神经网络在CDMA移动通信上行链路功率控制中的应用研究

提出了一种神经网络功率控制方案，研究了该方案在码分多址(CDMA)移动通信中实现最小发送功率控制问题。首先导出了最小发送功率控制模型。而后，利用最陡下降方法得到了求解该模型的神经网络的原理框图，并分析了用该网络进行最小发送功率控制的基本理论和实际性能，探讨了该网络相关参数的确定方法。最后用计算机仿真法模拟出该方案的运行性能。仿真结果表明与最小功率分配算法相比，神经网络功率控制方案可以提高基站接收信号的平均信扰比，降低信扰比的平均偏差，提高信扰比达到目标信扰比90％以上的用户数量，从而可以降低用户信号的中断概率、提高信道容量。     

快速Lagrange算法在双速率多用户检测器的功率控制中的应用研究

本文提出了一种快速Lagrange算法,并将它应用于宽带码分多址扩频通信双速率多用户检测器的功率控制中,从而使系统在达到不同的信扰比的条件下,各个用户的发送功率之和最小。本文分析了用该算法对双速率多用户检测器进行最小发送功率控制的基本理论和实际性能,探讨了该算法中相关参数的确定方法。该算法利用平均和反馈技术加快了Lagrange算法的收敛速度,因此有较好的实时性。仿真结果表明与快速随机功率控制算法相比,快速Lagrange功率控制算法可以提高双速率多用户检测器输出信号的平均信扰比,降低信扰比的平均偏差,提高达到信扰比要求的用户数量。     

自适应RBF神经网络在CDMA移动通信上行链路功率控制中的应用研究

提出了一种自适应RBF神经网络功率控制方案。详细研究了该网络在DS-CDMA通信中，进行上行链路闭环功率控制(基于信扰比(SIR))的应用理论，给出了该网络参数的计算方法。最后用计算机仿真法模拟出该控制器的运行性能。结果表明基于SIR的自适应RBF神经网络功率控制器能自适应地调整移动台的发射功率，使基站接收信号的信扰比始终非常接近于一个常数，且有比定步长功率控制更小的SIR跟踪误差，从而可以降低接收信号的中断概率、提高信道容量。     

认知无线电系统中一种改进的功率控制博弈算法

分布式功率控制是认知无线电(CR)系统中的关键技术之一,它直接影响到无线系统的性能。本文采用了博弈论的方法来实现对CR用户的分布式功率控制,在David Goodman的非协作博弈算法的基础上,给出了一种改进的效用函数,它使各用户在满足要求信干比条件下发送功率最小,同时使整个系统内由各种干扰引起的失真最小。本文通过理论推导证明了新的效用函数存在纳什均衡,并且均衡点唯一,同时仿真验证了该算法的收敛性,仿真结果表明这种兼顾用户自身利益以及用户间公平性的效用函数能降低发送功率,并且有效提高CR系统的性能。     

认知无线电中基于多次博弈的功率控制算法

基于博弈论对认知无线电网络中的功率控制问题进行了建模分析,提出了一种基于多次博弈的功率控制算法,证明了该算法中纳什均衡的存在性和惟一性。仿真结果表明,基于该博弈模型的功率控制算法收敛性比传统算法好,经过7次左右迭代即可收敛,满足系统实时性要求,同时又能够以较低的功率水平满足不同用户对信干比的要求,实现了对不同用户发射功率的有效控制,系统性能明显提高。     

一种新型的基于信干比预测的上行链路功率控制算法

针对TD-SCDMA系统的上行链路,本文提出了一种新型的基于信干比预测的内环功率控制算法。利用自适应滤波器输入信号的正交分量作为权向量的调整方向,根据前几帧和当前帧测得的信干比对下一帧信干比进行预测,基站依据预测的结果对发射功率进行控制。仿真结果表明:与传统功率控制方法相比,该方法控制精度高,实现简单,收敛速度快。     

TD-SCDMA系统中一种软件集成智能天线算法

给出了一种采用信干噪比准则的、集成了预多波束天线与LMS自适应天线的软件天线方案,该方案采用开关合并方法,把软件天线输出接到最大输出信噪比的算法输出,实现算法分集.在TD-SCDMA动态模型上对提出的方法进行了仿真,结果表明,采用集成软件天线方案的误码率性能要优于单纯的预多波束天线或LMS自适应智能天线.仿真过程考虑了用户来波方向和用户到基站距离的动态变化,以及功率控制算法和系统同步过程的影响.     

分布式无线通信系统中的主从协同功控

分布式无线通信系统通过多个基站与移动台协作通信有效地提高了系统的容量和覆盖范围。然而传统的功率控制算法并不适用于移动台同时接收多个基站信号的情况。本文提出了一种基于适用多小区结构的主从协同功控算法。该算法把为移动台服务的基站分为主基站和从基站,各从基站以主基站分配的功率为参考值分配功率,可使整个覆盖区域内的所有移动台达到平衡的信干比,且可适用于任意拓扑结构的,使用全向天线或定向天线的分布式无线通信系统,并可以采用低复杂度和开销的分布式算法实现。仿真结果表明,在不同环境中,与现有的分布式系统中功控算法相比,新算法可以显著地提高整个系统的容量。     

异构蜂窝网络中用户关联与基站功率的协同优化

为实现异构蜂窝网络中宏基站和小基站之间的负载均衡,提出了一种基于效用函数最大化模型的用户关联机制和基站功率控制的协同优化方案.通过迭代算法求解该协同优化问题,首先在基站功率固定的情况下求得最佳用户关联策略,然后在所得的用户关联策略基础上通过Zoutendijk可行方向法求得基站最佳功率.通过协同优化获得的用户关联策略和基站功率控制实现了基站之间的负载均衡,通过降低宏基站功率和关闭闲置小基站降低了基站的能耗.仿真实验表明,所提方案和不实施功率控制的用户关联策略相比,实现了宏基站与小基站之间的负载均衡,降低了宏基站对小基站用户的干扰,提升了小基站用户的信号干扰噪声比,用户速率中位值提高了20％.     

下行时间反转非正交多址接入系统的设计与优化

针对时间反转多址接入系统在用户相关性较大时，用户间干扰严重，导致系统和速率下降问题，提出一种将时间反转多址接入技术与功率域非正交多址接入技术相结合的下行多址系统方案.将相关性较高的用户分为一组，组内用户符号采用非正交叠加传输的方式，不同用户组的符号采用时间反转滤波器进行预处理，实现多用户符号的同时同频传输.给出了一种用户分组算法，进一步在用户最小速率和基站的总发送功率约束下，采用迭代信干噪比注水算法优化用户的发送功率以最大化系统和速率.仿真结果表明，本文方案在配备单根发送天线、预滤波器采用迫零准则设计时高发送功率下的系统和速率比常规的时间反转多址接入方案约高30%；天线数目越多，性能优势越明显.     

Performance comparison of different selection combining algorithms in presence of co-channel interference

In this paper, we present a unified approach for the computation of the outage probability, the level crossing rate (LCR), and the average outage duration (AOD) of selection combining (SC) in the presence of multiple cochannel interferences and under both minimum signal-to-interference ratio (SIR) and desired signal power constraints. We consider three selection algorithms, namely: 1) the best signal power algorithm; 2) the best SIR algorithm; and 3) the best total power (desired plus interference) algorithm. As a specific application example, we analyze the three algorithms for a low-complexity dual-branch SC receiver subject to multiple interferers over Rayleigh fading channels. When applicable, the new results are compared to those previously reported in the literature dealing with the outage probability, AOD, and LCR of 1) interference-limited systems and 2) power-limited systems. Numerical examples show that the minimum desired signal power constraint induces a floor to the outage probability, AOD, and LCR performance measures. They also show that the best SIR algorithm provides the best outage probability and AOD performance for low average SIR. On the other hand, the best signal power algorithm and the best S+I algorithm outperform the best SIR algorithm for high average SIR. It is also shown that the best SIR algorithm tends to have more outage level crossings.     

Achievable-SIR-based predictive closed-loop power control in a CDMAmobile system

A power control algorithm with two prediction models based on an achievable signal-to-interference power ratio (SIR) has been proposed under a multipath Rayleigh fading environment in a code-division multiple-access (CDMA) mobile system. An achievable SIR is defined as the maximum-minimum SIR among all users at a particular time step. The corresponding mobile transmission powers are denoted as the "optimum transmission powers." In the individual power predictor (IPP) model, a linear transversal filter is assigned to each user. The output of the IPP, which is a linear combination of the optimum transmission powers of the mobile during the current and previous power measurement periods, predicts the optimum transmission power of the mobile in the next time step. In the global power predictor (GPP) model, a single predictor, constructed by a linear neural network, is used to predict the optimum transmission powers of all mobiles in the next time step. In both predictor models, the weights of the predictors are updated by using the recursive least squares algorithm. To further improve the performance, a reduced power-measurement period has been studied. Simulation results show that the proposed power control algorithm can achieve a lower outage probability and a smaller dynamic range of transmission power compared with a conventional power control scheme     

Utility-based power control with QoS support

This paper addresses the issue of incorporating QoS requirements expressed in terms of some minimum SIR targets into the traditional utility-based power control problem. As suitable projection methods seem to be not amenable to distributed implementation, we first focus on a primal-dual algorithm to solve the utility-based power control problem subject to the SIR requirements. We prove a global convergence of the algorithm for a large class of utility functions and show that it can be implemented in a distributed wireless environment. However, the approach has an important drawback: An optimal solution may not exist as the SIR targets may be infeasible due to, for instance, channel effects. This motivates a reformulation of the problem so that an optimal solution always exists. We consider the possibility of using a barrier method to closely approach the desired SIRs of the users and combine this approach with the conventional utility-based power control problem to incorporate best effort users. We prove relevant properties of optimal solutions and propose a distributed recursive algorithm with global convergence. Finally, the performance of the proposed approaches is verified by simulations.     

一种基于计费的WCDMA功率控制方法

在第三代移动通信系统中,为了有效地提高系统容量和通信质量,需要对无线资源如发射功率作合理的动态分配。该文通过研究 WCDMA系统中上行链路的干扰情况,推导得出 WCDMA系统的容量与业务性能指标的关系。通过定义网络资源份额,将功率控制问题转换为总量小于1的网络资源份额的分配问题。然后利用统一价格拍卖对网络资源份额进行最优配置,使得发射功率这一重要无线资源合理地分配给对其评价最高的用户业务。最后给出了上述算法的数值仿真。     

Fast stochastic power control algorithms for nonlinear multiuser receivers

Uplink communication in a cellular radio network is considered where the base station in each cell employs linear or nonlinear (decision feedback) multiuser receivers. For any such receiver, the problem of interest is that of minimizing the total transmit power under the constraint that all the users of the network achieve their quality-of-service objective in terms of signal-to-interference ratio (SIR). When the solution is feasible for the desired SIR requirements, the optimum powers are computed with a distributed iterative power control strategy suitable for implementation at each base station. While the deterministic algorithm requires both in-cell and out-of-cell user information, the stochastic algorithm proposed in this paper can be implemented at the base stations in a truly distributed manner requiring knowledge of only in-cell parameters. Such an algorithm was proposed previously for the case where base stations use linear (single user) matched filter (MF) receivers. However, the feasibility region in terms of attainable SIRs for a well-designed multiuser receiver, particularly for a nonlinear receiver that employs decision feedback, is generally much larger than it is for the linear MF receiver. The stochastic power control algorithm in this paper, for linear or nonlinear multiuser receivers, converges in the mean-square sense to the minimal powers when the target SIRs are feasible. The second major focus of this paper is to improve the convergence properties of the conventional stochastic approximation based power control strategy by using the more recent results on averaging. Convergence issues of both the "nonaveraged" and "averaged" algorithms are investigated, and numerical examples are presented to demonstrate the performance improvement due to averaging.     

一种支持QoS的WCDMA混合神经网络反向链路功率控制算法

本文提出了一种混合神经网络反向链路功率控制算法,其外环控制采用Adaline神经网络模型,以不同业务的目标误帧率为指标,实时检测链路的误码状况,调整SIR目标值.内环控制采用Hopfield神经网络模型,通过控制移动台的发射功率确保SIR达到该目标值.与固定步长功率控制算法相比,该算法提高了控制精度和系统的稳定性,能够获得更高的通信质量.仿真实验也验证了算法的有效性.     

Control of induction motors for both high dynamic performance andhigh power efficiency

The authors attempt to control induction motors with maximum power efficiency as well as high dynamic performance by means of decoupling of motor speed (or motor torque) and rotor flux. For maximum power efficiency, the squared rotor flux is adjusted according to a minimum power search algorithm until the measured power input reaches the minimum. Since the motor speed is dynamically decoupled from the rotor flux, this can be done successfully without any degradation of motor speed responses. The controller depends on rotor resistance but not on stator resistance. However, the performance of the control scheme is robust with respect to variations in rotor resistance because an identification algorithm for rotor resistance is employed. The identification algorithm for rotor resistance has some advantages over the previous methods. To demonstrate the practical significance of the results, some experimental results are presented     

Power control algorithm in cognitive radio system based on modified Shuffled Frog Leaping Algorithm

Based on the non-cooperative power control game introduced by David Goodman, in this paper, we will introduce the concept of target SIR, modify the utility function, and propose a modified power control game algorithm. In this proposed power control game algorithm, it will be proved that the Nash equilibrium exists and is unique. To further improve the accuracy of the solution, the Shuffled Frog Leaping Algorithm (SFLA) will be modified and adopted by incorporating the basic ideas of Artificial Fish (AF). It can be shown that the proposed algorithm will have better global convergence and will have less possibility to be tripped in local optimum. Simulation results show that the proposed power control algorithm based on modified Shuffled Frog Leaping Algorithm (MSFLA) can not only increases the controllability on the target SIR but also reduces the user transmission power and improves system performance.