Multi-User MIMO Mobile CDMA Uplink System Employing Turbo Coding and Joint Detection Through a Multipath Rayleigh Fading Channel

In this paper, a generalized multiple-input multiple-output (MIMO) antenna system that can be fitted to the uplink of a wireless communication system is considered for the general case of multi-user. At the transmitter, the information bits are Turbo coded, then interleaved and passed through a serial-to-parallel converter. The channel is assumed bad urban suffering from multipath Rayleigh fading resulting in inter-symbol and multiple access interferences (ISI and MAI). At the front-end of the receiver, a number of receiving antennas are used followed by a joint multi-user estimator based on the Minimum Mean Square Error Block Linear Equalizer (MMSE-BLE).Computer simulations demonstrate a significant performance improvement in both single user and multi-user cases.This paper depends in parts on that presented at the 11th European Wireless Conference, Cyprus, Nicosia, pp. 187–192, April 2005. Yasmine A. Fahmy was born in Guiza, Egypt, on June 4, 1976. She received the B.Sc., M.Sc. and Ph.D. degrees in Communication and Electronics engineering from Cairo University, Egypt on 1999, 2001 and 2005 respectively. She is presently an assistant professor at Cairo University, Egypt. Her current field of interest is wireless communication and channel estimation. Hebat-Allah M. Mourad received her B.Sc., M. Sc. and Ph.D. degrees in electrical communication engineering from Cairo University, Egypt, in 1983, 1987 and 1994 respectively. Since 1983, she has been with the Department of Electronics and Communications, Faculty of Engineering, Cairo University, and is currently associate professor there. Her research interests include optical fiber communications, mobile and satellite communications. Emad K. Al-Hussaini received his B.Sc degree in Electrical Communication Engineering from Ain-Shams University, Cairo, Egypt, in 1964 and his M.Sc and Ph.D. degrees from Cairo University, Giza, Egypt, in 1974 and 1977, respectively. From 1964 to 1970, he was with the General Egyptian Aeroorganization. Since 1970, he has been with the Department of Electronics and Communications, Faculty of Engineering, Cairo University, and is currently professor there. He was a research fellow at Imperial College, London, UK, and at the Moore School of Electrical Engineering, University of Pennsylvania, Philadelphia, PA, USA, in the academic years 1976/1977 and 1981/1982, respectively. In 1990, he received the Egyptian national encouragement award for outstanding engineering research. He has written several papers for technical international journals and conferences. His research interests include signal processing, fading channel communication, modulation, and cellular mobile radio systems. Dr Al-Hussaini is a senior member of IEEE. He is listed in Marquis Whos Who in the World and in the IBC (International Biographical Center, Cambridge) for outstanding people of the 20th century.     

一种基于检测信息可靠度的部分软干扰消除迭代多用户检测算法

该文提出了一种基于检测信息可靠度的部分软干扰消除迭代多用户检测算法。如果由从信道译码器所获得的发送字符的先验信息大于某一预定阈值,则认为对其检测具有较高的可靠度,因而可以考虑将其对应的多址干扰成分从匹配滤波器输出向量中直接消除,相当于减小了干扰用户的数目,从而可以减小迭代多用户检测算法的复杂度。该算法的计算复杂度能够随着多址干扰的减小和信道信噪比的增大而降低。     

基于改进人工鱼群-蛙跳算法优化LSSVM参数短期负荷预测

短期电力负荷预测在电力系统安全调度、经济运行方面起到关键作用。在用最小二乘支持向量机进行负荷预测时,参数选择将直接影响预测精度。为了提高LSSVM负荷预测精度,文中提出一种基于Levy变异自适应视野人工鱼群-蛙跳算法对LSSVM进行参数优化的方法。以某县负荷、天气等历史数据对LSSVM进行训练,建立LAVAFSA-SFLA-LSSVM、AFSA-LSSVM、LAFSA-SFLA-LSSVM共3种预测模型,对该地区某日24 h的电力负荷进行预测。算例结果表明,LAVAFSA-SFLA-LSSVM预测精度比AFSA-LSSVM和LAFSA-SFLA-LSSVM更高,预测误差更小。     

接地网故障诊断的线性最小二乘优化模型及算法

变电站接地网对变电站的安全运行具有重要的意义,是电力运行部门十分关注的问题,近年来也成为学术界研究的一个热点。运用电路基本理论,提出了基于灵敏度分析的线性最小二乘优化模型及算法。首先建立了可测节点电压变化量与接地网导体电阻变化量之间的灵敏度关系线性模型,给出了灵敏度的求解步骤,最后提出了基于线性最小二乘优化模型及算法。通过对一个实际接地网的故障仿真说明,提出的诊断模型和算法具有较高的诊断精度。     

部分并行软干扰消除迭代多用户检测算法研究

本文提出了一种基于部分并行干扰消除(PPIC)结构的迭代多用户检测算法,并对基于PPIC的迭代多用户检测器的迭代结构进行了改进.由于PPIC多用户检测器前一级输出的信息的准确度会影响到后一级的检测,所以为了提高基于PPIC的迭代多用户检测器的性能,对PPIC每一级的输出信息结合最大后验概率(MAP)信道译码器单独进行迭代处理,这样就提高了PPIC每一级输出的信息的准确性.该迭代结构可用于其他基于PIC型的迭代多用户检测算法.     

基于混合编程的高精度激光多普勒信号处理技术

针对激光多普勒信号中存在较大噪声干扰的实际情况,为了抑制这些噪声干扰,提高激光多普勒测速仪的测量精度,提出了对激光多普勒信号进行最小均方差(LMS)自适应滤波后作快速傅里叶变换(FFT),基于混合编程思想对所得到的频谱,先进行频谱细化,再进行频谱校正的信号处理方法,并对理想正弦信号和实测多普勒信号分别进行仿真计算和实验研究。仿真和实验结果表明：LMS自适应滤波技术可以有效抑制激光多普勒测量中的多频率噪声的干扰,此技术能够适应于很宽的信噪比范围,大大提高多普勒信号的信噪比;频谱细化技术可以提高激光多普勒信号的频谱分辨率,频谱校正技术可以准确地校正多普勒频率,使校正后的频率更加接近于真实值;信号处理精度比直接进行FFT提高2~3倍。     

微型光纤光谱仪的波长定标分析

为了提高光纤光谱仪的测量精度,采用标准汞氩灯谱线和最小二乘法的3阶线性拟合,取得了完整的波长定标方案。结果表明,算术平均误差小于0.167nm,标准差小于0.217nm,波长与像素的拟合相关程度较高;定标后波长不确定度优于0.11nm,误差小于0.15nm,波长重复性可达0.01nm。这一结果对提高光谱仪实际应用中的测量精度是非常有益的。     

基于小波分析和鲁棒最小二乘的信息融合估计算法

对于农田土壤的多传感器检测系统来说,其测量的信息具有非线性和时空变异等特性,因此对信息融合方法的基本要求是具有鲁棒性和并行处理能力.应用小波分析理论,对原始测量数据进行了降噪处理,使降噪后的数据更能反映土壤的本质及变化规律:应用鲁棒最小二乘估计技术可以对不同传感器数据进行综合处理,去除冗余,克服歧义,得到比任何单个传感器更全面、更准确、更可靠的信息.针对农业中的自然环境具有很强的不确定性和经验性,运用基于小波分析的降噪和现代信息融合思想,提出了一种基于小波降噪和鲁棒最小二乘的信息融合估计方法.通过实验分析,其结果表明该方法是可行和值得研究的.     

线性调频步进信号雷达目标运动参数估计方法

针对目标运动对线性调频步进信号雷达成像的影响,提出一种基于时频分析的目标运动参数估计方法。对差频处理后的各簇回波信号进行快速傅里叶变换,利用变换后信号与子脉冲序列的线性调频关系,通过维格纳分布和Radon变换对目标不同时刻运动参数进行估计。结合二值数学形态学与图像边缘检测方法提高对多散射点目标运动参数估计的精度。在此基础上,针对目标可能出现的变速运动情况,利用最小二乘算法拟合整个成像时间内目标运动速度的变化,较好地实现对机动目标的运动参数估计。仿真实验验证了本文方法的有效性。     

一种恒流源驱动的高精度温度测量系统设计

为提高温度测量精度,利用REF200提供的0.4mA恒定电流驱动串联的四线制温度传感器PT1000和精密电阻,在传感器和精密电阻两端分别提取电压信号并对其进行调理,通过高精度AD7712对所得到的电压信号进行放大和A/D转换,设计了一种高精度温度测量系统。为了减小高精度温度测量中铂电阻非线性所引起的误差,在上位机中对数字信号进行了最小二乘法算法处理。测试结果表明,该系统稳定可靠,其随机误差和系统误差均小于0.1℃,实现了高精度温度测量。