基于免疫算法的Hopfield神经网络多用户检测器

提出的基于免疫算法的Hopfield神经网络多用户检测器，将扰乱的Hopfield神经网络多用户检测器的输出作为免疫算法的初始种群，利用了免疫算法的全局收敛的特点，从而克服了Hopfield易收敛到局部能量最小点的缺点。理论分析和仿真结果表明：该检测器具有良好的抗多址干扰和抗远近效应的能力。     

基于免疫算法的智能多用户检测技术在CDMA中的应用

多用户检测技术是第3代移动通信系统CDMA中的一项关键技术.在多用户检测器中求解最佳矢量的问题可以转化为在免疫算法中求解具有最高适应度抗体的问题.文中用免疫算法来解决CDMA中的多用户检测问题.通过性能分析和计算机仿真,并与最佳多用户检测器和传统检测器相比较,发现基于免疫算法的多用户检测技术能较好地实现多用户检测的功能,这是一种切实可行的方案.     

一种基于免疫系统的RBF网络在线训练方法

 针对径向基函数(RBF)网络和免疫系统的相似性,本文提出了一种基于免疫模型的RBF网络在线学习方法以解决动态问题.该方法借鉴了免疫系统动态调整以对抗不断入侵的抗原的机制,通过免疫初步覆盖、免疫交叉响应和疫苗注射等免疫操作,加速算法效率、提高算法精度和动态性能.通过以上操作使得RBF网络能够根据样本的变化迅速地调整网络结构与参数.计算机仿真研究表明,采用这种方法设计的RBF网络在动态环境下具有优良的精度和泛化能力.     

采用Rao-Blackwellised粒子滤波的时变多用户检测

传统多用户检测方法通常假定接收方已知活跃用户数,其一般为这个系统所能容纳的最大用户个数.在此前提下,传统多用户检测方法能够获得较好的性能.然而在实际多址移动通信系统中活跃用户个数及其参数往往都是时变的,因此传统多用户检测方法性能恶化.针对这个问题,本文首先采用随机集理论( Random Set Theory,RST)建立多用户动态模型,基于此模型将信道分解为离散部分和连续部分,并通过分析两者的关系得到它们的状态转移概率;然后提出了采用Rao-Blackwellised粒子滤波(RBPF)算法的时变多用户检测器,实现了活跃用户数目变化和信道幅度变化的跟踪及用户发送数据估计;最后给出了算法在抗噪声能力、抗远近效应和系统容量等方面的仿真结果.仿真结果表明本文算法性能明显优于传统多用户检测方法.     

平坦瑞利衰落信道中多用户检测器的性能分析

在采用传统信号检测方式的CDMA系统中,多址干扰限制了系统的容量和性能.本文分析了在精确估计信道的情况下平坦瑞利衰落信道中的判决反馈和线性解相关两种多用户检测器的性能,主要分析了二者的误码率性能和抗远近效应的能力,并首次分析了衰落信道中的渐近多用户效率(AME).结果表明,判决反馈多用户检测器的渐近多用户效率优于线性解相关检测器.     

一种神经网络多用户检测器

本文提出采用Ｈｏｐｆｉｅｌｄ神经网络实现ＣＤＭＡ多用户通信系统中多用户信号的检测。利用基于检测序列最大后验概率最佳多用户检测器的似然函数与Ｈｏｐｆｉｅｌｄ神经网络的能量函数的对应关系,构造一种离散Ｈｏｐｆｉｅｌｄ神经网络多用户检测器。研究表明,这种多用户检测器具有优良的性能,其计算复杂度低于最佳多用户检测器、抑制多址干扰和克服远近效应能力又大大优于传统检测器。     

一种新的盲空时多用户检测器

多用户检测是DS-CDMA系统中的一项关键技术,而阵列天线也是一项减轻多用户干扰的方法.许多现存的多用户检测器需要知道很多系统参数,并且其自适应实现需要发送训练序列.在多径衰落信道下,这些参数是很难获得的.本文提出了一种新的基于Kalman滤波的盲空时多用户检测器(BSTKAL),这种多用户检测器不需要发送训练序列.研究结果表明,检测器具有较强的抑制多址干扰和克服"远-近"效应的能力,并且能快速收敛.     

移动通信中的多用户检测技术

对移动通信中的多用户检测技术进行了探讨,介绍了最初的最优和次最优多用户检测器,现代的各种多用户检测技术以及传统的多用户检测器的最新实现算法,并就多用户检测与其它技术的结合作了深入的研究.     

RBF神经网络CDMA多用户检测方法

分析了采用正交最小二乘(OLS)算法的RBF神经网络应用于DS-CDMA扩频通信的多用户检测的问题,给出了基于RBF网络进行多用户检测的理论依据和仿真分析性能。     

基于自适应子波网络的多用户检测

本文将子波网络用于实现DS-CDMA系统信道中多用户的信号检测.在实际中,当存在强干扰信号时传统检测器(单用户匹配滤波器)的性能会急剧恶化.本文基于MMSE(Minimum Mean-Square Error)线性检测器原理,利用自适应子波网络实现最小均方误差准则的优化,较好地消除了多址干扰.仿真结果表明,基于子波网络的多用户检测器可以快速收敛,并具有抗远近性.     

一种基于MOE的盲自适应的多用户检测器

盲自适应多用户检测器由于既能实时跟踪信道信息及用户信息,又不需要发送训练序列而成为研究的热点,但一般的盲自适应多用户检测技术存在收敛速度慢的弱点。提出一种基于MOE(最小输出能量)的盲自适应多用户检测器,通过合理地选取时变步长,可有效地提高多用户检测器的收敛速度,从而提高系统的性能。     

An Adaline Neural Network-Based Multi-User Detector Improved by Particle Swarm Optimization in CDMA Systems

The detector applied to each single user based on adaline neural network (ANN) is presented in this paper, which is equivalent to the joint one applied to all users in eliminating the multiple access interference in CDMA systems. Then, particle swarm optimization (PSO) algorithm combined with least mean square scheme is employed in the training procedure of the ANN, which can effectively remove the shortcoming of the poor dynamic adaptive behavior of conventional neural network, i.e. during the convergence procedure of the weights in conventional neural network, the training samples are usually required to be trained iteratively. However, in the improved detector, each training sample can be trained repeatedly, so that the converging speed is getting much faster. Simulation results show that, in the ANN based multi-user detector improved by PSO, the dynamic adaptive behavior has been remarkably improved.     

Blind adaptive multiuser detector for nonlinearly modulated satellite mobile CDMA systems

This paper presents a novel blind adaptive noncoherent decorrelative multiuser detector for nonlinearly modulated satellite mobile Code Division Multiple Access （CDMA） systems. By using the known signature waveforms of the counterpart earth station in the blind adaptive multiuser detector, the system performance has been improved obviously. The computation results about the convergence properties of the new detector and the previous detectors demonstrate that the proposed multiuser detector has better performance than previous multiuser detectors for nonlinearly modulated CDMA systems.     

基于免疫克隆量子算法的多用户检测器

为了解决CDMA系统最佳多用户检测的高计算复杂度问题,基于免疫克隆选择理论和新的遗传量子算法,该文提出了免疫克隆量子算法。该算法把根据神经网络制作的疫苗接种到克隆量子算法的每一代中,通过接种疫苗到CQA中,可以加快CQA的收敛速度减少计算复杂度。另外,CQA所提供的好的初值可以改善疫苗的性能,接种的疫苗还改善了CQA的性能,文中给出了在免疫克隆量子算法中使用随机神经网络制作疫苗的统一理论框架结构。仿真结果证明了该方法不仅能够快速收敛到全局最优解,并且无论抗多址干扰能力和抗远近效应能力都优于传统检测器和一些应用以前智能计算算法的多用户检测器。     

混合粒子群优化算法在CDMA系统多用户检测中的应用

针对粒子群优化算法易早熟的问题,提出了一种混合粒子群优化算法(HPSO)。首先在算法中采用惯性权重的分段递减策略,以提高算法的全局搜索能力;然后在算法后期,引入拉伸技术剔除比局部极值大的点,缩小搜索空间,使算法能及时跳出局部最优从而加速收敛,最后提出了基于HPSO算法的多用户检测器。仿真结果表明在信噪比相同的条件下,该多用户检测器的误码率和抗远近效应性能更接近于最佳多用户检测器,有效解决了码分多址通信系统中的多址干扰问题。     

Blind adaptive energy estimation for decorrelatingdecision-feedback CDMA multiuser detection using learning-typestochastic approximations

This paper investigates the application of linear reinforcement learning stochastic approximation to the blind adaptive energy estimation for a decorrelating decision-feedback (DDF) multiuser detector over synchronous code-division multiple-access (CDMA) radio channels in the presence of multiple-access interference (MAI) and additive Gaussian noise. The decision-feedback incorporated into the structure of a linear decorrelating detector is able to significantly improve the weaker users' performance by cancelling the MAI from the stronger users. However, the DDF receiver requires the knowledge of the received energies. In this paper, a new novel blind estimation mechanism is proposed to estimate all the users' energies using a stochastic approximation algorithm without training data. In order to increase the convergence speed of the energy estimation, a linear reinforcement learning technique is conducted to accelerate the stochastic approximation algorithms. Results show that our blind adaptation mechanism is able to accurately estimate all the users' energies even if the users of the DDF detector are not ranked properly. After performing the blind energy estimation and then reordering the users in a nonincreasing order, numerical simulations show that the DDF detector for the weakest user performs closely to the maximum likelihood detector, whose complexity grows exponentially with the number of users     

平坦瑞利衰落环境下CDMA系统的多用户检测性能

在采用传统信号检测方式的CDMA无线通信网中,多址干扰限制了系统的容量和性能。多用户信号检测利用扩频码互相关信息在高斯信道中可以减小或消除多址干扰,缓解远近效应,增加系统容量。本文将多用户检测器直接用于平坦瑞利衰落的CDMA环境中,用分析与仿真相结合的方法讨论了典型多用户算法的误码性能。结果表明,平坦瑞利衰落信道中多用户检测算法的性能仍然优于传统检测算法。     

PERFORMANCE OF MULTIUSER DETECTION FOR CDMA SYSTEM IN A FLAT RAYLEIGH FADING ENVIRONMENT

In a CDMA communication network using conventional signal detection, system capacity is limited and its performance is degraded by the multi-access interference (MAI). Multiuser detection, which makes use of cross-correlation information between spread spectrum codes, can reduce or eliminate the MAI in a Gaussian channel so as to mitigate the near-far effects and increase the system capacity. This paper extends the multiuser detector to a flat Rayleigh fading CDMA environment, and discusses the bit error rate of typical multiuser detection algorithms in such a environment by combining theoretical analysis and computer simulation. It is shown that multiuser detection is superior to conventional detections in the flat Rayleigh fading channels.     

Population Declining Ant Colony Optimization Multiuser Detection in Asynchronous CDMA Communications

In this paper we present a population declining ant colony optimization (PDACO) multiuser detector for asynchronous CDMA communications. Ant colony optimization (ACO) algorithms have already been used in multiuser detection in CDMA systems; however, as the pheromone accumulates, we may not get a global optimum because it stops searching early. PDACO can enlarge searching range through increasing the initial population of the ant colony, and the population declines in successive iterations. So, the performance of PDACO is superior with the same computational complexity. PDACO is applied to multiuser detection in asynchronous CDMA systems over slowly multipath Rayleigh-fading channels in this paper. Via computer simulations it is shown that the performance of PDACO detector is much better in bit-error rate and near-far effect resistance than conventional detector, ACO detector and genetic algorithm detector, and is close the optimal multiuser detector.     

Receiver Design for Uplink Multiuser Code Division Multiple Access Communication System Based on Neural Network

In this paper, we consider the receiver design problem for the uplink multiuser code division multiple access (CDMA) communication system based on the neural network technique. The uplink multiuser CDMA communication system model is described in the form of space–time domain through antenna array and multipath fading expression. Novel suitable neural network technique is proposed as an effective signal processing method for the receiver of such an uplink multiuser CDMA system. By the appropriate choice of the channel state information for the neural network parameters, the neural network can collectively resolve the effects of both the inter-symbol interference due to the multipath fading channel and the multiple access interference in the receiver of the uplink multiuser CDMA communication system. The dynamics of the proposed neural network receiver for the uplink multiuser CDMA communication system is also studied.