Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

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.     

一种动态时变衰落信道下的频谱感知算法

针对时变慢衰落信道中频谱感知问题,提出一种新颖的动态状态空间系统模型,将授权用户状态与时变衰落信道状态看作2个隐藏系统状态;在此基础上,提出一种联合估计时变信道增益与授权用户状态的新型频谱感知方法。仿真结果表明,提出的新方案能够显著提高动态时变衰落信道中的频谱感知性能。     

基于授权用户状态迁移统计特性的频谱感知算法

通过动态监测各个频段使用状况并机会性地接入空闲频谱,认知无线电技术可显著提高已分配频段的频谱利用效率,继而有效地缓解频谱资源日趋枯竭的现状。文章首先采用一类具有记忆特性的状态迁移模型来刻画授权用户行为;综合考虑漏检概率与虚警概率的影响,建立了频谱检测的代价函数;在此基础上,采用最大后验概率准则实现检测算法,并对理论算法进行修正,使其满足实际场景下低复杂度、低检测时延要求。借助于有限状态机模型所隐含的编码增益,该算法能显著提高检测性能,数值仿真也进一步验证了算法有效性。     

Available and Waiting Times for Cognitive Radios

Cognitive radios (CRs) have been recently proposed for the problem of spectrum scarcity. The principle of CRs?? operation is based on the opportunistic access to the frequency spectrum mainly dedicated to primary users (PUs). The statistical time pattern of PUs?? channel usage and arrival can affect the usability of specific frequency bands for CRs. In this note, the effect of the arrival rate and channel holding time of PUs on the available times for CRs is analyzed. To this end, first, based on Poissonian arrivals, the available time for CRs is calculated. Then, assuming a gamma distribution for the inter-arrival times and a uniform distribution of channel holding time of PU in these intervals, the probability density function and moments of the available time for CRs are derived. Next, the effect of PUs statistical parameters on the average number of packets and the average symbol rate that a CR can transmit is analyzed. Also, taking that CR needs at least T seconds, the average waiting time is calculated.     

Channel assignment schemes for cooperative spectrum sensing in multi‐channel cognitive radio networks

In this paper, channel assignment for spectrum sensing is studied in multi‐channel cognitive radio (CR) networks to maximize the number of channels satisfying sensing performance (called available channels). Beginning with a nonlinear integer programming problem, we derive the upper bound of optimal value through many‐to‐many assignment problem and then propose three algorithms for both centralized and distributed scenarios. In centralized case, a heuristic scheme is proposed based on the signal‐to‐noise ratios (SNRs) over all primary channels (PCs). Then, a greedy scheme is proposed to reduce the reported information from the CRs. In distributed case, a novel scheme with multi‐round operation is designed following the coalitional game theory. In each round, each CR selects some PCs based on SNRs. Then, the CRs selecting the same channel play coalitional game, and thereby, multiple games are played concurrently over multiple channels. Finally, the best coalition for each channel is chosen among the formed coalitions to perform the cooperative spectrum sensing. The simulation results show that the proposed schemes can significantly increase the number of available channels. Copyright © 2013 John Wiley & Sons, Ltd.     

The effects of channel knowledge on cooperative spectrum sensing in Nakagami-n/q fading channels

Wireless Networks - Cooperative spectrum sensing (CSS) is an efficient method to detect vacant spectrum of a primary user (PU) by combining sensing information of multiple cognitive radios (CRs) in...     

Distributed Cooperative Wideband Spectrum Sensing Algorithm Based on Subspace Methods

We present a novel distributed cooperative spectrum sensing algorithm from compressive sampling in wideband cognitive radio (CR) networks. Each CR utilizes compressive sampling to reduce data acquisition costs. A subspace method is then adopted to directly detect occupied channels without reconstructing the sparse spectrum. To obtain the spatial diversity gain, global signal subspace is estimated by the distributed projection approximation subspace tracking (DPAST) algorithm in which the CRs exchange information locally and cooperate without the need for a fusion center. Then, the orthogonality property of the signal subspace and noise subspace can be exploited to find spectral support to complete the spectrum sensing. We study the convergence behavior of the DPAST algorithm and evaluate the performance of spectrum sensing. Simulation results indicate that the DPAST can effectively estimate the global signal subspace, and the proposed compressed wideband spectrum sensing scheme performs better than spectrum sensing at a single CR.     

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.     

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.     

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.     

A reliable cooperative spectrum detection scheme in cognitive radio networks

Reliable spectrum detection of the primary user (PU) performs an important role in the cognitive radio network since it’s the foundation of other operations. Spectrum sensing and cognitive signal recognition are two key tasks in the development of cognitive radio (CR) technology in both commercial and military applications. However, when the CR terminals receiving signals have little knowledge about the channel or signal types, these two tasks will become much more difficult. In this paper, we propose a reliable cooperative spectrum detection scheme, which combines the cooperative spectrum sensing with distributed cognitive signal recognition. A novel improved cooperative sensing algorithm is achieved by using a credibility weight factor and the “tug-of-war” rule, which is based on the double threshold detection and Dempster–Shafer theory, to determine whether the PU signals exist. In this scheme, cognitive signal recognition can be used to identify the signal type when the PU signal is present. During the cognitive signal recognition processing, the CR terminals make local classification of the received signals by using Daubechies5 wavelet transform and Fractional Fourier Transform, and send their recognition results to the globe decision making center. A distributed processing uses these cognitive terminals’ local results to make final decisions under the Maximum Likelihood estimation algorithm. Simulation results show that the proposed method can achieve good sensing probability and recognition accuracy under the Additive White Gaussian Noise channel.     

An optimal cooperative spectrum sensing strategy with exponential primary link traffic

In this paper, we investigate the optimal sensing settings for a cognitive radio (CR) network consisting a number of CR users and a fusion center (FC). Our objective is to maximize the channel utilization under the constraint that the signals from the primary user (PU) are sufficiently protected. We focus on the utilization of the channel in which PUs dynamically enter the network with burst nature. Thus, we apply the average error probability (AEP) as the metric of channel utilization. Moreover, in order to protect the PU signal from being interfered, the missing detection probability is applied as the constraint function. Assuming that counting rules are utilized in the FC, we derive the false alarm probability, the missing detection probability, and the AEP in the maximum a posteriori (MAP) fashion. Then, after proving the monotonic properties of the objective function and the constraint function, we propose an efficient algorithm named Algorithm I that can derive the optimal settings for maximizing the channel utilization. Moreover, a simplified algorithm named Algorithm II is also proposed to minimize the AEP, supposing that perfect synchronization exists between the CR users and the PU. Finally, we show our numerical results and compare our optimal results with those found by exhaustive searches. We conclude that our Algorithm I produces optimal results very close to those found by exhaustive searches. Performance comparison between Algorithms I and II is also provided in terms of the AEP and the probability of missing detection. Copyright © 2012 John Wiley & Sons, Ltd.     

An adaptive handoff strategy for cognitive radio networks

Spectrum handoff plays an important role in spectrum management as it is the process of seamlessly shifting the on-going transmission of a secondary user (SU) to a free channel without degrading the quality of service. In this paper, we develop an adaptive handoff algorithm that allows an SU to detect the arrival of a primary user (via sensing) and adapt to a reactive or a proactive handoff strategy accordingly. The adaptive handoff scheme first allows an SU to decide whether to stay and wait on current channel or to perform handoff. Then, in case of handoff, an SU intelligently shifts between proactive or reactive handoff modes based on primary use (PU) arrival rate. Further, a PU prioritized Markov approach is presented in order to model the interactions between PUs and SUs for smooth channel access. Numerical results show that the proposed handoff scheme minimizes the blocking probability, number of handoffs, handoff delay and data delivery time while maintaining channel utilization and system throughput at maximal level compared to simple reactive and proactive schemes.     

A Distance Based Reliable Cooperative Spectrum Sensing Algorithm in Cognitive Radio

Spectrum sensing is the most critical task in cognitive radio (CR) which needs to be performed very precisely in order to efficiently utilize the underutilized spectrum and to provide sufficient protection to the primary users (PUs). To improve the sensing performance under fading, shadowing and hidden terminal problems more than one CR users collaboratively perform the spectrum sensing called as cooperative spectrum sensing (CSS). In conventional CSS the decision of each CR is fused at fusion center with equal weights. But due to variable distance of each CR from the PU all decisions are not equally reliable and therefore should be assigned different weights according to their reliability. In this paper we propose a new weighting scheme for CSS under Rayleigh faded channel. In proposed weighting scheme, based on the distance of each CR from the PU reliability of CR nodes is determined and correspondingly appropriate weights are assigned to different users. The CSS algorithm using new weighting scheme gives better performance than conventional CSS algorithm.     

认知无线电网络中次用户平均吞吐量的优化

协作频谱感知的认知无线电网络中,已有研究表明增加参与协作频谱感知的次用户数量能够提高感知性能,进而提高信道吞吐量。然而,由于信道容量的限制,不断增加参与协作感知的次用户数量并不会使信道吞吐量无限提高,反而会使次用户平均可获得的吞吐量不断降低。针对上述问题,该文以次用户平均吞吐量为优化目标,证明多信道条件下,对于任意给定的融合参数,次用户的平均吞吐量是感知时间的凸函数,并提出交叉迭代算法进行2维优化。仿真结果表明,当信噪比为-10 dB时,次用户使用交叉迭代算法获得的平均吞吐量较已有算法可提高20%以上。     

Channel assignment scheme in clustered multichannel cognitive radio networks with outdated CSI over Rayleigh fading channels

This work investigates channel assignment for cooperative spectrum sensing in multichannel cognitive radio networks, where the heterogeneity of primary user (PU) activity and the effect of varying channel condition on the received signal‐to‐noise ratio during cluster formation are considered. With the objective to minimize interference to the PU while enhancing multiple spectrum utilization of the secondary user (SU), an overlapping cluster‐based assignment is formulated into a nonlinear integer optimization problem. To obtain an efficient solution, the nonlinear integer problem is transformed into a mixed integer linear problem, based on which, this paper proposes an exact solution and then two new heuristic algorithms for suboptimal solutions, respectively. Furthermore, a comparative study of four different cluster head selection schemes with respect to their performance in cooperative spectrum sensing, under cluster's heterogeneity in terms of SUs distribution relative to PU transmitter location is presented. Based on the study, a robust cluster head selection scheme is proposed. Simulation results show that good sensing performance and increased opportunistic spectrum utilization in multichannel cognitive radio networks are two sides of a coin that depend on the ratio of the SUs to the number of PU channels. How far away the PU is from the cluster center is also seen to be key in the optimal selection of cluster heads in cooperative spectrum sensing.     

大规模MIMO-OFDM系统结构化压缩感知信道估计中导频优化方法研究

对于FDD模式的大规模MIMO-OFDM系统,本文研究了将结构化压缩感知理论用于该系统的稀疏信道估计。考虑在该系统中将每个发送天线上的导频重叠放置,即每个发送天线可以在相同的时频资源块上发送导频符号,那么此时的系统稀疏信道估计问题可以建模为结构化压缩感知重建问题。为了优化导频位置和导频符号来改进稀疏信道估计的质量,提出了一种最小化完全块间相关值的导频优化准则以及基于此准则的导频搜索算法,完全块间相关值是结构化压缩感知框架下衡量恢复矩阵子块间相关程度的量值。仿真结果表明,与其他导频相比,使用此优化方法获得的导频可以使信道估计误差明显减小,其性能增益大约为2~5 dB。另外,仿真结果还表明,在相同的导频数量前提下,使用优化导频获得的性能增益会随着发送天线数量的增加而变得更加明显。      

主用户干扰约束下的机会频谱接入感知−传输时隙优化调度

提出一种基于主用户干扰约束的机会频谱接入感知-传输时隙调度优化方案。首先,推导切换机制下认知系统的吞吐量和主用户干扰率,建立感知时间和感知周期联合优化模型;然后,在主用户干扰率和次用户感知质量双重约束下,推导了可最大化认知系统吞吐量的最优感知时间和感知周期的闭合表达式;最后,阐述了时隙优化调度方案并计算了认知系统可获得的最大吞吐量。仿真结果表明,所提出的时隙调度方案可以为认知系统提供更高的吞吐量,并更好地适应主用户干扰率和感知质量约束的变化。     

Cooperative Spectrum Prediction in Multi-PU Multi-SU Cognitive Radio Networks

Spectrum sensing is considered as the cornerstone of cognitive radio networks (CRNs). However, sensing the wide-band spectrum results in delays and resource wasting. Spectrum prediction, also known as channel status prediction, has been proposed as a promising approach to overcome these shortcomings. Prediction of the channel occupancy, when feasible, provides adequate means for an SU to determine, with a high probability, when to evacuate a channel it currently occupies in anticipation of the PU’s return. Spectrum prediction has great potential to reduce interference with PU activities and significantly enhance spectral efficiency. In this paper, we propose a novel, coalitional game theory based approach to investigate cooperative spectrum prediction in multi-PU multi-SU CRNs. In this approach, cooperative groups, also referred to as coalitions, are formed through a proposed coalition formation algorithm. The novelty of this work, in comparison to existing cooperative sensing approaches, stems from its focus on the more challenging case of multi-PU CRNs and the use of an efficient coalition formation algorithm, centered on the concept of core, to ensure stability. Theoretical analysis is conducted on the upper bound of the coalition size and the stability of the formed coalition structure. A through simulation study is performed to assess the effectiveness of the proposed approach. The simulation results indicate that cooperative spectrum prediction leads to more accurate prediction decisions, in comparison with local spectrum prediction individually performed by SUs. To the best of our knowledge, this work is the first to use coalitional game theory to study cooperative spectrum prediction in CRNs, involving multiple PUs.