MC-CDMA系统迭代检测中的均衡

本文研究在同步MC- CDMA系统中的上行链路中的均衡技术。接收机采用多用户检测和译码相结合的迭代检测技术;其中,串行干扰消除用于多用户检测,一个SISO译码器用于信道译码。仿真给出在不同的均衡策略下如ORC、EGC、MRC、MMSE,迭代检测接收机的性能     

DS/CDMA同步信道中的多用户联合检测和译码

将迭代(Turbo)处理的思想应用于DS/CDMA系统同步信道的多用户检测和译码中,接收机利用信道译码的先验信息进行多用户前端处理,而其输出又作为信道译码器软输入,从而使多用户检测和信道译码联合进行,通过迭代逐渐逼近单用户性能,减少多址干扰的影响。仿真结果给出了迭代处理方法在不同信噪比条件下的比特误码率性能。     

基于解相关判决反馈检测的迭代多用户接收器

提出了一种基于解相关判决反馈检测的迭代多用户接收器,它同时实现多用户检测,信道译码和信道参数估计,数据检测、译码与参数估计相辅相成。随着迭代次数的增加,比特误码率减低;同时,参数估计值也趋于最优值。     

Turbo译码原理及其在CDMA多用户检测中的应用

研究了Turbo(并行级联码)译码原理及其在CDMA多用户检测中的应用。文中简述了Turbo译码原理及逐符号最大后验算法(symbol-by-symbol MAP),并将Turbo译码原理应用于CDMA系统的多用户检测,提出了基于Turbo译码原理的多用户检测接收机方案,通过计算机仿真验证该方案的性能。结果表明,本文所提出的方案经过4次迭代之后,其误码率接近单用户界,说明这种接收机可去除多址干扰(MAI)的影响。     

MC-CDMA系统迭代检测中的一种信道估计算法

在DS—CDMA系统中，联合译码的迭代多用户检测是克服多址干扰增加系统容量的有效方法。本文将多用户检测和译码相结合的迭代检测技术应用于MC—CDMA系统，其中，多用户检测器由串行干扰消除和其后的MMSE滤波器组成。文中提出一种时域信道估计作为迭代初始值的频域信道估计算法，比单纯的频域信道估计方法节约导频符号数量，并且由于信道估计性能的改善，加快了迭代检测的收敛速度。     

Turbo MUD技术在TD-SCDMA系统中的应用

TD-SCDMA已成为第3代移动通信国际标准之一,它采用联合检测技术来抑制符号间干扰(ISI)和多址干扰(MAI)。介绍了Turbo多用户检测(MUD)技术在TD-SCDMA系统中的应用,该技术将Turbo迭代译码思想引入到联合检测,有机结合多用户检测和信道译码2种技术,通过在软MUD和软信道译码间多次进行迭代并及时交换软信息(如后验概率)来提高系统性能。研究表明,采用TurboMUD可使系统性能显著提高。     

编码的多载波CDMA系统中Turbo时空多用户检测

联合MAP多用户检测和信道译码的迭代多用户检测技术可显著提高多载波CDMA系统的容量和性能,本文给出了结合智能天线和迭代MAP多用户检测的Turbo时空多用户检测算法,该方法进一步提高了系统的性能.Turbo时空多用户检测算法不仅极大减小了传统最优MAP多用户检测算法的运算量,而且,此算法性能在AWGN和频率选择性衰落信道中都能逼近单用户编码多载波CDMA系统多天线接收的性能.     

一种低复杂度的Turbo多用户检测技术

基于Turbo原理,提出了一种适合于同步DS－CDMA系统的迭代多用户接收机结构,它通过在反复迭代的软输入出多用户检测器和一组信道译码之间获得连续的软判决,从而得到一种低复杂度的多用户检测算法－软MMSE干扰消除。     

快跳频多址通信多级迭代干扰消除多用户检测

提出了多级迭代干扰消除快跳频多址多用户检测算法。首先使用传统检测器检测,对只有一个最大行的用户做出正确译码,对相应时频矩阵元素进行信干噪声功率比估计,确定干扰消除迭代权值,然后,对干扰元素做加权运算,逐渐消除干扰,直到所有用户译码完成。该算法消除了迭代中权值估计带来的误差,计算量同用户数成线性关系。仿真结果表明：提出的多级迭代干扰消除算法性能优于文献中的多用户检测算法,特别是在用户数较多时性能有较明显改善。     

MC-CDMA系统迭代检测中的一种基于EM的信道估计算法

该文将多用户检测和译码相结合的迭代检测技术应用于MC-CDMA系统。多用户检测器由串行干扰消除和其后的MMSE滤波器组成。信道估计器采用一种基于期望最大(EM)信道估计算法,该算法降低了信道估计的复杂度,仿真表明其具有良好的性能。     

Iterative multi-user detection and decoding for space-time block coding systems

1 Introduction Recently space–time coding (STC) techniques [1] are designed to combat fading in wireless links by utilizing multiple antenna systems, in which transmit diversity and coding gains can be exploited without sacrificing additional power and b…     

Turbo编码STBC系统中削弱误差传播的迭代多用户检测技术

空时编码(STC)技术将天线阵列信号处理和信道编码技术联合起来实现无线信道容量的有效增加。为了抑制空时分组编码(STBC)系统的共道用户干扰,对低复杂度的多用户检测算法进行研究,该文提出了一种STBC系统的迭代(turbo)多用户接收机。该接收机由一个软入软出(SISO)基于均值的软判决多用户检测器(Soft Decision Multi-User Detector, SDMUD)和一组SISO Turbo信道解码器构成。两者之间通过迭代交换外信息,精确地估计用户信号。仿真结果表明这种接收技术经3次迭代后性能改善约2dB,并且系统性能会随着接收天线的增多而得到明显提高,从而大大增加系统容量。     

Turbo Decoding and Detection for Wireless Applications

A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon's visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon's capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated space-time and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted.     

同步CDMA系统中多步迭代多用户检测技术

同时考虑系统性能和运算量，将多步联合检测和迭代多用户检测技术结合起来，提出了多步迭代多用户检测技术。相对于单纯的MSJD，系统性能将大大提高；相对于单纯的迭代多用户检测，运算量将大大减少。     

Comparative study of turbo decoding techniques: an overview

We provide an overview of the novel class of channel codes referred to as turbo codes, which have been shown to be capable of performing close to the Shannon limit. We commence with a discussion on turbo encoding, and then move on to describing the form of the iterative decoder most commonly used to decode turbo codes. We then elaborate on various decoding algorithms that can be used in an iterative decoder, and give an example of the operation of such a decoder using the so-called soft output Viterbi (1996) algorithm (SOVA). Lastly, the effect of a range of system parameters is investigated in a systematic fashion, in order to gauge their performance ramifications     

Achieving near-capacity on a multiple-antenna channel

Recent advancements in iterative processing of channel codes and the development of turbo codes have allowed the communications industry to achieve near-capacity on a single-antenna Gaussian or fading channel with low complexity. We show how these iterative techniques can also be used to achieve near-capacity on a multiple-antenna system where the receiver knows the channel. Combining iterative processing with multiple-antenna channels is particularly challenging because the channel capacities can be a factor of ten or more higher than their single-antenna counterparts. Using a "list" version of the sphere decoder, we provide a simple method to iteratively detect and decode any linear space-time mapping combined with any channel code that can be decoded using so-called "soft" inputs and outputs. We exemplify our technique by directly transmitting symbols that are coded with a channel code; we show that iterative processing with even this simple scheme can achieve near-capacity. We consider both simple convolutional and powerful turbo channel codes and show that excellent performance at very high data rates can be attained with either. We compare our simulation results with Shannon capacity limits for ergodic multiple-antenna channel.     

The super-trellis structure of turbo codes

In this contribution we derive the super-trellis structure of turbo codes. We show that this structure and its associated decoding complexity depend strongly on the interleaver applied in the turbo encoder. We provide upper bounds for the super-trellis complexity. Turbo codes are usually decoded by an iterative decoding algorithm, which is suboptimum. Applying the super-trellis structure, we can optimally decode simple turbo codes and compare the associated bit-error rate results to those of iterative algorithms     

Efficient SIC-MMSE MIMO detection with three iterative loops

In this paper, we propose an efficient joint iterative detection and decoding (JIDD) scheme with a soft interference cancellation minimum mean squared error (SIC-MMSE) based method for a turbo coded multiple-input multiple-output (MIMO) system. In the proposed method, we activate a loop inside the SIC-MMSE based MIMO detection process in addition to the iterative loop between the MIMO detector and turbo decoder, so that the iteration inside the SIC-MMSE detection can be performed in parallel to the iterations inside the turbo decoder. Subsequently, soft outputs from each loop is exchanged for next further iteration, and this makes three iterative loops in total. In comparison with the conventional JIDD schemes, employing additional loop inside the MIMO detection process largely contributes to enhance the performance. In addition, the additional loop speeds up the performance convergence and eventually requires smaller overall computational complexity at the same performance.     

The iterative turbo decoding algorithm has fixed points

It is shown that the iterative decoding algorithm proposed to decode “turbo codes” has fixed points regardless of the specific constituent codes and regardless of the noise variance of the additive white Gaussian noise (AWGN) channel     

一种适用于空分复用MIMO系统的迭代检测器

本文在比特交织turbo编码调制的空分复用M IMO系统发送框架下,研究了一类与Turbo码的迭代译码联合进行的软干扰抵消迭代检测算法。在首次检测中,使用了基于匹配滤波(M F)的多级串行软干扰抵消方法,在后续的检测中使用了单级并行软干扰抵消方法。本文又把迭代检测同turbo码的迭代译码联合,大大降低了每次联合检测turbo译码需要的迭代译码次数。