一种新的硬判决并行干扰消除算法

多址干扰的存在是影响CDMA系统性能和限定系统容量的重要因素。针对多址干扰信号的特点，研究了一种改进的硬判断决并行干扰多用户检测器。分析和仿真结果表明，该多用户检测器具有更好的性能和抗远近效应的能力，具有广泛的应用前景。     

Improved Space-Time Selective Interference Cancellation Scheme for CDMA Systems

IntroductionAdaptiveantennaarrayscanreduceco channelinterference (CCI)fromotherusersaswellasmitigatetheeffectofmultipathfadinginwirelessenvironments .SinceCDMAsystemsareinterferencelimitedinnature ,smartantennahasbeenregardedasoneofthecoresystemcomponents…     

智能天线系统中干扰抵消的算法研究

首先分析了智能天线在CDMA系统中应用,理论分析了通过空间特征向量来对其实现“零陷“,提出采用压低基站的上行干扰提升系统的性能的新算法,实验仿真显示:该算法通过空域滤波,能够显著提高系统性能.     

BLIND DIFFERENTIAL ADAPTIVE MULTIUSER DETECTION

IntroductionThe problem of combating multi- access interfer-ence ( MAI) in CDMA systems has receivedgreat attention recently[1～ 3] . In Ref. [4 ] ,M.Honig employed a blind adaptive multiuser de-tector based on the minimization of mean- out-put- energy( MOE) to overcome MAI,and itre-quired no more knowledge than did the conven-tional single- user receiver.Surplus energy wasemployed to suppress the effects of multi- accessinterference and thus provided an optimal detec-tion solution. The…     

基于分组纠错码指导的多分辨率SIC算法

采用维纳均衡器和能量均匀分布扩频矩阵的SOFDM系统在频率选择性衰落信道中的误比特率小于OFDM系统,但是维纳均衡器的使用引入了子信道间干扰,且SOFDM系统的各子信道信干比相等,现有的相继干扰消除(SIC)算法无法有效地消除该干扰.为解决这一问题,文中提出了基于分组纠错码指导的多分辨率SIC算法,描述了该算法的子信道间干扰消除原理和实现过程,并通过计算机仿真验证了该算法的有效性.     

基于Gram-Schmidt正交化法的串行干扰消除算法

基于Gram-Schmidt正交化法,提出了一种改进的串行干扰消除算法.不同于传统的串行干扰消除算法,该算法运用Gram-Schmidt正交化法,通过扩频序列获取正交序列作为最优解扩码,使得检测器每一级最强用户的解扩码与其他用户的扩频码所张的子空间正交,从而实现对多址干扰的完全抑制.给出了具有幅度失配的系统误码率近似公式,讨论了幅度失配对检测性能的影响.仿真结果表明,改进算法能有效抑制CDMA系统中的多址干扰,改善系统性能.     

An Iterative Power Allocation Algorithm for Group-wise Space-Time Block Coding Systems

An iterative transmit power allocation (PA) algorithm was proposed for group-wise space-time block coding (G-STBC) systems with group-wise successive interference cancellation (GSIC) receivers. Group-wise interference suppression (GIS) filters are employed to separate each group's transmit signals from other interferences and noise. While the total power on all transmit symbols is constrained, all transmit PA coefficients are updated jointly according to the channel information at each iteration. Through PA, each detection symbol has the same post-detection signal to interference-and-noise ratio (SINR). The simulation results verify that the proposed PA algorithm converges at the equilibrium quickly after few iterations, and it achieves much lower bit error rates than the previous single symbol SIC PA and the fixed ratio PA algorithms for G-STBC systems with GSIC receivers .     

Complexity Iterative Receiver for Turbo-BLAST over Frequency Selective Fading Channels

The computationally efficient iterative receiver is investigated for Turbo-BLAST ( Bell Labs layered space time) system over frequency selective fading channels. Compared with the conventional receiver based on soft interference cancellation ( SIC), an iterative detection scheme based on bit-level cancellation is presented to reduce the complexity of the receiver by decomposing of an M-QAM constellation into a linear combination of binary constellations. Simulation results demonstrate that compared with the conventional SIC scheme, the proposed scheme based on bit-level cancellation performs almost as well as the SIC scheme after several iterations while proving a lot of saving in computational complexity.     

中频数字对消器的原理及仿真分析

提出了一种利用广播电视信号对目标进行无源定位中的中频数字对消器,描述了该对消器的原理及模型,给出了仿真分析及实验结果,并指出工程设计中需要考虑的一些问题.实验结果表明:该对消器对电视信号中频直达波信号对消比达到了35 dB以上,在雷达应用中可抗有源干扰和天线副瓣.     

PIC-MF-based Iterative Receiver for Multiuser Space Frequency Block Coding Systems

A novel low-complexity iterative receiver for multiuser space frequency block coding (SFBC) system was proposed in this paper. Unlike the conventional linear minimum mean square error (MMSE) detector, which requires matrix inversion at each iteration, the soft-in soft-out (SISO) detector is simply a parallel interference cancellation (PIC)-matched filter (MF) operation. The probability density function (PDF) of PIC-MF detector output is approximated as Gaussian, whose variance is calculated with a priori information fed back from the channel decoder. With this approximation, the log likelihood ratios (LLRs) of transmitted bits are under-estimated. Then the LLRs are multiplied by a constant factor to achieve a performance gain. The constant factor is optimized according to extrinsic information transfer (EXIT) chart of the SISO detector. Simulation results show that the proposed iterative receiver can significantly improve the system performance and converge to the matched filter bound (MFB) with low computational complexity at high signal-to-noise ratios (SNRs).     

Lattice-basis reduction precoding based on successive interference cancellation design for multiuser MIMO downlink system

Two kinds of lattice-basis reduction precoding schemes based on successive interference cancellation are proposed. The successive interference cancellation (SIC) structure can be obtained by either orthogonal and a right triangular matrix (QR) decomposition, or the Vertical Bell Labs Layered Space Time (VBLAST) algorithm which provides optimal user ordering. Moreover, the extended channel approach is applied to the proposed SICbased schemes. Simulation results show that the proposed schemes can achieve comparable BER performance to vector precoding (VP).     

A Dynamic Job Scheduling Algorithm for Parallel System

One of the fundamental problems in parallel and distributed systems is deciding how to allocate jobs to processors. The goals of job scheduling in a parallel environment are to minimize the parallel execution time of a job and try to balance the user‘s desire with the system‘s desire. The users always want their jobs be completed as quickly as possible, while the system wants to service as many jobs as possible. In this paper, a dynamic job-scheduling algorithm was introduced. This algorithm tries to utilize the information of a practical system to allo-cate the jobs more evenly. The communication time between the processor and scheduler is overlapped with the computation time of the processor. So the communication overhead can he little. The principle of scheduling the job is based on the desirability of each processor. The scheduler would not allocate a new job to a processor that is already fully utilized. The execution efficiency of the system will he increased. This algorithm also can he reused in other complex algorithms.     

A New Parallel Algorithm in Power Flow Calculation: Dynamic Asynchronous Parallel Algorithm

Based on the general methods in power flow calculation of power system and onconceptions and classifications of parallel algorithm, a new approach named DynamicAsynchronous Parallel Algorithm that applies to the online analysis and real-time dispatching and controlling of large-scale power network was put forward in this paper. Its performances of high speed and dynamic following have been verified on IEEE-14 bus system.     

NEURAL NETWORK TRAINING WITH PARALLEL PARTICLE SWARM OPTIMIZER

Feed forward neural net works such as multi-layer perceptron,radial basis function neural net-works,have been widely applied to classification,function approxi mation and data mining.Evolu-tionary computation has been explored to train neu-ral net works as a very promising and competitive al-ternative learning method,because it has potentialto produce global mini mum in the weight space.Recently,an emerging evolutionary computationtechnique,Particle Swar m Opti mization(PSO)be-comes a hot to…     

PID模糊控制在医用理疗仪温度控制器中的应用

本文介绍了用PID模糊控制技术中来解决在温度控制器控温过程中会产生的惯性温度误差问题。系统中的PID算法采用增量算法为基本算法,并按照实际应用做了适当的修改。经过实际测试,系统运行良好,证明在此医用理疗仪温度控制器中应用此PID算法取得了令人满意的结果。     

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针对无容量约束的单分配轴-辐式物流网络设计问题的特点,为其建立了单分配p-枢纽中位模型,并提出了一种基于蚁群算法的启发式求解算法. 该算法分两步实现：首先利用蚁群算法来确定网络中枢纽节点的位置,然后用另一种启发式算法将非枢纽节点分配给枢纽节点,同时,将一种基于6种邻域结构的变邻域搜索算法作为蚁群算法的局域搜索策略以提升算法的全局搜索能力,并加快收敛速度. 最后结合澳大利亚邮政数据进行了算例仿真实验,并对蚁群算法中参数的合理设置进行了测试分析,实验结果表明,该算法在求解此问题时有着良好的有效性和较快的求解效率.     

无容量约束单分配轴-辐式物流网络设计

针对无容量约束的单分配轴-辐式物流网络设计问题的特点,为其建立了单分配p-枢纽中位模型,并提出了一种基于蚁群算法的启发式求解算法. 该算法分两步实现：首先利用蚁群算法来确定网络中枢纽节点的位置,然后用另一种启发式算法将非枢纽节点分配给枢纽节点,同时,将一种基于6种邻域结构的变邻域搜索算法作为蚁群算法的局域搜索策略以提升算法的全局搜索能力,并加快收敛速度. 最后结合澳大利亚邮政数据进行了算例仿真实验,并对蚁群算法中参数的合理设置进行了测试分析,实验结果表明,该算法在求解此问题时有着良好的有效性和较快的求解效率.     

基于数据修正的改进型灰色-RBF网络预测

针对既呈趋势性,又呈波动性的时间序列难以预测的问题, 提出了基于失真数据的修正的改进型灰色-RBF网络预测模型及算法.即用改进型灰色模型提取趋势性因素,用神经网络处理波动性因素,另尝试性的提出还须排除异常干扰因素,即查找和修正序列的异常数据.并以南昌铁路车站旅客发送量预测为例,验证了算法的有效性,收到很好的预测效果.     

两自由度并联机器人的RBF神经网络辨识自适应控制

针对平面两自由度五杆并联机器人的轨迹跟踪问题,提出了一种基于RBF神经网络的自适应PID控制方法.该控制方案利用RBF神经网络自适应学习辨识并联机器人系统的未知非线性动态,可以在线调整PID控制参数以实现高精度控制.仿真结果显示该控制策略可以精确实现对于并联五杆机器人的轨迹跟踪控制,该方法的自适应性和跟踪性能均优于传统的PID控制.     

通道内平行铁路间列车径路选择优化研究

论文通过运用系统工程和系统科学的方法与理论,将通道系统进行抽象的描述,选取通过能力、旅行速度、运行调整和运输成本四个方面,作为通道系统分工比选和判断优劣的标准,建立了通道分工的系统优化模型,并运用满意优化的理论,给出了模型的算法步骤.最后,运用研究成果,确定出了京兰通道（北京-集宁段）列车的优化分工方案.