分布式MIMO系统小区平均遍历容量分析

针对分布式MIMO系统的圆形小区平均遍历容量展开研究.文章首先建立了包含快衰落、阴影衰落和路径损耗的复合衰落信道模型;然后,对分布式天线采用覆盖式（BT）传输策略,并在高信噪比条件下,导出给定移动台位置时,区上、下行点对点链路遍历容量表达式.最后,考虑移动台在小区内任意分布特点,进一步推导出小区平均遍历容量闭合近似表达式.仿真结果表明,所推导的近似表达式可很好的反应系统的实际性能.导的近似表达式可很好的反应系统的实际性能.     

波束成形下DMIMO系统下行小区平均遍历容量分析

主要对波束成形下分布式MIMO系统下行小区平均遍历容量展开分析。首先建立了包含快衰落、阴影衰落和路径损耗的复合衰落信道模型。然后,在分布式基站功率受限条件下,推导各基站权重向量即最优波束;并基于ST-MRT传输策略,推导特定移动台位置条件下,小区下行点对点遍历容量表达式。最后,考虑移动台在小区内任意分布的特征,进一步推导出波束成形下小区平均遍历容量理论近似表达式。结果表明所推导的理论近似表达式可很好地反应系统的实际性能。     

分布式MIMO系统信道容量分析

首先推导了分布式MIMO点对点链路遍历信道容量的近似表达式或理论下界,然后给出小区平均遍历容量的表达式.在此基础上,研究D-MIMO与C-MIMO系统分别在BT和ST两种天线选择机制下的平均遍历容量.最后通过仿真,证明了所推导理论表达式的正确性,同时比较了两种MIMO系统的信道容量.     

分布式天线系统中的系统下行误符号率分析

首先建立了包含快衰落、阴影衰落和路径损耗的复合衰落信道模型,对分布式天线采用覆盖式（BT）传输策略,推导出给定移动台位置的小区下行点对点链路误符号率表达式.并在高信噪比条件下,通过给出移动台在小区的任意分布图,推导出小区下行平均误符号率的近似闭合表达式.仿真结果表明,所推导的近似表达式可很好地反应系统的实际性能.     

多小区分布式发射天线位置优化

在分布式发射天线的多小区环境下,分析了多层同频干扰对小区平均遍历容量及天线位置的影响,给出了分布式天线位置选择与小区平均遍历容量的关系.数值分析和仿真结果表明外围的第一层同频小区干扰能量决定了分布式天线的最佳位置摆放,在半径1000m的小区中,各天线距离小区中心450m附近时,小区的平均遍历容量达到峰值.     

分布式天线系统中的系统下行误符号率分析

首先建立了包含快衰落、阴影衰落和路径损耗的复合衰落信道模型,对分布式天线采用覆盖式(BT)传输策略,推导出给定移动台位置的小区下行点对点链路误符号率表达式。并在高信噪比条件下,通过给出移动台在小区的任意分布图,推导出小区下行平均误符号率的近似闭合表达式。仿真结果表明,所推导的近似表达式可很好地反应系统的实际性能。     

分布式天线系统中的下行容量分析

针对分布式天线系统(DAS)的下行容量问题展开研究。首先建立了包含路径损耗、阴影衰落和瑞利衰落的复合信道模型;然后,基于该信道模型,分别对各态历经容量和中断容量进行了分析。考虑到小区内移动台的分布特点,在选择分集传输策略下,推导了各态历经容量和中断容量的近似解析表达式。仿真结果表明,所推导的2个近似解析表达式均能准确地评估分布式天线系统的系统性能。     

分布式天线系统MIMO信道容量分析

结合了分布式天线系统和MIMO信道特点的分布式MIMO系统可以改善覆盖特性,提高系统容量。提出了包含路径损耗、快衰落和阴影衰落的两层分集分布式MIMO系统。对MIMO信道容量的分析表明,分布式MIMO系统具有良好的信道容量均匀覆盖特性。与传统集中式天线系统相比,分布式MIMO系统可以获得更好的小区平均信道容量。对下行信道容量的数值分析表明,由于“充水”方式功率分配可以充分利用MIMO信道信息,此时的分布式MIMO系统可以比等功率分配条件下的分布式天线系统多获得0.25bit/(s·Hz)每发送天线的信道容量增量。     

复合衰落信道下分布式MIMO系统下行中断概率分析

针对复合衰落信道模型下分布式MIMO系统下行中断概率问题,首先建立了一个综合考虑Nakagami-m衰落、路径损耗和阴影衰落的复合衰落信道模型;然后针对存在中心基站的分布式MIMO系统,提出了一种更符合实际应用环境的准均匀小区移动台分布模型;接着利用矩生成函数、Gauss-Hermite积分公式和Simpson积分公式等数学手段推导了任意移动台分布下、单小区内系统平均下行中断概率闭合表达式;最后将准均匀移动台分布模型应用到该中断概率闭合表达式,并通过MATLAB仿真证明了所推导得到的闭合表达式及小区分布模型的合理性。     

天线相关性对MIMO系统BER性能的影响分析

推导了一种基于拉普拉斯角能量分布的天线相关性的精确算法表达式与近似表达式,分析了影响MIMO系统天线空间相关性的因素,并将之用于对MIMO系统的BER分析。在均匀线性阵列跟圆形阵列中,对比了不同衰落因子下,系统BER随信噪比、天线之间距离以及信号到达角的变化关系。分析了决定系统BER的因素以及降低系统BER的方法。最后通过对近似算法的研究发现,在衰落因子a值比较大时,近似算法能很好地代替精确算法,并能大大简化计算复杂度。     

System Capacity Analysis and Antenna Placement Optimization for Downlink Transmission in Distributed Antenna Systems

System capacity and antenna placement play crucial roles in wireless communication systems, and they are of great value to network planning. In this paper, we are motivated to analyze the system capacity and optimize the antenna placement in distributed antenna systems. This paper establishes a composite channel model which takes path loss, lognormal shadowing and Rayleigh fading into consideration. To reduce the computational complexity, an approximate theoretical expression of system capacity is derived with selective transmission at the transmitter and maximal ratio combining at the receiver. An antenna placement optimization problem is formulated, and then a genetic algorithm (GA) based searching scheme is proposed to solve the proposed optimization problem. The computational complexity analysis indicates that the proposed GA-based searching scheme is computationally efficient in terms of both running time and storage space. Numerical results show that the approximate theoretical expression of system capacity can provide a very good approximation to the simulation results, and the proposed GA-based searching scheme for solving the antenna placement optimization problem can consistently offer a large capacity gain over other existing schemes.     

Particle swarm optimization–based power allocation for Alamouti amplify and forward relaying protocol

The performance of wireless communication systems is improved over flat fading channel by using Alamouti coding scheme, which provides the quality of diversity gain. In this paper, performance analysis of symbol error rate (SER) and particle swarm optimization (PSO)–based power allocation (PA) for Alamouti amplify and forward (AF) relaying protocol using maximum ratio combining (MRC) technique is presented. Analytical expression of SER upper bound and SER approximation is derived for Alamouti AF relaying protocol with quadrature phase shift keying (QPSK) modulation over Rayleigh fading channel and Rician fading channel. In addition, PSO‐based optimum PA factor is calculated on the basis of the minimum SER of proposed method. PSO‐based optimum PA gives 0.5 dB of improved signal‐to‐noise ratio (SNR) compared with the equal power allocation (EPA). The theoretical approximate SER result is compared with the simulated SER. The proposed protocol provides full diversity gain and reduces SER compared with the existing AF and decode and forward (DF) relaying protocols over Rayleigh fading channel and Rician fading channel.     

Nakagami衰落上DE-QPSK在联合收发分集下的性能分析

利用高斯Q函数的高阶次幂在最大比合并（MRC）分集接收瑞利衰落信道上统计平均的结果,推导了Nakagami 衰落信道上采用组合发射选择合并（SC）/接收 MRC 天线分集的相干检测差分编码四相相移键控（DE-QPSK）的平均误符号率（ASER）精确表达式。利用高斯Q函数的近似表达式和矩生成函数（MGF）方法,推导了Nakagami衰落信道上采用组合SC/MRC天线分集的相干检测DE-QPSK 的ASER近似表达式。通过数值计算和仿真,验证了DE-QPSK的ASER精确表达式的正确性以及近似表达式的准确性。利用精确表达式和近似表达式可研究收发天线数目和衰落参数对DE-QPSK的ASER性能的影响,为实际SC/MRC天线分集方案的设计提供了理论指导。     

Closed-form expressions of approximate error rates for optimum combining with multiple interferers in a Rayleigh fading channel

This paper presents approximate error rates of M-ary phase shift keying (MPSK) for optimum combining (OC) with multiple cochannel interferers in a flat Rayleigh fading channel. For the first-order approximation, we derive the closed-form expression for ordered mean eigenvalues of the interference-plus-noise covariance matrix, which facilitates performance evaluation for the OC with arbitrary numbers of interferers and antenna elements without Monte Carlo simulation and multiple numerical integrals. We also derive the closed-form expressions for approximate error rates of MPSK for the OC in terms of the average error rate of MPSK for maximal ratio combining (MRC). From the simple evaluation of ordered mean eigenvalues, we show that the first-order approximation gives a simple and accurate way to analyze the performance of the OC.     

基于单纯形法的量子粒子群优化算法

针对粒子群优化算法容易陷入局部极值点,进化后期收敛慢和优化精度较差等缺点,提出了将单纯形搜索法与量子粒子群算法混合的改进算法,更好的平衡了全局搜索和局部搜索能力.仿真结果表明,该算法效率高、优化性能好,其性能远远优于一般的粒子群算法与量子粒子群算法.     

一种基于权重优化的σ策略的微粒群优化算法

微粒群算法是一种受鸟类和鱼类群体行为启发而产生的一种智能化计算方法,针对微粒群算法易于陷入局部最优的缺点,对标准PSO算法进行了改进,提出了一种更为简化的PSO算法,即σ-PSO。在σ-PSO中,用相位角的增量代替速度的增量,通过绘制相位角来确定微粒的位置。用这种新的权重优化算法与标准PSO算法对大学生的评价进行仿真的结果进行比较,证明该算法具有一定的优越性。     

Signal Ratio Detection and Approximate Performance Analysis for Ambient Backscatter Communication Systems with Multiple Receiving Antennas

Recently, ambient backscatter attracts much attention since it can utilize ambient radio frequency signals to enable battery-free devices to communicate with others. Most existing studies about ambient backscatter assume that the reader is equipped with one receiving antenna. In practice, the reader can utilize multiple antennas to overcome channel fading. In this paper, we investigate the problem of signal detection for ambient backscatter systems with multiple receiving antennas. Specifically, we formulate a new transmission model where the reader is equipped with at least two antennas and propose a ratio detector that exploits the ratio of the signal strength received at each antenna. It is shown that the closed-form expression of the optimal detection threshold for this detector is difficult to derive. Therefore, we derive a reasonable approximate expression for the optimal detection threshold. Moreover, we obtain the closed-form expression for approximate bit error rate (BER). Furthermore, we propose an antenna selection scheme if the reader is equipped with more than two antennas. The selection scheme is investigated through the BER performance. It is found that the largest gain in BER can be achieved when the antenna number increases from two to three, and that much less gain is obtained from enlarging the antenna number when the reader already has four antennas. Finally, simulation results are provided to corroborate our theoretical studies.     

幅值比约束下稀布阵的旁瓣抑制混合算法

针对非均匀稀布圆环阵的旁瓣抑制问题提出了一种基于粒子群算法和二阶锥规划算法的混合算法。该混合算法结合两种算法的优势,将粒子群算法作为全局搜索器进行阵元位置的优化,二阶锥规划算法作为局部搜索器进行阵元权值的优化,能够获取较低的峰值旁瓣电平。该算法同时引入相邻阵元最小间距的约束,优化了算法的搜索空间,提高了寻优效率。最后,考虑到阵列天线系统的可实现性,给出了动态幅值比约束下的混合算法。与粒子群算法和参考文献方法的对比实验结果表明:本文算法可进一步降低稀布圆环阵的旁瓣电平,仿真数据验证了算法的有效性和天线系统的可实现性。     

基于改进型粒子群算法的阵列天线综合

粒子群优化(PSO)算法是一种通过粒子之间的合作与竞争来实现复杂多维空间的最优区域搜索的优化算法。本文中改进型PSO算法(NPSO),通过增加积分控制项改善了PSO算法全局搜索能力,并将该方法应用于多元环形阵列天线方向图的综合,实现了阵列方向图与预先给定的目标方向图的高度逼近。最后通过数值实例说明这种NPSO方法的有效性。     

基于改进粒子群算法的稀布阵列优化设计

针对稀布线阵的阵元位置优化问题,提出了一种基于改进的自适应粒子群算法的稀布阵综合新方法。该方法首先采用自适应策略,根据粒子的适应度值自适应地调整其惯性权重和学习因子,提高了种群的寻优能力;然后对粒子群算法的速度更新公式进行了修正,保证了速度的有效更新;在算法停滞时,通过引入交叉策略进一步加快了算法的收敛速度。该方法高效地实现了多约束稀布线阵的综合,获得了更低的峰值旁瓣电平,数值仿真验证了算法的有效性。