最优认知用户配对与协作感知算法研究

针对协作算法频谱感知和时隙消耗方面的不足,提出一种最优用户配对与协作感知算法。采用接收信噪比最优的认知用户为感知用户且以接收信噪比次优的认知用户为其中继的配对准则,获得最佳频谱感知性能。通过优化设置协作门限,选择性地采用非协作或协作模式,获得更低的时隙消耗。同时,推导了在瑞利平坦衰落环境下该算法的频谱检测概率下界与时隙消耗。数值计算结果表明,与原有算法相比,该算法不仅检测概率更高且时隙消耗更低。     

优化的最佳中继协作频谱感知

在基于中继的协作频谱感知中,尽管通过引入认知中继可有效提高协作频谱感知性能,然而认知中继的引入也会带来额外的系统开销及复杂度增加问题。为了节约系统开销,本文在前期取得研究成果的基础上,进一步提出了一种基于删余的最佳中继协作频谱感知方案,只有当次用户检测到主用户信号且目标次用户的报告信道衰落严重时,才申请认知中继的协作传输,同时目标次用户将其检测到的感知信息发送到认知中继;最后,分别从检测性能和次系统可获得的容量角度对所提方案下的协作频谱感知性能进行了理论分析。分析和仿真结果表明,所提方案可以有效提高检测性能,当确保主用户受到足够保护的前提下,利用所提方案可以获得更高的次系统容量。      

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。     

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。     

基于第N佳中继选择的协作频谱感知检测概率分析

为获得最佳感知,系统在n个备选用户中选择最佳中继进行协作感知。但实际系统可能由于各种原因选择了第二佳或乃至更为一般的第N佳中继。为此,提出基于第N佳中继选择的协作频谱感知,推导了其在瑞利平坦衰落下的检测概率,并给出闭合表达式。数值计算表明,随着N的增加,系统检测概率不断下降,乃至低于任意选择;随着n的增加,基于最佳或接近最佳选择的系统检测概率明显提高,而基于最差或接近最差选择的系统检测概率则有所下降。     

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．     

基于中继的协作频谱感知

频谱感知技术是认知无线电系统实现的前提和基础。由于无线衰落环境下单节点频谱感知结果可靠性不高,主要讨论协作频谱感知中的中继协作频谱感知技术。针对单个中继节点的协作频谱感知网络,分析了在AF协议下的频谱感知结果。导出了在瑞利衰落环境下中继节点参与协作感知的检测概率上限的闭合表达式,并进行了数值仿真。数值分析结果表明中继节点参与协作能够提高频谱感知性能。     

非理想频谱检测对主用户干扰的性能分析

实际中认知中继网络的频谱检测不可能完全正确检测频谱状态,次级用户传输会对主用户传输产生干扰。在分布式协作频谱检测和集中式协作频谱检测情况下,研究了认知中继网络中非理想频谱检测对主用户干扰性能的影响。在瑞利信道下推导了非理想频谱检测条件下主用户干扰概率的数学表达式。最后,仿真结果证明了理论分析的合理性,并表明非理想频谱检测会对主用户产生较大干扰,而中继节点数目的增加可以明显降低干扰概率。     

双信任度加权的K秩准则频谱感知算法

基于信任度的协作频谱感知算法,可以很好地解决本地检测的隐藏终端和频谱衰落等问题。但其对于多用户的大量数据分析,缺乏高效的数据统计和融合算法,算法的检测性能有待提高。为此,提出了一种基于双信任度加权的K秩准则协作频谱感知算法。它在主用户存在与不存在两种情况下,分别采用不同的信任度加权的算法,并与K秩准则的融合策略相结合。仿真结果表明,算法在保证数据统计和融合能力的前提下,有效的提高了检测性能和感知能力。     

基于自适应决策融合的合作频谱感知方法

频谱感知是认知无线电(CR)的关键技术之一。在该机制中,对主用户(PU)信号的可靠检测是实现CR的前提。提出一种基于自适应决策融合的合作频谱感知算法用于频谱感知,该算法通过估计PU的先验概率与各个CR用户(SU)的漏检及虚警概率,然后运用Chair-Varshney准则对局部判决进行决策融合以得到全局判决。仿真结果表明,采用该方案的全局虚警和漏检概率明显低于单个SU,可有效提高CR系统频谱感知的可靠性。     

CR网络中采用平均检测概率约束的空时二维感知方法

针对认知无线电网络的空闲频谱检测,提出一种采用平均检测概率约束的空时二维感知方法。以检测概率在整个检测区域内的统计平均值,作为从用户（认知用户）接入主用户（授权用户）频谱的约束,并由此设置检测门限,在理论上得到时域、空域及空时二维空闲频谱接入概率。分析和仿真结果表明,与采用检测概率做约束的传统方法相比,以平均检测概率做约束所得到的时域虚警概率和空域虚警概率均降低,认知无线电网络空时二维空闲频谱的接入概率显著提高。      

认知系统中多天线协作频谱感知方案

针对认知无线电的核心问题——频谱感知,采用性能好的协作频谱感知,这里研究了认知无线电系统中一种多天线协作频谱感知方案,此方案中的噪声信号和主用户的信号均认为是独立复高斯随机信号。同时,次用户将检测到的信号通过波束成形后传向融合中心,而优化函数为发射功率受限的条件下,最大化全局的检测概率。理论推导和方针结果表明,所提出的方案有效地提高了检查概率,充分发挥了空间分集和多用户分集的优势,普遍提高了系统的感知概率。     

认知中继网络中认知用户基于频谱感知机会中继的中断性能分析

认知无线电中继网络中,认知用户需要成功感知到其所在簇内的主用户频谱空穴后才能成为认知中继节点,且各认知中继节点发射功率受到各自主用户干扰温度限制(ITC)。该文对认知中继节点采用分布式空时编码和解码转发协议时认知用户的中断性能进行了分析;给出了认知用户在干扰温度限制下中断概率的上下界,得出中断概率的上下界在不同干扰温度限下与认知用户归一化数据速率、中继数量和其对主用户检测概率的关系。给出了源节点和频谱感知中继节点在相同干扰温度限下的数值仿真,并对仿真结果进行了分析。     

Adaptive Decode-and-Forward Protocol Based Cooperative Spectrum Sensing in Cognitive Radio with Interference at the Secondary Users

In this paper a novel multiple-user cooperative spectrum sensing scheme (MCSS) based on hybrid relay is proposed to achieve the spatial diversity gain in detection of the primary user (PU) in a cognitive radio (CR) network. A practically important case where co-channel interference signals are present at the network is considered for the analysis. Closed-form expressions of detection probability \((\hbox {P}_{\mathrm{d}})\) and false alarm probability \((\alpha )\) for the proposed adaptive decode-and-forward based multiple-user cooperative spectrum sensing scheme (ADF-MCSS) using energy detector over Rayleigh fading sensing channels is derived in presence of co-channel interference at the secondary user which is far away from the PU. Further we extend the concept of two user amplify-and-forward (AF) and decode-and-forward (DF) cooperative spectrum sensing schemes in multiple-user scenario (i.e. AF-MCSS and DF-MCSS) over Rayleigh fading channels when the secondary user (which is far away from PU) is affected by interference. Closed-form expressions of AF-MCSS and DF-MCSS schemes over a Rayleigh fading channels are also evaluated and compared with that of proposed ADF-MCSS in presence of interference signals at the secondary user. Further the performance analysis of AF-MCSS, DF-MCSS and ADF-MCSS schemes are compared with the existing non-cooperative spectrum sensing schemes in presence of interference at the secondary user. Our analysis is validated by numerical and simulation results for multiple-user CR network. The impact of number of cooperative relays, SNR in sensing channel, energy of interference signal, false alarm on detection probability in proposed ADF, AF and DF schemes is shown.     

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.     

Simultaneous spectrum sensing,data transmission and Energy harvesting in multi‐channel cognitive sensor Networks with imperfect signal cancellation

In multichannel cognitive sensor networks, the sensor users which have limited energy budgets sense the spectrum to determine the activity of the primary user. If the spectrum is idle, the sensor user can access the licensed spectrum. However, during the spectrum sensing, no data transmits. For improving the network throughput and saving more energy consumption, we propose the simultaneous spectrum sensing and data transmission scheme where the sensor receiver decodes the received signal, and from the remaining signal, the status of the channel (idle/busy) is determined. We also consider that the sensor users are powered by a radio‐frequency (RF) energy harvester. In this case, energy harvesting, data transmission, and spectrum sensing are done simultaneously. On the other hand, we select the proper sensor users for spectrum sensing and energy harvesting. We also allocate the best channels for data transmission simultaneously so that the network throughput maximizes and the constraints on the energy consumption and the detection performance are satisfied for each band. We formulate the problem and model it as a coalition game in which sensors act as game players and decide to make coalitions. Each coalition selects one of the channels to sense and transmit data, while the necessary detection probability and false alarm probability and also the energy consumption constraints are satisfied. The utility function of a coalition is proposed based on the energy consumption, false alarm probability, detection probability, and the network throughput. This paper proposes an efficient algorithm to reach a Nash‐stable coalition structure. It is demonstrated that the proposed method maximizes the network throughput and reduces the energy consumption while it provides sufficient detection quality, in comparison to other existent methods.     

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。     

感知不确定下卫星认知无线网络多频谱接入优化策略

针对卫星认知无线网络频谱感知不确定性较大导致传统频谱接入机制效率降低的问题,该文提出一种基于动态多频谱感知的信道接入优化策略。认知LEO卫星根据频谱检测概率与授权用户干扰门限之间的关系,实时调整不同频谱感知结果下的信道接入概率。在此基础上以系统吞吐量最大化为目标,设计了一种基于频谱检测概率和虚警概率联合优化的判决门限选取策略,并推导了最佳感知频谱数量。仿真结果表明,认知用户能够在不大于授权用户最大干扰门限的前提下,根据授权信道空闲状态动态选择最佳频谱感知策略,且在检测信号信噪比较低时以更加积极的方式接入授权频谱,降低了频谱感知不确定性对信道接入效率的影响,提高了认知系统吞吐量。     

基于HMM和平衡二叉树递归搜索的宽带频谱感知

为了使得二级或无许可证用户在给定宽带上获取空闲的子带以供使用,针对认知无线电中的宽带频谱感知技术进行研究,提出一种有效的宽带频谱感知算法。算法采用隐马尔可夫模型(HMM)对初级用户的动态行为进行建模,以克服目前宽带感知技术的局限性;其次,利用现有窄带感知技术,将感知频带划分为较小的频道,将其建模为一棵平衡二叉树,并对频谱孔洞进行递归搜索。如果检测到有孔洞在频率上相邻,则将它们合并成一个单一的频谱孔洞,使得认知二级用户的容量在整个频带上最大化。仿真实验结果表明,与现有宽带频谱感知方法相比,提出的宽带频谱感知算法具有更好的感知性能增益和更强的鲁棒性。     

Cooperative Spectrum Sensing with Adaptive Node Selection for Cognitive Radio Networks

In cooperative spectrum sensing, secondary users can cooperate based on their local sensing observations so as to detect primary signals in a more reliable manner. However, because of the low strength of received primary signals, observations from some secondary users may contribute little to global decisions at the fusion center. To reduce energy consumption and sensing overhead, cooperation is recommended only with a subset of nodes receiving high-strength primary signals. This paper proposes a selection probability based cooperative spectrum sensing scheme that exploits historical observations to exclude nodes receiving low-strength primary signals. The selection probability is maintained based on local sensing information and global decisions. Simulation results demonstrate that the proposed scheme can exploit location advantages and shows almost the same detection performance as cooperative spectrum sensing with accurate node selection.