可见光通信中HACO-OFDM系统的信道估计研究

针对可见光通信(VLC)中混合非对称幅度截断光正交频分复用(HACO-OFDM)系统中非视距路径(NLOS)信道会恶化可见光通信系统的误码性能,提出一种用于HACO-OFDM系统的信道估计方案。在该方案中,块状导频仅被添加到奇数子载波,通过联合最小二乘(LS)算法和三次样条插值获得完整的信道状态信息(CSI)。仿真结果表明,HACO-OFDM系统采用提出的信道估计方案后,显著改善了来自NLOS信道信号的误码性能。本方案实现简单,能够较准确的获取信道状态信息,可以提高NLOS场景下的可见光通信质量。     

IR-UWB测距中NLOS状态的鉴别

NLOS效应是IR-UWB测距定位系统中影响精度的主要因素之一。该文提出不依赖于信道估计,直接从接收信号采样序列中提取特征参量进行NLOS鉴别的方法,构造了采样序列的首均比与峰均比乘积作为鉴别参量,并与使用峭度和平均附加时延这两个参量的鉴别性能进行了对比。仿真结果表明:相干测距所对应的鉴别性能要好于非相干测距,原因是更为精确的DP检测结果及高采样速率使得参量提取值更能准确地反映信道状态信息;使用峭度和平均附加时延作为鉴别参量所能获得鉴别性能均不理想,而使用采样序列的首均比与峰均比乘积能使鉴别成功率提高10%左右。在定位模块中融入该文所获得的NLOS的鉴别结果将有助于定位精度的进一步提升。     

室内环境下NLOS误差的鉴别及其抑制算法

室内定位技术中,现有抗非视距误差的算法需要利用NLOS先验信息或统计特性.为了克服这一缺点,提出了一种低复杂度的几何面积判决鉴别算法.通过利用几何面积判决鉴别算法的判决结果,推导出一种Taylor级数抑制NLOS误差的室内定位算法.仿真试验表明,与传统室内定位抗非视距误差的算法相比,该算法定位精度高,收敛速度快,有较好的抗NLOS性能.     

非线性卫星信道下的粒子滤波盲均衡方法

针对卫星信道中高功率放大器产生非线性失真的问题,本文提出了一种基于粒子滤波技术的盲均衡法。该算法优势在于不需要对非线性信道线性化处理,而是利用带权值的离散随机样本点来对期望分布进行近似,通过将非线性模型建模成状态空间模型,对信道参数进行跟踪和符号序列估计。仿真结果表明,算法实现了对放大器非线性幅度和相位特性的粒子滤波估计,并对符号序列进行了盲恢复,在误比特率为 较截断Volterra均衡有1.5 dB左右的性能增益;通过增加粒子数目和平滑长度能一定程度上提高算法性能,但在复杂度与性能折中考虑下,不能无限增加粒子数目。      

卷积码在UWB Rake接收机中的应用

针对有码间干扰的TH-PPM-UWB通信系统,研究了基于卷积码Rake接收机的性能,并在IEEE 15.3a UWB的LOS信道和NLOS信道下对采用卷积码Rake接收机的误比特率进行计算机仿真,仿真结果表明,当SNR达到一定值后,无论是LOS信道还是NLOS信道,相对未编码的Rake接收机,采用卷积码的Rake接收机性能明显提高,在NLOS信道更为显著。     

适用于低速UWB的多径接收算法改进

叉指数优化选择是传统MMSE-Rake(最小均方差Rake接收机)算法的重要组成部分,广泛应用于UWB(超带宽)Rake接收机中。为了提高在低速传输条件下UWB系统对多径信号接收的快速识别能力,提出了一种基于优化抽头系数的MBER(最小误比特率)改进算法,该算法可在不降低多径分辨率的前提下,通过简化Rake叉指数实现快速定位。仿真结果表明,在低速CM3(NLOS信道)和CM4(特殊情况下NLOS信道)多径模拟信道传输条件下,改进后的算法在性能上优于传统MMSERake算法,不仅降低了Rake接收机的复杂度,还提高了信号接收的实时性。     

MIMO-OFDM系统的迭代信道估计算法

由于传统的信道估计方法忽略了信道参数的不确定性,因此,提出了基于因子图利用软信道参数信息的低复杂度的迭代估计算法。该算法首先将信道参数信息视为高斯变量,并通过概率信息表示其均值和方差,从而避免了对变量的积分,降低计算复杂度;然后利用和积算法,由导频位置处的初始信道信息,通过转移函数节点进行信息交互,最终获得信道频率响应。仿真结果表明,相对于传统的信道估计算法,新的迭代估计算法能够获得更好的误码率性能。     

一种粒子滤波的盲多用户检测快速算法

该文在时间观察状态空间模型基础上,针对粒子滤波计算复杂的问题,构造了一种在同步快变平衰落信道下计算复杂度低的粒子滤波的DS-CDMA盲多用户检测快速算法。该算法通过对超过门限数目的粒子分类,以不同类别粒子的概率差值作为粒子滤波所需粒子数目是否足够的判断准则,自动调节不同情况下所需的粒子数目,并对不同类别粒子概率差值下盲多用户检测性能进行分析。仿真结果表明,该文算法可以在保证盲多用户检测性能的前提下有效地降低运算复杂度,且检测性能与概率差值成正比。     

短波衰落信道下Turbo均衡算法研究

短波衰落信道下由于多径和衰落的影响,接收机的解调性能严重恶化,甚至无法正常通信。针对短波信道的特性,阐述了现有的经典Turbo均衡算法与结构,对短波信道的变化情况进行了分析,并提出了Turbo均衡的简化算法,该算法基于最小均方误差准则,利用译码器的输出构造平均信息与方差信息,修正了信道循环矩阵从而使得计算复杂度大大降低。最后对其在衰落信道下的性能进行了仿真,仿真结果表明,提出的Turbo均衡简化算法既降低了复杂度,又不损失性能。     

场面信道特征重构的非视距多点定位性能研究

任何有关非视距(Non-Line-of-Sight,NLOS)的先验信息知识都可显著提高定位精度.基于国内某机场场面实际NLOS环境,借鉴移动通信和航空信道研究成果,建立了一种基于已知先验信息的、低空场面信道传输特征重构的多点定位信道模型.推导了入射波在高斯分布下的多普勒功率谱的解析式,得到信道中相对运动产生的频率扩散情况.对比了信道相关系数的实际值和理论值,来描述所建立信道的相关性.分析了不同天线配置下的信道容量,和先验知识比较对所建立的信道进行评估.仿真结果表明,所建立信道能够准确地描述出机场场面NLOS环境的特征,可用于多点定位系统设计和时间差定位算法的研究.     

基于粒子滤波和交互多模型的移动定位方法

为提高非视距情况下移动辐射源的定位精度,提出一种改进的交互粒子滤波算法.该算法对目标运动多模型和信号到达时间差测量噪声分布多模型联合建模.在交互多模型状态更新中利用粒子滤波对目标时变状态以及视距/非视距混合信道参数进行估计,抑制了非视距测量误差对移动定位的影响.仿真结果表明,改进算法的性能要优于现有的视距条件运动多模型和视距/非视距条件单一运动模型的定位算法,并且定位误差接近于推导的后验克拉美劳下界.     

Non-line of Sight Error Mitigation in Ultra-wideband Ranging Systems Using Biased Kalman Filtering

In this paper, a non-line of sight (NLOS) error mitigation method based on biased Kalman filtering for ultra-wideband (UWB) ranging is proposed. The NLOS effect on the measures of signal arrival time is considered one of the major error sources in range estimation and time-based wireless location systems. An improved biased Kalman filtering system, incorporated with sliding-window data smoothing and hypothesis test, is used for NLOS identification and error mitigation. Based on the results of hypothesis test, the estimated ranges are either calculated by smoothing the measured range when line of sight (LOS) status is detected, or obtained by conducting error mitigation on the NLOS corrupted measured range when NLOS status is detected. The effectiveness of the proposed scheme in mitigating errors during the LOS-to-NLOS and NLOS-to-LOS transitions is discussed. Improved NLOS identification and mitigation during the NLOS/LOS variations of channel status are attained by an adaptive variance-adjusting scheme in the biased filter. Simulation results show that the UWB channel status and the transition between NLOS and LOS can be identified promptly by the proposed scheme. The estimated time-based location metrics can be used for achieving higher accuracy in location estimation and target tracking.     

NLOS环境下移动台位置与速率估计

NLOS (Non-line of Sight)误差是定位中的主要误差来源,直接影响了定位的精度 。在MIMO（Multiple Input Multiple Output）系统中,基于NLOS信道模型的定位方法成为 解决NLOS定位误差问题的利器。基于此提出一种新颖的几何方法,仅采用两条NLOS路径就可 计算MS(Mobile Station)的位置,并且只需要利用单个基站便可完成MS的定位,克服了基站 数目过少无法准确定位MS的缺陷。在此基础上,还给出了最小二乘与最大似然算法利用多条 NLOS路径来改善定位精度的方法,并利用它对NLOS环境下运动的MS进行定位跟踪。理论分析 和仿真结 果都证明该定位方法在NLOS环境中对MS定位的有效性与精确度。     

严重遮挡非视距环境下的三维定位方法

在严重遮挡非视距环境中,由于定位源与未知节点之间被障碍物遮挡而无法检测直射路径,极大地制约了无线定位方法的应用。提出一种能够规避直射路径遮挡现象的三维定位框架,利用单次反射路径和方位信息,论证了定位源、未知节点和散射体的三维空间位置关系,提出了基于最小二乘准则的空间位置优化算法,并推导出空间位置的求解方法。同时对定位算法进行均方根误差（RMSE, root mean-square error）的理论分析。通过蒙特卡罗仿真实验分析了三维定位框架中距离和方位偏差对算法性能的影响,仿真结果与算法的RMSE理论结果相符,说明了三维非视距定位算法的有效性。     

Bootstrapping M-estimators for reducing errors due to non-line-of-sight (NLOS) propagation

Mobile positioning is made difficult by nonsymmetric contamination of measured time-of-arrival (TOA) data caused by non-line-of-sight (NLOS) propagation. In this letter, a robust NLOS error mitigation algorithm based on Bootstrapping M-estimation is proposed without prior NLOS error distribution. A simulation comparison is performed in different channel environments between the proposed algorithm and two additional ones (least-square and Huber estimator). The proposed algorithm clearly outperforms the other two.     

A minimum entropy estimation based mobile positioning algorithm

The problem of locating a mobile terminal has received significant attention in the field of wireless communications. The wireless location problem is made difficult by nonsymmetric contamination of measured Time of Arrival (TOA) data caused by Non-Line-Of-Sight (NLOS) propagation. In this paper, a novel robust NLOS error mitigation algorithm based on minimum entropy estimation is proposed without prior statistics knowledge of NLOS propagation error.We compare the proposed algorithm with two additional ones, the Normal Least-Squares estimator and the Huber estimator, through MATLAB simulation in different COST 259 channel environment. Results reveal that the proposed algorithm is more robust to NLOS error than the other two, although it is not always superior to the other two on location accuracy.     

Harris Hawk Optimization Algorithm‐based Effective Localization of Non‐Line‐of‐Sight Nodes for Reliable Data Dissemination in Vehicular Ad hoc Networks

Vehicular Ad hoc NETwork (VANET) is considered as the appropriate candidate for provisioning risk‐free environment that confirms secure cooperation and very minimal congestion among the vehicular nodes in the network. The establishment and maintenance of connectivity between vehicular nodes are determined to be influenced by the existence of Non‐Line‐of‐Sight (NLOS) nodes that introduce channel congestion and broadcasting storm into the network during emergency message delivery. Thus, NLOS nodes need to be localized with optimality for enhancing the emergency data delivery rate with minimized latency degree and energy consumption in the network. In this paper, Harris Hawk Optimization Algorithm (HHOA)‐based NLOS nodes Localization Scheme (NLOS‐LS) (HHOA‐NLOS‐LS) is proposed for facilitating reliable data dissemination among vehicular nodes under emergency situations. HHOA utilizes chasing styles and cooperative behavior of Harris hawks termed as surprise pounce for efficient localization based on reference nodes. In particular, the intelligent strategy of Harris hawks' behavior in attacking the prey in all directions is included for localizing the NLOS nodes from the reference nodes positioned in all directions of the network. It is capable of localizing the NLOS nodes based on adaptive localizing (chasing) styles attained through reference nodes dependingon the dynamic nature of NLOS nodes. The simulation results prove that the mean localization rate is improved by 23.21%, mean neighborhood awareness rate by 19.82%, mean emergency message delivery rate by 18.32% and mean channel utilization by 17.28% when compared to the baseline Weighted Inertia‐based Dynamic Virtual Bat Algorithm (WIDVBA)‐based NLOS‐LS (WIDVBA‐NLOS‐LS), Cooperative Volunteer Vehicular Nodes (CVVN)‐based NLOS‐LS (CVVN‐NLOS‐LS), Vote Selection Mechanisms and Probabilistic Data Association (VSMPDA)‐based NLOS‐LS (VSMPDA‐NLOS‐LS), and Weighted Distance Hyperbolic Prediction (WDHP)‐based NLOS‐LS (WDHP‐NLOS‐LS) for a varying number of vehicular nodes in the network.     

Hybrid seagull and thermal exchange optimization algorithm‐based NLOS nodes detection technique for enhancing reliability under data dissemination in VANETs

The reliability of data dissemination in vehicular ad hoc network (VANET) necessitates maximized cooperation between the vehicular nodes and the least degree of congestion. However, non‐line of sight (NLOS) nodes prevent the establishment and sustenance of connectivity between the vehicular nodes. In this paper, a hybrid seagull and thermal exchange optimization (TEO) algorithm‐based NLOS node detection technique is proposed for enhancing cooperative data dissemination in VANETs. It inherits three different versions of the proposed hybridized algorithm; three different approaches for localization of NLOS nodes depending upon its distance from the reference nodes are incorporated. It is considered as a reliable attempt in effective NLOS node localization as it is predominant in maintaining the balancing the degree of exploration and exploitation in the search process. In the first variant, the method of the roulette wheel is utilized for selecting one among the two optimization algorithm. In the second adoption, this hybridization algorithm combines TEO algorithm only after the iteration of SEOA algorithm. In the final adoption, the predominance of the seagull attack mode is enhanced by including the heat exchange formula of TEO algorithms for improving exploitation capability. The simulation experiments of the proposed HS‐TEO‐NLOS‐ND scheme conducted using EstiNet 8.1 exhibited its reliability in improving the emergency message delivery rate by 14.86%, a neighborhood awareness rate by 13%, and the channel utilization rate by 11.24%, compared to the benchmarked techniques under the evaluation done with different number of vehicular nodes and NLOS nodes in the network.