多输入多输出天线蜂窝系统中的分布式功率控制方法

在蜂窝无线通信系统设计中,基于信号干扰比(SIR)测量的功率控制方法得到广泛的应用。该文提出多输入多输出(MIMO)天线蜂窝系统中的基于SIR测量的分布式功率控制(DPC)方法。该方法通过控制移动台或者基站的发射功率可以达到以下两个目标的其中之一:(1)最小化所有基站或者移动台的平均接收SIR中断概率;(2)在满足目标SIR要求的前提下最小化平均发射功率。数值仿真结果显示,该文提出的DPC方法在低的计算复杂度下,可以达到降低SIR中断概率和减小发射功率的目的。     

分布式残余频偏信道中STBC-OFDM的发射功率优化

在分布式残余频偏信道中,考虑多径瑞利衰落,针对采用判决反馈检测的两发射天线STBC-OFDM链路,提出了一种发射功率优化方法:根据平均信道功率增益、残余频偏方差以及噪声方差的大小,以最小化平均误比特率下界为目标,设置两分布发射天线的发射功率,仿真结果表明:相比于传统的各天线满功率发射方法,所提方法能够在节省发射功率的同...     

多带OFDM-UWB动态子载波分配算法

超宽带系统的传输功率谱密度是严格限制的,发射功率是超宽带系统的主要性能指标之一.为了最小化系统总发射功率,论文在给定用户速率和误比特率限制的前提下提出了一种新的功率最小化的自适应子载波分配算法.该算法采用次优算法,通过基于差值的子载波选择、子载波比特分配和相同比特子载波分配优化三个完整的动态分配,有效避免了衰落严重的子...     

MIMO系统中基于ZF/MMSE检测的 自适应功率分配方案

 本文研究了MIMO系统中的功率分配技术.针对基于ZF/MMSE检测的MIMO系统,提出了一种简单的自适应功率分配方案.该方案在不使用预编码技术对MIMO信道进行对角化的前提下,遵循最小化系统BER的准则,为发送数据流分配发射功率.与采用SVD预编码的功率分配方案相比,本文提出的方法减少了系统需要的反馈信息量.仿真表明该方法能够有效地提高系统的BER性能,而且基于MMSE检测的系统性能接近于采用SVD预编码的功率分配性能.     

cdma2000 1x前向功率分配分析

本文提出了一种在多径传输约束条件及不同的移动台运动速度条件下对前向信道链路进行功率分配的方法,这是根据导频信道和业务信道之间各自信号强度的相关性合理地分配前向链路中的信道发射功率.通过实验测试及理论推导,本文给出了这种相关性曲线,从而发现了最佳的导频信道功率,它能够在满足1%FER时使总发射功率最小.     

MIMO-MC-CDMA中基于拉氏算子的资源分配算法

提出一种应用于多输入多输出MC-CDMA系统的功率、码道自适应分配算法。基于接收端的信道反馈信息,发送端在总发射功率受限的条件下通过多用户间功率和码道的分配最大化系统吞吐量。算法通过限制用户的最大和最小码道数来实现用户之间的带宽公平性。算法最终归结为一个约束优化问题并利用拉格朗日乘子法进行求解。提出一种用于加快拉格朗日乘子收敛速度的搜索算法,计算机仿真验证了算法的有效性。     

分布式残余频偏信道中的Alamouti STBC-OFDM功率分配

在具有不同残余频偏的分布发射天线多径瑞利衰落信道中,该文使用Cholesky判决反馈检测的Alamouti STBC-OFDM链路,提出了一种抑制残余频偏影响的发射功率分配方法:以最小化残余频偏下链路的平均误比特率下界为准则,为发射天线分配功率。首先推导了残余频偏下链路的平均误比特率下界,然后给出了发射天线间最优功率分配因子的闭合解。仿真结果表明,与传统的假设频率理想同步的功率分配方法相比,在残余频偏对性能影响占主导作用的场景中,该文方法提升了链路性能,提升程度随着两根发射天线到接收机间平均信道功率增益之比的增加而增大。     

夹层天线罩壁电性能的多目标遗传优化

提出最小极化差异、最大入射角范围和最大工作频率范围准则,基于这些准则对实际的C-夹层结构的电性能进行了遗传优化,并与基于最大功率透射系数和最小功率反射系数准则的结果进行了比较.所考虑的实际的C-夹层是一种14层结构,其中包括防雨涂层、胶膜、树脂过渡层等.采用页面存储技术建立每一层的材料库从而实现染色体中连续数值变量和离散非数值变量的混合编码.多目标优化通过基于约束条件的单目标优化算法实现.     

IRS和人工噪声辅助的MIMO-SWIPT系统安全传输方案设计

针对多天线无线携能通信系统中能量收集节点作为潜在窃听者的信息安全问题，提出了一种智能反射面(Intelligent Reflecting Surface, IRS)和人工噪声辅助的物理层安全传输方案。首先考虑发射功率、能量收集门限以及IRS单位模约束，以最大化系统安全速率为优化目标，在合法用户直射链路不可用的情况下，联合设计发射端波束赋形矩阵、人工噪声协方差矩阵以及IRS相移矩阵，建模一非线性多变量耦合的非凸优化问题；接着利用均方误差准则等价转换非凸目标函数，并利用连续凸逼近方法(Successive Convex Approximation, SCA)处理非凸的能量收集约束；最后基于交替优化框架，分别用拉格朗日对偶方法和基于价格机制的优化最小化(Majorization-Minimization, MM)算法求解发射端变量和IRS端变量。仿真结果表明，与现有方案相比，所提算法能够在保障能量收集需求的同时大幅度提升系统的安全性能。     

一种采用混合平衡准则的新功率控制算法

功率控制算法按准则可以分为基于功率平衡准则和基于SIR平衡准则两大主流。基于信干比平衡的功率控制算法存在正反馈问题。基于功率平衡和信干比平衡混合准则的功率控制算法可以解决正反馈问题,但复杂度较高,实现比较困难。提出了一种基于功率平衡和信干比平衡混合准则的功率控制算法。本算法在每次迭代中通过测试接收信号功率和接收信干比,只需要一次判决产生下一周期的发射功率,因此具有易于实现的优点。分析和仿真表明本算法是有效的。     

基于AF中继协议下的抗信道偏差波束成形算法

在协作通信中,各节点获得信道状态信息存在偏差会直接导致系统性能的衰减。同时,在保证基本服务质量的前提下,采用优化方法最大限度地节约传输成本,可以延长无线网络寿命。针对上述问题,在放大—转发协议中,采用最坏情况的设计思想,提出了CSI偏差下的双约束波束成形算法。该算法利用凸函数的性质和扩展的S引理将不易求解的半正定问题转化成拟凸优化问题,再利用二分法获得最优解。算法使用重要性采样构建椭圆形收敛域,在保证该收敛域是凸集的条件下,减少了搜索范围。通过仿真证明,该算法在中继总功率和单个中继功率的双重约束条件下,仍然能够通过协作分集提高系统增益,并有效抵抗CSI偏差带来的性能损失。     

Optimal Power Allocation with Limited Feedback of Channel State Information in Multi-User MIMO Systems

In this paper,an expression for the user’s achievable data rate in the multi-user multiple-input multiple-output(MU-MIMO)system with limited feedback(LF)of channel state information(CSI)is derived.The energy efficiency(EE)is optimized through power allocation under quality of service(QoS)constraints.Based on mathematical equivalence and Lagrange multiplier approach,an energy-efficient unequal power allocation(EEUPA)with LF of CSI scheme is proposed.The simulation results show that as the number of transmitting antennas increases,the EE also increases which is promising for the next generation wireless communication networks.Moreover,it can be seen that the QoS requirement has an effect on the EE of the system.Ultimately,the proposed EEUPA with LF of CSI algorithm performs better than the existing energy-efficient equal power allocation(EEEPA)with LF of CSI schemes.     

Robust beamforming in the MISO downlink with quadratic channel estimation and optimal training

Estimation of the channel state information (CSI) in quadratic form (i.e., quadratic channel estimation) in the downlink can be performed at the base station by using the relayed signals from the mobile users, which facilitates optimization with transmitter CSI. In this letter, the condition for the optimal training sequence for quadratic channel estimation in a multiuser multiple-input single-output (MISO) antenna system in the downlink is first obtained. The mean-square-error (MSE) in the CSI estimate is then analyzed. Based on the quadratic CSI estimates, a robust beamforming optimization algorithm to minimize the base station power while achieving individual users' quality-of-service (QoS) constraints, measured by the MSE in data reception, is proposed.     

Power control for delay constrained multi‐channel communications using outdated CSI

In this paper, we study the power allocation scheme for a single user, multi‐channel system, e.g., orthogonal frequency‐division multiplexing (OFDM) systems, under time‐variant wireless fading channels. We assume the receiver feeds back perfectly estimated channel state information (CSI) to the transmitter after a processing delay. The objective of the power allocation is to maximize throughput subject to quality‐of‐service (QoS) constraint. The QoS measure of our consideration is a triplet of data rate, delay, and delay bound violation probability. A two‐step sub‐optimal power allocation scheme is proposed to address the impact of outdated CSI. In the first step, the total transmission power that can be used within one block is determined according to the summation of the channel gains of all the channels. In the second step, the total transmission power is allocated among all the channels. The proposed power control scheme is less sensitive to the feedback delay. Compared to the optimal power allocation scheme designed for the perfect CSI scenario, it has lower computational complexity while achieving comparable capacity. Copyright © 2010 John Wiley & Sons, Ltd.     

Robust joint optimization for MIMO AF multiple-relay systems with correlated channel uncertainties

In the paper, robust joint optimization of the source/relays precoders and destination equalizer is proposed for non-regenerative dual-hop multiple-input multiple-output (MIMO) amplify-and-forward (AF) multiple-relay systems with correlated channel uncertainties. By taking the imperfect channel state information (CSI) into consideration, the robust transceiver/relays joint optimization is developed based on the minimum mean-squared error (MMSE) criterion under individual power constraints at the source and relays. The optimization problem of precoding and amplifying matrices under power constraints belongs to neither concave nor convex so that a nonlinear matrix-form conjugate gradient (MCG) algorithm is applied to explore local optimal solutions. Simulation results illustrate that the robust transceiver/relays joint architecture for an AF-MIMO multiple-relay system outperforms the non-robust transceiver/relays design.     

Maximizing the minimum achievable rates in Cognitive Radio networks subject to stochastic constraints

In this paper, considering errors in estimating the channel state information (CSI), we investigate the problem of robust beamforming in cognitive radio (CR) networks to maximize the minimum achievable rates for secondary users (SU). In addition to the constraints on the transmit power of the users, stochastic constraints on the signal to interference plus noise ratio (SINR) at SUs and interference power at the primary users (PU) are imposed to guarantee the quality of service (QoS) of the network. Bernstein inequalities and semi-definite relaxation are used to transform stochastic constraints to equivalent deterministic inequalities. By replacing new deterministic constraints in the optimization problem and defining new matrices, we write the problem of finding optimal beamforming weights in the form of quasiconvex optimization problem. Generalization of the Dinkelbach’s method is used to obtain optimal beamforming weights. Also, the problem of finding optimum beamforming weights is solved for the case that perfect CSI is available at the transmitters. Simulation results confirm that, the proposed method provides higher achievable rates in comparison with the previous works that minimize the total transmit power. The proposed method is robust because stochastic constraints are satisfied while the estimation of CSI includes some errors.     

Outage-based design of robust Tomlinson–Harashima transceivers for the MISO downlink with QoS requirements

We consider a broadcast channel in which the base station is equipped with multiple antennas and each user has a single antenna, and we study the design of transceivers based on Tomlinson–Harashima precoders with probabilistic quality of service (QoS) requirements for each user, in scenarios with uncertain channel state information (CSI) at the transmitter. Each user's QoS requirement is specified as a constraint on the maximum allowed outage probability of the receiver's mean square error (MSE) with respect to a specified target MSE, and we demonstrate that these outage constraints are associated with constraints on the outage of the received signal-to-interference-plus-noise-ratio (SINR). We consider four different stochastic models for the channel uncertainty, and we design the downlink transceiver so as to minimize the total transmitted power subject to the satisfaction of the probabilistic QoS constraints. We present three conservative approaches to solving the resulting chance constrained optimization problems. These approaches are based on efficiently solvable deterministic convex design formulations that guarantee the satisfaction of the probabilistic QoS constraints. We also demonstrate how to apply these approaches in order to obtain computationally efficient solutions to some related design problems. Our simulations indicate that the proposed methods can significantly expand the range of QoS requirements that can be satisfied in the presence of uncertainty in the CSI.     

Worst-case performance optimization for robust power control in downlink beamforming

In this paper,¹ we examine the problem of robust power control in a downlink beamforming environment under uncertain channel state information (CSI). We suggest that the method of power control using the lower bounds of signal-to-interference-and-noise ratio (SINR) is too pessimistic and will require significantly higher power in transmission than is necessary in practice. Here, a new robust downlink power control solution based on worst-case performance optimization is developed. Our approach employs the explicit modeling of uncertainties in the downlink channel correlation (DCC) matrices and optimizes the amount of transmission power while guaranteeing the worst-case performance to satisfy the quality of service (QoS) constraints for all users. This optimization problem is non-convex and intractable. In order to arrive at an optimal solution to the problem, we propose an iterative algorithm to find the optimum power allocation and worst-case uncertainty matrices. The iterative algorithm is based on the efficient solving of the worst-case uncertainty matrices once the transmission power is given. This can be done by finding the solutions for two cases: (a) when the uncertainty on the DCC matrices is small, for which a closed-form optimum solution can be obtained and (b) when the uncertainty is substantial, for which the intractable problem is transformed into a convex optimization problem readily solvable by an interior point method. Simulation results show that the proposed robust downlink power control using the approach of worst-case performance optimization converges in a few iterations and reduces the transmission power effectively under imperfect knowledge of the channel condition.     

Variable power adaptive MIMO OFDM system under imperfect CSI for mobile ad hoc networks

Future high speed mobile applications require diverse Quality of Service (QoS). To provide flexible data rate services while satisfying the low delay requirements, adaptive MIMO OFDM is a promising technique over time varying channels. In this paper a variable power adaptive MIMO OFDM system under imperfect CSI using cross layer design for mobile ad hoc networks is proposed. Data throughput is maximized while maintaining the delay QoS requirements in the presence of channel estimation errors. Numerical results show that the variable power adaptive MIMO OFDM system provides better spectral efficiency than its constant power counterpart.     

动态频谱访问中的最小最大公平功率与数据率联合控制算法

该文研究动态频谱访问中次用户通过功率控制共享主用户频谱资源的问题。将最小最大公平功率与数据率联合控制问题建模为准凹优化问题,提出了基于迭代求解线性规划问题的功率控制算法。此外,还提出了通过次用户间相互协作估计次用户到主用户以及次用户间链路增益的方法,分析了链路增益估计误差的统计特性,提出了利用保护裕量降低链路增益估计误差对主用户和次用户服务质量影响的方法。仿真结果表明:所提出算法的性能与现有算法相同,但计算时间仅为现有算法的10%~50%,甚至更低;1 dB的干扰裕量和1.5 dB的信干噪比裕量足以保证主用户和次用户服务质量免受链路增益估计误差的影响。