最优中继选择的子载波选择算法性能分析

将协作分集技术与正交频分复用(OFDM)技术相结合的协作通信系统,研究了一种OFDM协作通信最优中继选择算法和在此基础上与最优中继选择算法结合后子载波选择算法,并对它的性能进行详细分析.同时利用仿真分析了中继转发子载波信道容量和信噪比关系的协作通信性能,以及最优中继选择算法和基于最优中继选择算法的子载波选择算法的误码率.仿真结果显示,基于协作通信系统误码率性能得到了更大的提高.可见,协作分集技术与OFDM技术结合的协作通信系统大大提高了无线通信系统的性能,降低了误码率,增强了无线通信的鲁棒性.     

基于中断概率的协作通信中继选择与功率分配算法

研究了功率受限情况下多中继协作通信网络的中继选择和功率优化问题。在AF网络中,提出了一种低复杂度中继选择与功率分配算法,其目标是在总功率一定的条件下使系统的中断概率最小。本算法对源节点和所有潜在中继节点进行功率分配,结合当前信噪比选择最优的中继集合,通过最速下降法求出使系统中断概率最低的功率分配因子。该算法不需要知道大量瞬时信道信息、不需要系统在等功率条件下进行中继选择,只需求得中继节点排列矩阵便可根据当前信噪比自适应获得最优中继节点集合。仿真结果表明,在相同条件下,该算法明显优于不同中继节点集合下几种算法的中断性能,并且与传统的SAF及AAF算法相比,有效降低了中断概率,提升了系统性能和功率效率。     

中继增强的无线蜂窝多小区系统的联合调度与功率控制算法

针对采用全局频率复用的中继增强的无线蜂窝多小区系统,该文考虑多种通信模式并存的混合场景,提出了一种干扰感知的联合资源分配策略。以最大化系统总吞吐量为目标,同时考虑小区间干扰对中继节点与移动站点的影响,以及基站与中继节点各自的发射功率约束。为了降低计算复杂度,针对用户与中继节点配对问题提出了一种基于小区间干扰的调度算法;针对功率控制问题分别提出了一种基于符号规划的最优功率分配算法和一种次优的最小能耗功率分配算法。仿真结果表明,该文所提算法逼近最优资源分配,在系统吞吐量与能量效率等性能方面具有显著优势。     

基于信道统计特性的中继选择算法

该文提出了一种在非再生协作网络中,基于信道统计特性的最优中继选择方法。首先在等功率条件下,根据信道统计特性,定义一个等效信道增益的参数,该参数反映了中继节点在协作过程中两个阶段的信道特性。然后提出一种基于该参数的降序排列的中继选择方法。该方法在不同的信噪比范围内,选择不同的节点集合,使得系统的吞吐率中断概率最小。分析表明该选择方法的分集增益阶数能达到N+1,N为中继节点数目。仿真结果表明这种中继选择算法的中断概率性能优于其他算法。该方法进一步与功率分配相结合,构成了一种低复杂度的次优的中继选择方法。仿真结果表明这种次优算法能够取得和穷举算法相似的性能。     

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。     

基于认知的协作系统中继分配算法

随着无线移动通信系统的飞速发展,无线通信网络能耗急剧增加,基于中继协作技术的绿色无线通信研究受到众多研究者的关注.针对基于认知的中继协作系统,提出了一种以最大主系统能效为目标的中继分配算法.该算法在不影响主系统性能基础上,对主系统请求次系统用户作为中继转发数据,且共享主用户频谱进行了简要介绍.算法中次系统通过最大权重匹配方法为主系统分配中继（次用户）,在满足主系统能效最大化的同时,实现了次系统与主系统的频谱共享.对算法进行仿真验证,提出的算法能获得较高的主系统能效,同时提高了整个系统的频谱利用率.     

D2D通信中基于社交门限的最优中继选择方案

在基于设备直传(D2D)通信的中继系统中,提出了一种基于社交感知的增强型中继选择策略.该策略首先在D2D中继网络中引入社交门限值,对潜在中继用户进行筛选和过滤,从而有效降低了探测成本;然后利用最优停止理论实现了最优中继节点的选择.仿真结果表明,与已有中继选择策略相比,所提出的策略能够以较少的中继探测次数获得较高的系统性能收益,从而实现能耗与收益之间的折中.     

改进蛙跳算法的多中继协作系统最优功率分配

协作通信与直接通信相比能够显著地提高系统性能,功率分配是协作通信中的一个关键问题。为了获得合理的协作中继通信系统功率分配方案,提出一种基于改进蛙跳算法的多中继节点功率分配方法。首先对功率分配问题进行分析,将其转换为一个非线性优化问题,然后将青蛙表示为源节点,中继节点的功率,以平均信噪比作为青蛙的食物,并通过青蛙的信息交流和协作找到最优的功率分配方案,最后采用仿真对比实验对本文算法性能进行测试。仿真结果表明,相对于其它功率分配方法,改进蛙跳算法有效地提高了系统的信道容量,降低了中断概率,以较低的复杂度提高了系统的性能。     

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。     

Greedy Algorithm Applied to Relay Selection for Cooperative Communication Systems in Amplify-and-Forward Mode

Using a relaying system to provide spatial diversity and improve the system performance is a tendency in the wireless cooperative communications. Amplify-and-forward (AF) mode with a low complexity is easy to be implemented. Under the consideration of cooperative communication systems, the scenario includes one information source, M relay stations and N destinations. This work proposes a relay selection algorithm in the Raleigh fading channel. Based on the exhaustive search method, easily to realize, the optimal selection scheme can be found with a highly complicated calculation. In order to reduce the computational complexity, an approximate optimal solution with a greedy algorithm applied for the relay station selection is proposed. With different situations of the communication systems, the performance evaluation obtained by both the proposed algorithm and the exhaustive search algorithm are given for comparison. It shows the proposed algorithm could provide a solution approach to the optimal one.     

Optimal cooperative strategy based on quantum bat for cognitive radio of energy harvesting

In order to reduce energy consumption and improve spectral efficiency of the cognitive relay wireless communication system in 5G network,an optimal cooperative transmission strategy of information and energy was designed for cognitive relay radio with wireless energy harvesting.For the proposed optimal cooperative strategy,the maximal throughput formula and outage probability of secondary user were deduced.In order to resolve the derived maximum throughput equation,a quantum bat algorithm which was based on the optimization mechanism of quantum computing and bat algorithm was designed to solve the deduced equation,and the optimal cooperative transmission scheme for information and energy could be obtained.Simulation results show that the proposed optimal cooperative strategy not only can meet the information transfer demand of primary user,but also can realize the energy self-supply of the secondary user system and improve the communication quality of the secondary user.The proposed optimal cooperative strategy has a better performance than the cooperative strategy of existing cognitive relay radio for different simulation scenarios.     

Joint resource allocation,routing and CAC for uplink OFDMA networks with cooperative relaying

In this paper, we propose a joint resource allocation, routing, and connection admission control (CAC) scheme for uplink transmission in orthogonal frequency division multiple access (OFDMA) relay networks with cooperative relaying. For cooperative relaying, relay station can relay uplink data from mobile station (MS) to base station with cooperation of the MS using transmit diversity. Transmit diversity can be achieved by virtual MISO via distributed space–time coding. The proposed scheme jointly allocates OFDMA resources and selects path for each user with CAC to maximize the upink throughput of cooperative OFDMA relay networks. The basic OFDMA resource unit is considered as a resource element which is one subcarrier over one OFDMA symbol. An efficient multi-choice multi-dimensional knapsack (MMKP) algorithm is presented for the proposed scheme. The proposed MMKP algorithm provides a unified framework which is applicable to OFDMA networks with and without cooperative relaying. We evaluate the performance of the proposed scheme with and without cooperative relaying in a hilly terrain with heavy tree density by using OPNET-based simulation. We show that the cooperative relaying improve the uplink system throughput compared with non-cooperative relaying, and the proposed scheme outperforms the conventional link quality-based scheme in both cooperative and non-cooperative relay networks.     

Nelder‐Mead–based power optimization for secrecy enhancement in amplify‐and‐forward cooperative relay networks

Cooperative communication based on relaying nodes has been considered as a promising technique to increase the physical layer security (PLS) performance in wireless communications. In this paper, an optimal power allocation (OPA) scheme based on Nelder‐Mead (NM) algorithm is proposed for improving the secrecy rate of amplify‐and‐forward (AF) cooperative relay networks employing cooperative jamming (CJ) scheme. The proposed hybrid jamming scheme allows the source and selected relay to transmit the jamming signal along with the information to confound the eavesdropper. The path selection probability of ant colony optimization (ACO) algorithm is used for selecting the relay for transmission. The performance based on secrecy rate is evaluated for “n” trusted relays distributed dispersedly between the source and destination. Gradient‐based optimization and three‐dimensional exhaustive search methods are used as benchmark schemes for comparison of the proposed power optimization algorithm. The secrecy performance is also compared with conventional AF scheme and CJ scheme without power optimization (EPA). The impact of single and multiple relays on secrecy performance is also evaluated. Numerical results reveal that, compared with the gradient method and exhaustive search algorithm, the proposed power allocation strategy achieves optimal performance. Also, the derived OPA results show a significantly higher secrecy rate than the EPA strategy for both CJ and AF schemes.     

采用最优放大因子的全双工中继选择方案

在多中继协作通信系统中,提出一种基于放大转发协议的全双工中继选择算法并进行了相应的理论分析。由于全双工中继中自干扰的存在,为保证通信的质量,首先利用传统的最大化边界信干噪比算法选择一个中继,然后利用中继的最优功率放大因子来减小自干扰对系统的不利影响。基于最优放大因子的全双工中继选择方案在系统中断概率、中继节点功率消耗、目的节点接收信干噪比方面都优于采用最大化边界信干噪比的系统。最后,我们利用蒙特卡洛仿真结果证明了该选择算法的优势。      

Cooperative communications with relay selection for wireless networks: design issues and applications

Relay selection schemes for cooperative communications to achieve full cooperative diversity gains while maintaining spectral and energy efficiency have been extensively studied in a recent research. These schemes select only the best relay from multiple relaying candidates to cooperate with a communication link. In the present paper, we reviewed recently proposed cooperative communication protocols that integrate with relay selection mechanisms. The key design issues for relay selection mechanisms, for example, relaying candidate selection, optimal relay assignment, and cooperative transmission, were identified. We further discussed the challenges of optimal relay assignment in multi‐hop wireless sensor networks and presented the potential applications of cooperative communications with a relay selection in such networks. Future research directions were outlined, for example, the issues of service differentiation and system fairness in cooperative communication systems and the joint use of game theory and adaptive learning techniques in relaying candidate selection and optimal‐relay assignment mechanisms for efficient allocation of network resources. Copyright © 2011 John Wiley & Sons, Ltd.     

认知无线电中一种感知节点集自适应选择算法

本文主要考虑认知网络中感知节点集的选择问题。联合谱感知技术虽然可以极大地提高认知系统的感知性能,但是随着参与感知的认知节点数目的增加,对系统资源的占用也会越来越多,使系统的传输效率下降。本文首先给出了认知网络中最优感知节点集的概念,接着分析了最优感知节点集的节点数目和平均接收信噪比所必须满足的条件,最后通过推导得到了在固定虚警概率条件下最优感知节点集的检测概率与它的节点数目和平均接收信噪比之间的关系表达式,并在此基础上提出了一种最优感知节点集的自适应选择算法。该算法不但能在认知网络中寻找最优感知节点集,同时还可以适应认知网络的动态拓扑变化。仿真结果证明了该算法的有效性。      

Relay Selection Algorithm with Simplified Precoding for MIMO Multiple Relay Channels

Considering an Amplify-and-Forward (AF) cooperative network with the help of multiple relay nodes, a relay selection algorithm with simplified precoder is proposed for the two-hop relay channels. This new algorithm based on the approximate received signal-noise rate (SNR), which chooses only one relay with the maximal received SNR gain to assist in transmission, can significantly reduce the required system consumption, achieve excellent bit-error-rate (BER) and average throughput, and maintain full diversity order. Simulation results demonstrate that the performance of the proposed scheme with a low complexity approaches to the optimal iteration method. And for practical situation with distance attenuation factor, the performance gain of our scheme is also in evident.     

Equation Chapter 1 Section 1基于中继的协作频谱感知性能分析及优化

提出了一种基于目标的中继协作频谱感知方案,证明了SU到SR链路上的信道条件对系统性能有较大的影响;鉴于此,提出了一种优化的最佳中继协作频谱感知(optimized BRCSS)方案,通过联合考虑目标SU到SR链路上的信道条件和 SR 到 FC 链路上的信道条件选择最佳认知中继;最后,从更实际的应用场景考虑,为了节约系统开销,进一步提出了一种自适应的最佳中继协作频谱感知方案（A-BRCSS）,即 SU 根据其信道条件,自适应地选择是否需要认知中继的协作传输。分析和仿真结果均表明,相比传统最佳中继协作频谱感知方案, Optimized BRCSS方案可以实现更高的感知性能;所提A-BRCSS方案可以实现几乎最佳的感知性能。     

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。