Overhead-Throughput Tradeoff Under a Novel Frame Structure in Centralized Cooperative Cognitive Networks

Cooperative spectrum sensing plays an important role in cognitive radio networks since it improves the detection performance by exploiting spatial diversity. However, the cooperation among terminals also brings additional communication overhead. In this paper, overhead-throughput tradeoff issues are investigated in four scenarios namely (1) identical sensing channel and perfect reporting channel, (2) identical sensing channel and imperfect reporting channel, (3) different sensing channel and perfect reporting channel, (4) different sensing channel and imperfect reporting channel of each secondary user (SU). Taking the reporting overhead into consideration, a novel frame structure consisting of an initial subframe and M consecutive subframes, is proposed to maximize the achievable throughput of the secondary network. And for each scenario, the overhead-throughput tradeoff is formulated as an optimization problem with respect to the number of reporting SUs. A brute-force approach is then used to resolve such optimization problem. Given the optimal number of reporting SUs, a set of candidate SUs is then selected according to the probability of detection, the probability of false alarm and the probability of reporting error. Numerical results show that an optimal overhead-throughput tradeoff is achieved given the optimal number of reporting SUs. In addition, the probability of false alarm is shown to be the most important factor affecting the performance of achievable throughput within the secondary network because the lower probability of false alarm corresponds to the case that the secondary network can use the channel with a higher chance.     

Sensing throughput trade‐off for an energy efficient cognitive radio network under faded sensing and reporting channel

The trade‐off between sensing time and throughput is investigated in the context of an energy‐efficient cognitive radio network considering both the sensing and reporting channels are Rayleigh faded, while the existing literature considered the fading in sensing channel only. In this paper, such a trade‐off is re‐examined under Rayleigh faded sensing as well as reporting channel. Novel analytical expressions for overall detection probability and false alarm probability are developed under such scenario. The performance is investigated in terms of detection probability, false alarm probability, throughput and energy efficiency of the network for different sensing parameters such as sensing time, number of samples, sensing channel signal‐to‐noise ratio and reporting channel signal‐to‐noise ratio. Our analysis shows that the quality of the reporting channel significantly affects the trade‐off performance of the network. Copyright © 2015 John Wiley & Sons, Ltd.     

衰落信道下的协作频谱检测及其性能分析

在低信噪比和复杂性环境下,协作频谱检测是准确实现频谱感知的有效手段。文中分析了基于能量检测的单用户频谱检测算法以及基于硬判决和等权重的多用户协作频谱检测技术,导出了在高斯信道、Rayleigh衰落信道和Nakagami-m衰落信道情况下协作频谱检测虚警概率和漏检概率的闭合解析式,并对此进行了仿真验证和比较。结果表明,等权重协作频谱检测算法能够有效克服衰落信道对频谱检测的影响。     

Hard and softened combination for cooperative spectrum sensing over imperfect channels in cognitive radio networks

Recently, cognitive radio (CR) access has received much attention to overcome spectrum scarcity problem. Spectrum sensing methods are often used for finding free channels to be used by CR. In this paper, the problem of cooperative spectrum sensing will be investigated in CR networks over realistic channels. This problem is not clarified until now by taking into account the error effect on the decision reporting. The analytical expressions of the hard and softened one bit and two bits hard combination scheme for cooperative spectrum sensing will be derived. These expressions are investigated to compare with simulation results. The analysis and simulation results show that the performance of cooperative spectrum sensing is limited by the probability of reporting errors. Moreover, it is shown that there is a significant performance loss when a final decision regarding to primary user’s (PU) state made at the fusion depends on a set of local spectrum sensing information that are distorted by imperfect reporting channels during transmission. The probability of detection is degraded due to imperfect reporting channel by 16.5% and 12.2% with one bit hard combination and softened two bits hard combination, respectively. To reduce this performance loss, Amplify and Forward (AAF) relying mechanism will be proposed. The probability of detection is improved by 8% and 9.3% with one bit hard combination and softened two bits hard combination, respectively using AAF relaying mechanism.     

Performance Evaluation of Cooperative Spectrum Sensing Scheme with Censoring of Cognitive Radios in Rayleigh Fading Channel

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radio (CR) users in Rayleigh fading channel is analyzed. More precisely, CR users which employ energy detectors are censored depending on the quality of radio channels between them and a fusion center (FC). Each CR makes a hard decision about primary user (PU) using energy detection and transmits the information to FC using BPSK signaling if that CR user is selected to transmit. A training based channel estimator is used at the FC to estimate the complex Gaussian fading coefficients characterizing the channels between the CR users and the FC. This channel state information on fading coefficients is used for censoring the CR users. Two fusion rules such as majority logic fusion and maximal ratio combining (MRC) fusion rules are applied at the FC for estimating the performance in terms of probability of missed detection (P_m). We develop a simulation test bed for evaluating the performance of CSS scheme. Probability of missed detection has been evaluated for both perfect and imperfect channel estimation for various probabilities of false alarm (P_f), reporting and sensing channel SNR values.     

Robust spectrum sensing under noise uncertainty for spectrum sharing

Spectrum sensing plays an important role in spectrum sharing. Energy detection is generally used because it does not require a priori knowledge of primary user, (PU) signals; however, it is sensitive to noise uncertainty. An order statistics (OS) detector provides inherent protection against nonhomogeneous background signals. However, no analysis has been conducted yet to apply OS detection to spectrum sensing in a wireless channel to solve noise uncertainty. In this paper, we propose a robust spectrum sensing scheme based on generalized order statistics (GOS) and analyze the exact false alarm and detection probabilities under noise uncertainty. From the equation of the exact false alarm probability, the threshold value is calculated to maintain a constant false alarm rate. The detection probability is obtained from the calculated threshold under noise uncertainty. As a fusion rule for cooperative spectrum sensing, we adopt an OR rule, that is, a 1‐out‐of‐N rule, and we call the proposed scheme GOS‐OR. The analytical results show that the GOS‐OR scheme can achieve optimum performance and maintain the desired false alarm rates if the coefficients of the GOS‐OR detector can be correctly selected.     

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.     

Channel estimation algorithms for cooperative spectrum sensing in amplify‐and‐forward cooperative system

In amplify‐and‐forward (AF)‐based cooperative spectrum sensing system, the bit‐error‐rate (BER) performance and detection probability will decrease because of the existence of channel estimation error. In this paper, the influence of channel estimation error on system performance is firstly deduced, and then, linear minimum mean‐square error (LMMSE) channel estimation algorithm with filtering delay time‐domain windowing (LMMSE‐filtering‐DTW) technique and modified singular value decomposition‐based LMMSE algorithm are proposed to improve the channel estimation performance for code division multiple access system and orthogonal frequency division multiplexing system in AF cooperative scenario, respectively. Simulation results verify the effectiveness of the two proposed channel estimation algorithms in cooperative spectrum sensing, and when E_b/ N₀ is bigger than 20 dB, given the required false alarm probability smaller than 15%, the difference of detection probability between the channel obtained using the proposed channel estimation algorithms and the ideal channel is less than 2.5%, respectively. Copyright © 2012 John Wiley & Sons, Ltd.     

Collaborative Spectrum Sensing of Cognitive Radio Networks with Simple and Effective Fusion Scheme

Cognitive radio (CR) provides a mechanism for effective spectrum usage. Spectrum sensing is an essential component of CR which comprises intelligent signal processing algorithms to identify the spectrum holes. In this paper, we propose a novel soft combining scheme, called mean cumulative sum (MCS), at the cognitive base station or Fusion center (FC), and we have investigated our proposed method through closed form expressions of probability of detection and probability of false alarm, respectively. We have also provided a method of obtaining an optimum threshold to minimize the sensing error which occurs in FC. Our simulation results show that proposed MCS combining scheme outperforms single user spectrum sensing and performs equally well as that of equal gain soft combining scheme. In addition, our results show that sensing error is reduced when optimum threshold is chosen at the FC.     

认知无线电中基于感知信息量化的合作频谱感知

针对认知无线电频谱感知性能的提高与传输开销的矛盾,本文提出了一种基于感知信息量化的合作频谱感知方案。该方法对各认知用户的本地检测结果采用3个判决门限进行2比特位的量化,在融合中心处对量化信息加权处理后,得到最终主用户是否存在的判决。本文详细研究了采用该方案的检测概率,虚警概率和吞吐量,理论分析和仿真结果表明,该方法在每个认知用户只增加1bit传输开销的前提下能够极大的改善检测性能,实现了检测性能与传输开销的较好权衡。     

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.     

集中式双非参量累积和的合作频谱感知技术

针对认知无线电网络频谱感知的检测时延降低问题，提出了一种采用双非参量累积和的合作频谱感知方法。在单主用户认知网络中，本地认知用户执行非参量累积和算法，处理能量观测数据，以缩短检测时延，减少对主用户先验信息的需求，同时为了降低带宽开销，只向融合中心传输1比特的预判决结果。融合中心在噪声干扰下接收融合预判决结果，执行非参量累积和算法，累加判决统计量，对主用户信号是否存在进行最终判决。仿真结果表明，在10%的虚警概率下，相比于传统的非参量合作频谱感知算法，双非参量累积和算法具有较低的检测延迟。      

Multi slot-throughput tradeoff in an improved energy detector based faded cognitive radio network

In this paper, the impact of a multi slot based cooperative spectrum sensing (CSS) on the performance of a cognitive radio (CR) network has been investigated. Each CR user, equipped with an improved energy detector (IED), uses a number of mini slots of the sensing time to perform the spectrum sensing. Each CR uses OR logic to combine the sub local decisions generated in each mini slot to obtain a local decision at CR level. Local decisions are sent to fusion centre (FC) over reporting channel. The FC obtains a final decision about the presence of primary user (PU) by combining the local decisions using a fusion rule: Majority or Maximal Ratio Combining. The performance of the CSS is assessed in terms of detection probability and false alarm probability considering both the sensing and reporting channels are Rayleigh faded. Furthermore, the impact of a number of sensing slots and IED parameter on throughput of CR network is also evaluated under the proposed spectrum sensing scenario. Impacts of several sensing parameters such as sensing channel SNR and reporting channel SNR on the performance of CR network are also evaluated. Performances of two fusion rules under study are compared. Effect of sensing error and synchronisation error is indicated. Further the study is extended for independent but non identically distributed (i.n.i.d.) Rayleigh faded channels as well as for a multiple PU scenario also.     

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。     

基于功率谱分段对消频谱感知算法研究及性能分析

在实用的认知无线电系统中,频谱感知技术必须具备在噪声电平高动态变化和无线信道严重衰落电磁背景下,进行实时盲频谱感知的能力,这为经典的频谱感知算法带来巨大的挑战。该文提出的功率谱分段对消频谱感知算法,依据傅里叶变换的渐进正态性和相互独立性,计算出功率谱的统计特性,利用监测频带内部分谱线强度和与全部谱线强度和的比值作为检验统计量进行信号存在性的判断。该文推导了算法的虚警概率和不同信道模型下正确检测概率的数学表达式,并依据Neyman-Pearson准则得到判决门限的闭式表达式。理论分析和仿真结果均表明:功率谱分段对消频谱感知算法对噪声不确定度具有鲁棒性;固定信噪比,算法的频谱感知性能不受噪声电平改变的影响;应用于高斯白噪声和平坦慢衰落信道中,可在较宽的信噪比范围内获得较优越的频谱感知性能;算法计算复杂度低,可在微秒级时长内完成频谱感知。     

Quickest Detection of Multi-channel Based on STFT and Compressed Sensing

This paper proposes a multi-channel quickest detection method based on compressed sensing and short-time Fourier transform. Quickest detection performs a statistical test to obtain the minimal detection delay subject to given false alarm constrains. Short-time Fourier transform, which reflects the time–frequency information, implements the multi-channel quickest detection. Compressed sensing reduces the sampling rate at first. Compared with single-channel spectrum sensing, this method substantially improves the spectrum access opportunity in time and frequency domain. The relationship between the detection delay and other parameters, such as the probability of false alarm, SNR, sparsity, and sampling rate, verifies the validity of the method. While simulation results show that this method can perform spectrum sensing in high detection probability and low probability of false alarm.     

Scheme of Cooperative Spectrum Sensing Based on Adaptive Decision Fusion Algorithm

Spectrum sensing is one of the core technologies for cognitive radios(CR),where reliable detection of the signals of primary users(PUs) is precondition for implementing the CR systems.A cooperative spectrum sensing scheme based on an adaptive decision fusion algorithm for spectrum sensing in CR is proposed in this paper.This scheme can estimate the PU prior probability and the miss detection and false alarm probabilities of various secondary users(SU),and make the local decision with the Chair-Varshney rule so that the decisions fusion can be done for the global decision.Simulation results show that the false alarm and miss detection probabilities resulted from the proposed algorithm are significantly lower than those of the single SU,and the performance of the scheme outperforms that of the cooperative detection by using the conventional decision fusion algorithms.     

Sensing of OFDM Signals in Cognitive Radio Systems with Time Domain Cross‐Correlation

This paper proposes an algorithm to sense orthogonal frequency‐division multiplexing (OFDM) signals in cognitive radio (CR) systems. The basic idea behind this study is when a primary user is occupying a wireless channel, the covariance matrix is non‐diagonal because of the time domain cross‐correlation of the cyclic prefix (CP). In light of this property, a new decision metric that measures the power of the data found on two minor diagonals in the covariance matrix related to the CP is introduced. The impact of synchronization errors on the signal detection is analyzed. Besides this, a likelihood‐ratio test is proposed according to the Neyman–Pearson criterion after deriving probability distribution functions of the decision metric under hypotheses of signal presence and absence. A threshold, subject to the requirement of probability of false alarm, is derived; also the probabilities of detection and false alarm are computed accordingly. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm.     

Cooperative Spectrum Sensing Scheme with Hard Decision Based on Location Information in Cognitive Radio Networks

Without an efficient way to achieve the reliability of the decision, the implementation of weighted data fusion is limited in the hard decision combination for cooperative spectrum sensing. To address this problem, a new cooperative spectrum sensing scheme based on the location information of the primary user (PU) and cognitive radio (CR) is proposed. In the new scheme, depending on the location information, the channel condition between the PU and each CR is obtained at the fusion center (FC), with which the local sensing reliability is first achieved. Then we calculate the transmission reliability between the CR and FC. Based on both the local sensing reliability and the transmission reliability, the combining weighting factor is determined for optimal data fusion. On the basis of this proposed scheme, we study the global sensing false alarm and detection probabilities, derive the expressions to obtain the optimal local sensing threshold, and perform an error analysis that demonstrates the impact of imperfect channel knowledge. Using both analytical and simulation methods, we find that the proposed scheme achieves better performance compared with the conventional logical fusion rules in the hard decision combination for cooperative spectrum sensing.     

基于瑞利多径衰落信道的信号包络频谱感知

为提高信号采样值之间的相关性和降低噪声对感知性能的影响,该文提出基于信号包络自相关矩阵的频谱感知算法。首先对采样信号等间隔时长截取,以相邻间隔的采样值计算信号自相关性,并构造出近似自相关矩阵。其次依据矩阵次对角线元素性质构造了统计量。分别计算了该统计量的检测概率分布函数与虚警概率分布函数,分析了频谱感知算法的检测性能,算法优化了信号相关性的计算,降低了噪声对感知性能的影响。最后通过仿真验证了不同参数对检测概率和虚警概率的影响,并提出了进一步提高检测性能的措施。