Detection efficiency of cooperative spectrum sensing in cognitive radio network

Sensing the spectrum in a reliable and efficient manner is crucial to cognitive radio. To combat the channel fading suffered by the single radio, cooperative spectrum sensing is employed, to associate the detection of multiple radios. In this article, the optimization problem of detection efficiency under the constraint of detection probability is investigated, and an algorithm to evaluate the required radio number and sensing time for maximal detection efficiency is presented. To show the effect of cooperation on the detection efficiency, the proposed algorithm is applied to cooperative sensing using the spectral correlation detector under the Rayleigh flat fading channel.     

Optimal fusion rule for cooperative spectrum sensing in cognitive radio networks

In this paper,we analyze performance of cooperative spectrum sensing under counting rules when exponential model is utilized to characterize the burst nature of primary user(PU) link.Our objective is to minimize the average error probability(AEP) so that the link utilization in the considered link achieves its maximum.We derive a closed-form expression of AEP as well as the probability of interference(PoI) by classifying cognitive transmission into six events.Then,we consider the minimization of AEP over counting rules under the constraint of interference.As the solution,we develop an efficient algorithm to evaluate the optimal fusion rule.Finally,we verify our analysis in numerical results.     

基于信道统计特征的认知无线电协作频谱检测

针对认知无线电到融合中心间的控制信道为Nakagami-m衰落信道的情况,研究了认知无线电协作频谱检测问题,推导出融合中心利用衰落信道统计特征的似然比协作频谱检测公式.该方法不需要瞬时信道状态信息,简化了协作频谱检测过程,便于实际应用.通过仿真对融合中心的协作频谱检测性能进行了分析,结果表明:利用衰落信道统计特征的似然比协作频谱检测的性能较利用瞬时信道状态信息的似然比频谱检测性能略有下降,但是在高信噪比或衰落不严重的情况下,二者的性能非常接近,认知无线电节点个数对两种频谱检测方法间的性能差距几乎没有影响.     

SNR-based weighted cooperative spectrum sensing in cognitive radio networks

Cooperative spectrum sensing (CSS) is an approach to confront fading environment. However, in conventional cooperative spectrum sensing (CCSS), the difference among the secondary users (SUS) is ignored when SUS suffer from different fading. In this article, a signal-to-noise ratio (SNR)-based weighted spectrum sensing scheme is proposed to improve the sensing performance. The sensing performance of the weighted spectrum sensing scheme is then derived. Considering the minor contribution of the SUS with small weighted factor, a selective CSS scheme is proposed, where SUS with low SNR are not selected into cooperative spectrum sensing. The simulation results confirm the analytical results. And the performance of weighted scheme is better than that of conventional schemes. In the case where the SNR of SUS are randomly distributed, the performance of selective scheme is almost the same as the weighted scheme while the number of cooperative SUS is reduced to save the consumption of system resource in cooperation with little additional complexity.     

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。     

最优线性认知无线电协作频谱感知技术研究

频谱感知是检测频谱空穴,实现动态频谱接入的前提和关键。单认知用户检测存在阴影效应和多径衰落等影响,检测效果较差。多用户协作频谱感知是目前频谱感知的主要手段。文中针对常用的协作频谱感知方法的不足,提出一种基于最优线性加权的协作频谱感知方法,对其检测模型与检测算法进行分析,并进行仿真。仿真结果表明,最优线性加权协作频谱感知在相同的条件下相比常用协作频谱感知具有更大的检测概率,更优良的检测性能。     

基于人工神经网络的认知无线电频谱感知研究

认知无线电是一种新的智能无线通信技术,通过感知周围环境特征,并采用构建理解的方法进行学习。频谱感知技术是认知无线电系统设计的重要组成部分,本文提出了基于人工神经网络（ANN）算法的认知无线电感知技术。由于单用户检测存在检测精度不高的问题,本文通过采用ANN的自主学习能力设计频谱检测分类器,对以往分类器所收集的环境信息进行学习和储存,从而对以后感知新的环境时起到先验信息的作用,能快速准确地判决出主用户的存在与否。通过与能量检测和循环平稳检测对不同调制方式信号进行信号识别仿真实验可以看出,相比原有的单用户频谱检测技术,ANN具有更高的有效性和可靠性。     

Delay QoS guaranteed cooperative spectrum sensing in cognitive radio networks

This letter proposes a delay QoS (Quality-of-Service) guaranteed cooperative spectrum sensing framework in which secondary users conduct spectrum sensing and data transmission simultaneously over two different parts of the primary user spectrum band. The optimal multi-minislot sensing scheme and the optimal fusion scheme are derived to minimize the transmission delay. Simulation results show that the delay performance is further improved by using the optimal fusion scheme, and the multi-minislot sensing scheme can achieve a time diversity gain in the delay performance.     

恶意环境中基于能量效率的安全协作频谱感知

频谱感知是认知无线电网络运行的前提,但是在恶意环境中,频谱感知数据存在被篡改的威胁.针对该问题,提出了一种低开销的对称加密方法,采用报文鉴别码对次级用户报告的数据进行鉴权,保证数据的完整性,从而缓解攻击对感知性能的影响.提出了协作频谱感知中能量效率的概念,并通过改变报文鉴别码长度优化能量效率.仿真验证了上述方法的有效性并给出了优化问题的数值解.     

认知无线电中协作压缩频谱感知算法

针对宽带频谱认知无线电环境中,传统能量检测法在信噪比较低时,容易出现误检而使系统的检测性能下降的问题,文中提出了一种新型高性能的协作频谱感知算法,它是基于压缩理论的多节点频谱感知方法,各节点之间采用基于双判决门限的协作方式。仿真结果显示,双门限协作压缩频谱感知算法在低信噪比的情况下,检测性能明显优于传统能量检测法。     

认知无线网络频谱感知与节点协同问题综述

认知无线电是被公认的解决移动无线网络频谱资源短缺和频谱资源动态分配问题的最有效和最有潜力的技术。基于认知无线电技术目前在移动无线网络中的实际应用情况,详细分析了认知无线网络目前所存在的无线频谱资源感知、探测和接入机制以及多用户节点协同等问题,并综述了频谱资源分配算法和认知无线网络容量问题的最新研究进展,最后提出用博弈论来研究解决认知无线网络多用户协同问题中的用户自私行为。     

认知无线电中基于拟合优度的多天线协作频谱检测

本文提出一种噪声方差未知时,基于拟合优度的多天线协作频谱检测方法。通过计算多个天线采样样本均值和方差比的分布函数与经验分布函数之间的Anderson-darling(AD)距离,并与备选的门限值比较,实现频谱检测。论文分析了衰落信道下,基于AD检验的协作频谱检测的虚警概率和检测概率下界。理论分析和仿真结果表明,基于AD检验的协作检测比基于随机矩阵的协作检测具有更好的性能,特别是在低信噪比和小样本条件下。     

一种基于功率限制下的认知无线电的频谱感知模型

文中在功率限制规则下提出了一种模型,考虑到了路径衰减指数、角度准、发射功率对检测性能的影响,更具有实际性和精确性。本文主要在路径衰减指数α2〉α1时通过仿真合作增益方面分析了检测性能,同时考虑到角度准、发射功率对检测性能的影响。通过仿真可以看出,在α2〉α1的情况下很难得到较好的合作增益改善。从而得到基于合作中继的方法并不适用于IEEE802.22系统。     

Dynamic control approaches of spectrum sensing in multi-band cognitive radio networks

In this paper,the dynamic control approaches for spectrum sensing are proposed,based on the theory that prediction is synonymous with data compression in computational learning. Firstly,a spectrum sensing sequence prediction scheme is proposed to reduce the spectrum sensing time and improve the throughput of secondary users. We use Ziv-Lempel data compression algorithm to design the prediction scheme,where spectrum band usage history is utilized. In addition,an iterative algorithm to find out the optimal number of spectrum bands allowed to sense is proposed,with the aim of maximizing the expected net reward of each secondary user in each time slot. Finally,extensive simulation results are shown to demonstrate the effectiveness of the proposed dynamic control approaches of spectrum sensing.     

Location based spectrum sensing performance analysis over fading channels in cognitive radio networks

This paper analyzes the spectrum sensing performance over fading channel,in which a licensee and multiple unlicensed users coexist and operate in the licensed channel in a local area. The overall average probabilities of detection and false alarm by jointly taking the fading and the locations of all secondary users into account are derived,and a statistical model of cumulate interference is constructed. Based on the cumulate interference,a closed-form expression of outage probability at the primary user's receiver according to a specific distribution of the fading is obtained. Finally,the sensing parameters so as to minimize the total spectrum sensing error and maximize the average opportunistic throughput are obtained. It is noted that the overall average performance analysis and results here enable to benchmark the design of specific spectrum sensing algorithms.     

Optimal multi-threshold quantization scheme for bioinformatics inspired cooperative spectrum sensing in cognitive radio networks

Hard decision combination provides bandwidth efficiency but the results produced are unreliable while soft decision combination has better results but at the expense of much consumption of bandwidth. An acceptable trade-off is achieved between the two in case of quantized decision combination. In this paper an optimal quantization scheme is proposed in which the local sensing information is quantized so the maximum detection probability is met while the false alarm probability remains under a certain constraint. The proposed optimal scheme works on the basis of energy detection and the local quantization thresholds are found through iterative search. Smith–Waterman algorithm (SWA) is used to compare the local sensing reports of the CR users and similarity indexes are found for the CR users. The local sensing decisions of the CR users below a certain calculated threshold are rejected and are not included in the final decision combination at the FC. For detailed analysis, SWA-based rules of decision combination with optimal quantization thresholds are compared with a scheme that employs SWA-based rules of decision combination with heuristically selected quantization thresholds and a conventional majority combination scheme. Simulation results show that the proposed scheme performs better than the other two schemes.     

Detection performance of cooperative spectrum sensing with hard decision fusion in fading channels

In this paper, we investigate the detection performance of cooperative spectrum sensing (CSS) using energy detector in several fading scenarios. The fading environments comprise relatively less-studied Hoyt and Weibull channels in addition to the conventional Rayleigh, Rician, Nakagami-m and log-normal shadowing channels. We have presented an analytical framework for evaluating different probabilities related to spectrum sensing, i.e. missed detection, false alarm and total error due to both of them, for all the fading/shadowing models mentioned. The major theoretical contribution is, however, the derivation of closed-form expressions for probability of detection. Based on our developed framework, we present performance results of CSS under various hard decision fusion strategies such as OR rule, AND rule and Majority rule. Effects of sensing channel signal-to-noise ratio, detection threshold, fusion rules, number of cooperating cognitive radios (CRs) and fading/shadowing parameters on the sensing performance have been illustrated. The performance improvement achieved with CSS over a single CR-based sensing is depicted in terms of total error probability. Further, an optimal threshold that minimises total error probability has been indicated for all the fading/shadowing channels.     

Power allocation in cognitive radio networks with cooperative spectrum sensing

This paper studies power allocation among cooperative nodes (CNs) and secondary user (SU) under the assumption that only mean channel gains are available. We aim to find the power allocation that maximizes the SU average throughput under the constraints of the total power and individual transmission power for CN. We also consider the requirement on cooperative spectrum sensing with target miss-detection probability. Due to the high computational complexity of the optimal solution, we derive a near-optimal solution with low complexity while satisfying the requirements on transmission power and miss-detection probability. Moreover, the closed-form expression of approximation of power ratio is presented. Finally, numerical results verify our analysis and show that the proposed scheme achieves significant performance gain over others, and closes to the optimal solution.     

Cyclo-energy detector for spectrum sensing in cognitive radio

In this paper, a cyclo-energy detector is proposed for the spectrum sensing problem based on the cyclostationary signal analysis. The proposed detector can determine the existence of primary user by estimating the primary user's received power according to the cyclostationarity features of the secondary user. By using this detector, the secondary user does not need to stop transmitting signals when sensing the frequency spectrum. Simulation results are presented to confirm the performance of the proposed detector.     

SNR wall and cooperative spectrum sensing in cognitive radio under noise uncertainty

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in Cognitive Radio (CR). However, its performance may suffer from the noise uncertainty, which is portrayed by the SNR wall in some literatures. In this paper we analyze the spectrum sensing performance under noise uncertainty and find an alternative approach to obtain the SNR wall. Then the average SNR wall is proposed to illustrate the statistically average impact of noise uncertainty. In addition, the cooperative sensing performance under noise uncertainty with AND rule is discussed. Analyses and numerical results show that cooperative sensing can significantly improve the sensing performance under the condition of noise uncertainty.