用户存在,次用户必须尽快地退出该频段,从而不影响主用户。在文中采用一种协作机制,即两用户进行协作频谱感知,从而提高主用户的检测率,减少了检测时间,并且得到捷变增益。我们用Matlab给出仿真结果。     

认知无线电中基于加权硬判决的协作频谱感知算法

Weighted one bit hard combination for cooperative spectrum sensing is proposed in this paper. Two thresholds are adopted to divide the possible energy value into three weighted regions.If the energy value falls into the corresponding region, it will be judged as “1”, no information or “0”. When the probability of false alarm is constrained to be constant, the objective is to maximize the probability of detection. The optimization problem is simplified by separating the weight of the middle region into several intervals. Simulation results show that the sensing performance of the proposed scheme is much better than that of the traditional one bit hard combination scheme and almost the same as that of the equal gain combination (EGC) scheme. Moreover, compared with the traditional one bit hard combination, fewer average sensing bits are required to transmit to the data fusion center with the proposed method.     

Multiple Relay Selection Based on Game Theory in Cooperative Cognitive Radio Networks

Due to the inefficiency of traditional fixed spectrum allocation policies, the paradox of apparent spec-trum scarcity occurs while most of the bands are under-utilized. This has prompted proposals for Dynamic spec-trum sharing (DSS), which explains why Cognitive radio network (CRN) has been widely accepted as a promising approach to settle inefficient usage of scarce available radio spectrum. As a subset of DSS, Dynamic spectrum leasing (DSL) strategy has been proposed based on game idea, where Primary user (PU) has an incentive to allow Cog-nitive users (CUs) to access its licensed spectrum for a fraction of time in exchange for revenue. This paper pro-poses an approach, named multiple relay selection based on Game theory (GTMRS), to optimize the utilities of PU and CUs as a whole, where a pricing-based spectrum leas-ing mechanism is applied. While the parameter price c is jointly determined by PU and CUs, all selected cognitive user's optimal cooperative powers can be satisfied through a non-cooperative game among themselves. Numerical re-sults show that more CUs are involved in the cooperation and both utilities of PU and CUs as a whole are improved, which means the whole system throughput is increased.     

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．     

认知无线电中的协作频谱检测技术

频谱检测技术是认知无线电中极其重要的环节,而协作式的频谱检测由于其良好的检测性能日益受到人们的关注。基于能量检测,协作频谱检测的算法主要有：与（AND）算法、或（OR）算法、计数算法、分区算法、似然比算法、线性加权算法和分布式无线通信系统（DWCS）算法。分析表明,这些协作检测算法能够改善系统的检测性能、减低干扰冲突、提高频谱利用率。     

认知无线电网络中基于合作的频谱检测研究

在认知无线电技术的实际应用场景中,针对单认知用户本地检测的局限性,以提高认知无线电网络的检测性能和缩短检测时间为目标,分别从分布式多用户和协作分集两种合作检测方式出发,对认知无线电网络中的合作检测算法和机制进行了分析及讨论,并在此基础上进一步提出了认知无线电合作检测的未来研究方向及难点问题.     

A Robust Cooperative Spectrum Sensing Scheme in Cognitive Radio Systems

Performance of cluster-based cooperative spectrum sensing is more greatly improved than that of the traditional cooperative spectrum sensing.However,the style of clusters is not pointed out on traditional cluster-based method.In view of all the fading in the cooperative spectrum sensing,space diversity,and selective diversity,a robust cooperative spectrum sensing scheme based on clusters is proposed.Simulation results show that the detection performance of this new scheme is more close to that of the ideal cluster-based cooperative spectrum sensing scheme,and the excellent performance with higher reliability is gained relative to the actual cluster-based cooperative spectrum sensing scheme.Finally,the number of users in a cluster of the proposed scheme is discussed.The two users in a cluster are not the optimal solution to the overall implementation of cognitive radio.     

认知无线电网络的一种协作频谱感知方案

认知无线电技术能够让非授权用户利用已经分配给授权用户的频段.为了不对首要用户的工作造成干扰,认知用户需要对频谱进行不间断的监测来判断首要用户是否存在.因此,频谱的感知是认知无线电技术的关键.协作频谱感知能够充分的利用网络资源,提高网络中的认知用户的检测概率.文中笔者简单地介绍了一种协作频谱感知的方案.仿真结果表明,通过该方法能够提高网络中认知用户的检测概率,提高网络的检测灵敏度.     

一种优化的认知无线电频谱感知策略

协作频谱感知技术可以有效地避免频谱感知过程中的隐终端问题,降低感知用户对主用户的干扰。但是随着协作感知中感知用户数目的增加,感知中的通信量也会增加。相对于传统的协作感知单门限判决法,双门限判决法可以在对感知性能影响很小的情况下,降低协作感知过程中的通信量。在传统的双门限感知技术的基础上,提出了一种基于权重的双门限协作算法。仿真结果表明,在保证较小的感知通信量下,相对于传统的双门限判决,提出的算法可以提高系统的感知性能。     

认知无线电频谱分配的博弈论方法

认知无线电中频谱分配问题目前受到了极大的关注。在问题的分析中,涉及了大量策略选择问题,因而可以利用博弈论的相关原理对其进行分析研究。文章介绍了认知无线电频谱分配的一些关键问题,分析了博弈论方法在认知无线电研究中的应用条件,并阐述了认知无线电频谱分配问题的博弈论框架,为今后的相关研究起到积极的促进作用。     

认知无线电多时隙联合频谱感知方法及优化

为了降低认知无线电中次用户对主用户的干扰,提出了次用户通过多个时隙的能量感知联合检测主用户的频谱感知方法。每个传输帧被分成若干个时隙,次用户在每个时隙的开始进行能量感知,通过合并多个时隙的感知结果,提高次用户对主用户的检测性能。为了最大化次用户的频谱效率,将主用户状态建模为二维马尔科夫随机过程,并根据该过程优化单时隙频谱感知时间。仿真结果表明：相比Liang的“先听后传”频谱感知方法,提出方法仅牺牲14％的频谱效率,却使干扰概率降低了28％;随着信噪比增加,提出方法的最大频谱效率逐渐接近“先听后传”频谱感知方法。     

协同认知无线网络中自适应中继节点选择算法

最优停止规则算法的优点是避免主用户考察所有次用户,使主用户能在较短观测时间内挑选出满足通信服务质量的中继节点。但存在些许不足之处,如仅考虑了单次协同通信情况,没有充分利用历史中继节点选择信息。为了克服上述缺点,需要优化该算法的性能,通过引入反馈机制,提出了自适应中继节点选择算法,在每次中继节点选择结束后更新信息库中次用户中继概率,主用户从中继概率高的次用户开始观测。研究结果表明:自适应中继节点选择算法的效率要比最优停止规则算法高;该算法可进一步减少观测次数,降低系统的传输时延和观测能耗,提高主用户的平均吞吐率。     

Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks

In this work, we propose a game theoretic framework to analyze the behavior of cognitive radios for distributed adaptive channel allocation. We define two different objective functions for the spectrum sharing games, which capture the utility of selfish users and cooperative users, respectively. Based on the utility definition for cooperative users, we show that the channel allocation problem can be formulated as a potential game, and thus converges to a deterministic channel allocation Nash equilibrium point. Alternatively, a no-regret learning implementation is proposed for both scenarios and it is shown to have similar performance with the potential game when cooperation is enforced, but with a higher variability across users. The no-regret learning formulation is particularly useful to accommodate selfish users. Non-cooperative learning games have the advantage of a very low overhead for information exchange in the network. We show that cooperation based spectrum sharing etiquette improves the overall network performance at the expense of an increased overhead required for information exchange.