MISO-CDMA多径系统中空时分组码的译码方法

空时编码是实现宽带无线数据通信和下一代移动通信系统的一种极有潜力的技术。为有效的将空时分组码应用到多径衰落环境下的码分多址系统，以充分利用多个路径的信号能量，现提出了一种多径环境下空时分组译码的新方法。由于空时分组码译码与信道估计紧密相关，为此本文对多径信道估计以及信道估计误差对本方法产生的影响作研究。仿真结果表明，采用多路径译码方法可以明显提高系统的误码性能。     

空时分组码与线性分组码相结合的MIMO系统

空时分组码能够实现MIMO系统的完全发射分集，但不能实现任何的编码增益。对此，提出了线性分组码与空时分组码级联的MIMO系统，该系统能够同时实现完全发射分集和编码增益。仿真结果表明，在比特误码率为10^-5时，与未进行前向纠错的空时分组码系统相比，该系统能提供了大约2．7dB的编码增益。     

空时分组码与线性分组码相结合的

空时分组码能够实现MIMO系统的完全发射分集,但不能实现任何的编码增益.对此,提出了线性分组码与空时分组码级联的MIMO系统,该系统能够同时实现完全发射分集和编码增益.仿真结果表明,在比特误码率为10-5时,与未进行前向纠错的空时分组码系统相比,该系统能提供了大约2.7dB的编码增益.     

基于差分空时分组码的OFDM系统的性能分析

本文介绍了差分空时分组码的编译码原理,研究了采用差分空时分组码的OFDM系统（DSTBC-OFDM）性能,仿真结果表明,DSTBC-OFDM系统的性能随着子载波数及子信道数的增加而提高。通过仿真,还证明了多天线技术与OFDM技术相结合,系统性能可得到提高,更适用于多径无线信道,而且采用差分编码技术,接收端不需要信道估计,可以大大降低接收机的复杂度。     

短波单载波空时分组码的频域均衡研究

短波通信受多径衰落、干扰复杂等影响严重。空时分组码(Space Time Block Code,STBC)技术在无需增加频谱资源和天线发射功率的前提下,可以利用多输入多输出(Multiple-Input Multiple-Output,MIMO)信道提供的分集增益提升传输可靠性。分析短波MIMO研究现状,提出短波单载波STBC频域均衡(Frequency-Domain Equalization,FDE)系统架构,针对短波信道引入的码间干扰研究MIMO MMSE-FDE均衡技术,并将单载波STBC频域均衡与时域均衡及短波现有波形进行仿真对比。仿真结果表明,相较于短波现有波形,单载波STBC频域均衡系统的可靠性有较大幅度提升,且性能与STBC时域均衡接近,但计算复杂度远低于STBC时域均衡。     

无线通信中的空时分组码

空时分组码技术结合信道编码、调制和天线分集技术,当发送天线一定时,他的解码复杂度正比于发送速率,在3G标准中,该技术有着重要的地位。对空时分组码及相关知识进行了介绍,并对可变速率的空时分组码设计进行了探讨,最后展望了空时分组码技术的应用前景。     

并行分离的高速空时分组码设计方法

为了提高空时分组码的编码速率,文中提出了一种基于发射端编码符号混淆、接收端多天线并行分离的高速空时分组码的设计方法.该方法可以提供很高的编码速率,适用于任意数量的发射天线.仿真分析结果表明文中提出的方法在相同有效吞吐容量下比1/2编码速率的空时分组码有6dB的性能增益.     

两种闭环准正交空时分组码的设计

针对准正交空时分组码(QOSTBC)存在自干扰的特性,提出了两种基于部分反馈的闭环QOSTBC的设计方法,这两种反馈方法可以减小QOSTBC的自干扰,提高QOSTBC的误码性能。仿真和分析结果表明提出的方法在相同反馈信息下的性能优于天线混淆(TAS)准正交空时分组码,在系统性能相差不大(不超过0.5dB)的情况下所需的反馈信息远小于信道正交化空时分组码(CO-STBC),而且提出的方法具有较低的设备复杂性和较好的鲁棒性。     

空时分组码MC-CDMA系统多用户检测

本文研究了在频率选择性瑞利衰落信道中工作于时分双工(TDD)模式的多载波码分多址(MC-CDMA)系统上行链路,在用户终端处使用两个发射天线,采用基于空时分组码的发射分集。考虑对应于子载波的衰落系数是信道冲激响应的离散傅里叶变换,给出了基于空时分组码的MC-CDMA系统上行链路信号模型。采用适用于同步CDMA系统的低代价Steiner估计器来进行基于空时分组码的MC-CDMA系统的信道估计,每个用户终端的两个发射天线各分配一个midamble。研究了基于空时分组码的MC-CDMA系统的解相关多用户检测、最小均方误差(MMSE)多用户检测,进行联合的多用户检测和空时码解码。仿真结果验证了上述模型及算法的有效性。     

空时分组码参数分析

在协议未知的条件下仅根据接收信号分析得到空时码的参数是MIMO系统盲接收中的重要技术.基于此应用背景对空时分组码的编码模型和接收信号模型进行研究,发现接收信号协方差矩阵的秩与空时分组码参数之间的关系,并由此利用随机矩阵理论的中噪声子空间最大特征值的概率分布求出信号协方差矩阵的秩,进而估得空时码参数.仿真结果表明,算法在未知码集的条件下不仅能够估计出空时分组码的码参数,还能够确定空时分组码的码块起点.     

基于空时分组编码的协同通信系统性能的研究

该文提出了一种基于空时分组编码的协同通信方案(WCC-STBC),通过理论分析得到了系统的误码率传输特性,并给出了Monte Carlo仿真结果。理论分析和仿真结果表明：WCC-STBC方案通过临近用户之间的空时协同发送可获得分集增益,增益的大小与协同信道及各用户信道的传输特性有关。在误比特率为10-3,两用户间协同信道的传输特性优于各用户(假设各用户传输特性相同)5dB时可获得约3dB的分集增益;一个用户信道的传输特性(假设其与两用户间协同信道传输特性相同)优于另一用户5dB时,信道传输特性较差的用户可获得约5dB的性能提升,且较好信道用户的性能损失并不大,仅约0.5dB。     

Channel Estimation by Using Short Training Sequences in CDMA Systems

Multiuser detection techniques are known to be effective to counter the presence of multiuser interference in code division multiple access channels. Multiuser detectors can provide excellent performance only when the channel impulse responses of all the users are precisely known. Hence, channel estimation becomes a challenging issue in mobile communication systems. In this paper, we address the problem of efficient maximum likelihood mobile radio channel estimation at high channel efficiency that requires a short training sequence along with the known spreading sequence. The proposed system can be employed in both the uplink and downlink of a heavily loaded multiuser CDMA system. The extension of the approach with unknown users' delays are also proposed. We present results that show the success of this method in recovering the transmitted bits with a relatively small number of preamble bits. Ahmet Rizaner was born in Larnaca, Cyprus, on January 31, 1974. He received the B.S. and M.S. degrees in Electrical and Electronics Engineering from the Eastern Mediterranean University, Famagusta, North Cyprus, in 1996 and 1998, respectively. He completed his PhD. degree in Electrical and Electronic Engineering in Eastern Mediterranean University and joined Eastern Mediterranean University as a lecturer in 2004. He is lecturing in the School of Computing and Technology. His main research interests include CDMA communications, adaptive channel estimation, and multiuser detection techniques. Hasan Amca was born in 1961 in Nicosia-Cyprus. He graduated from the Higher Technological Institute in Magosa-Cyprus (which is renamed later as Eastern Mediterranean University). He joined EMU in 1985 after receiving a M.Sc. (Digital Signal Processing) degree from the University of Essex in England (1985). He took his Ph.D. (Mobile Communications) from the University of Bradford where he was on a Commonwealth scholarship. He has been teaching in the Electrical and Electronic Engineering Department of Eastern Mediterranean University since 1993 where he also served as the vice chairman from Spring 1998 to Spring 2000. He has been appointed as the Director of the School of Computing and Technology of the EMU since Spring 2000. His research interests include Multi User Detection of CDMA signals, Adaptive Equalisation, Multi Carrier Systems, Mobile Radio Systems and Networks, Internet and Information Technology Applications in Education. Kadri Hacıoğlu was born in Nicosia, Cyprus. He received the B.Sc., M.Sc., and Ph.D. degrees in electrical and electronic engineering from the Middle East Technical University, Ankara, Turkey, in 1980, 1984, and 1990, respectively. After his two-year military service, in 1992, he joined the faculty of Eastern Mediterranean University, Magosa, North Cyprus, as an Assistant Professor, and became an Associate Professor in 1997. While there, he taught several classes on electronics, digital communications, speech processing and neural networks. During this time, he conducted research on applying fuzzy logic, neural networks, and genetic algorithms to signal processing and communications problems. From 1998 to 2000, he was a Visiting Professor in the Department of Computer Science, University of Colorado, Boulder. Here, he taught classes on neural networks and continued his research. Since 2000, he has been a Research Associate at the Center for Spoken Language Research, University of Colorado. He has authored or coauthored numerous papers and supervised a dozen M.Sc./Ph.D. theses. His current research interests are concept-based language modeling, speech understanding, natural language generation, and search methods in speech recognition/understanding. He also does research on multiuser detection and equalization in CDMA systems. Ali Hakan Ulusoy was born in Eskişehir, Turkey, on June 3, 1974. He graduated from the double major program of the department of Electrical and Electronic Engineering and department of Physics in Eastern Mediterranean University as the first rank student of Faculty of Engineering in 1996. He received his M.S. degree in Electrical and Electronic Engineering in Eastern Mediterranean University in 1998. He completed his PhD. degree in Electrical and Electronic Engineering in Eastern Mediterranean University and joined Eastern Mediterranean University as a lecturer in 2004. He is lecturing in the School of Computing and Technology. His current research interests include receiver design, multi-user detection techniques, blind and trained channel estimation in Code Division Multiple Access (CDMA).     

一种基于空时分组编码的MIMO-OFDM系统接收空间分集方案

文献[1]提出了一种使用正交设计的单输入多输出正交频分复用(SIMO-OFDM)系统的空间分集接收结构,目的是为了减少接收端DFT块的数目以降低系统复杂度和减少功率消耗。由于在线性处理过程中噪声叠加的影响,造成了一定的性能损失。本文提出了一种基于空时分组编码的多输入多输出OFDM(MIMO-OFDM)系统空间分集接收方案,通过在文献[1]提出的分集结构中引入使用空时分组编码的发射分集,弥补了因减少DFT块数目而造成的性能损失。本文对使用空时分组编码后的处理过程进行了推导,并对使用空时编码前后的系统性能进行了仿真和比较。     

Effect Investigation of Channel Estimation Deviation on STBC Performance in CDMA System

1　Introduction　Inrecentyears ,Space Timecode (STC) [3,8～ 11] hasattractedmuchattentionfrommanyscholarsinthefieldofwirelesscommunicationsasaneffectivetransmitdi versitytechniquecombatingfadinginwirelesscommuni cations.SpaceTimeBlockCode (STBC) [3] ,whichisproposedbyS .M .Alamoutiin 1998asasub optimaltransmitdiversitytechnique ,canobtain gainthroughemployingtwoantennasattransmitend .However,STBChastheassumptionofflatfadingchannelcondi tionthatlimitsitsuseonbroadbandwirelesscommuni cat…     

Complexity Reduction in SISO Decoding of Block Codes

SISO decoding for block codes can be carried out based on a trellis representation of the code. However, the complexity entailed by such decoding is most often prohibitive and thus prevents practical implementation. This paper examines a new decoding scheme based on the soft-output Viterbi algorithm (SOVA) applied to a sectionalized trellis for linear block codes. The computational complexities of the new SOVA decoder and of the conventional SOVA decoder, based on a bit-level trellis, are theoretically analyzed and derived for different linear block codes. These results are used to obtain optimum sectionalizations of a trellis for SOVA. For comparisons, the optimum sectionalizations for Maximum A Posteriori (MAP) and Maximum Logarithm MAP (Max-Log-MAP) algorithms, and their corresponding computational complexities are included. The results confirm that the new SOVA decoder is the most computationally efficient SISO decoder, in comparisons to MAP and Max-Log-MAP algorithms. The simulation results of the bit error rate (BER) performance, assuming binary phase -- shift keying (BPSK) and additive white Gaussian noise (AWGN) channel, demonstrate that the performance of the new decoding scheme is not degraded. The BER performance of iterative SOVA decoding of serially concatenated block codes shows no difference in the quality of the soft outputs of the new decoding scheme and of the conventional SOVA.     

Trained Space-Time Block Decoding for Flat Fading Channels with Frequency Offsets

Space-time block coding (STBC) is a recent appealing solution to the problem of exploiting transmit diversity in multi-antenna systems for communications over flat fading channels. In a standard STBC scheme the receiver requires Channel State Information (CSI), which can be acquired via training at the expense of a reduced information rate. Alternatively, the requirement of CSI can be avoided altogether by using differential encoding. The existing trained or differential schemes for STBC assume that the channel is time-invariant during the transmission of at least two data blocks. However, wireless channels may often be time varying owing to frequency offsets induced by either Doppler shifts or carrier frequency mismatches. In this paper we present a simple trained STBC scheme for fading channels with frequency offsets. This revised version was published online in July 2006 with corrections to the Cover Date.     

An MMSE Decoding Algorithm without Matrix Inversion in QSTBC

The matrix inversion operation is needed in the MMSE decoding algorithm of orthogonal space-time block coding （OSTBC） proposed by Papadias and Foschini. In this paper, an minimum mean square error （MMSE） decoding algorithm without matrix inversion is proposed, by which the computational complexity can be reduced directly but the decoding performance is not affected.