Design of low-density parity check codes for MIMO systems with doubly-iterative receivers

In this paper, the Multiple Input Multiple Output (MIMO) doubly-iterative receiver which consists of the Probabilistic Data Association detector (PDA) and Low-Density Parity-Check Code (LDPC) decoder is developed. The receiver performs two iterative decoding loops. In the outer loop, the soft information is exchanged between the PDA detector and the LDPC decoder. In the inner loop, it is exchanged between variable node and check node decoders inside the LDPC decoder. On the light of the Extrinsic Information Transfer (EXIT) chart technique, an LDPC code degree profile optimization algorithm is developed for the doubly-iterative receiver. Simulation results show the doubly-receiver with optimized irregular LDPC code can have a better performance than the one with the regular one.     

频率选择性信道下空间相关MIMO的迭代检测技术

给出了一种频率选择性信道下空间相关MIMO的系统模型,其发送端采用准循环系统RA码,接收端采用一种对空间相关和非相关信道均适用的软干扰消除迭代检测算法.该算法首先采用基于最小均方误差检测(MMSE)的滑动窗口模型进行干扰消除,然后采用多天线联合最大似然检测(ML)以得到软信息,再将得到的软信息传递到译码器译码并输出发送比特的软信息作为下一次迭代的先验信息,即完成一次迭代.此模型能够取得比较好的误码率性能(BER),其改进方案既增加了发送端的调制域分集,性能又有提升.作为比较,基于软干扰消除的逐天线MMSE迭代检测的方案(ABA SC/MMSE)性能很差.仿真结果也证明了以上观点.     

A simple soft linear detection for coded multi‐input multi‐output systems

We propose a very simple and efficient soft linear multi‐input multi‐output (MIMO) detection scheme. The detection process is divided into two separate problems. The proposed scheme first detects MIMO symbols using conventional linear detection methods and produces soft bit information using a simple soft demapping method. Next, we refine the soft information by accounting for uneven post‐detection noise variance across MIMO layers. From the simulation result investigated in this paper, we first emphasize that powerful channel coding may suppress the differences of diversity gains among various MIMO detection schemes. This implies that the channel decoding operation may not be transparent to performance gain that resulted from MIMO detection process. The proposed scheme concentrates on accurate estimation of soft post‐MIMO detected information in a very simple manner, rather than concentrating on a complex MIMO detection scheme prior to decoding process. In combination with turbo codes, the proposed scheme produces comparable performance to maximum likelihood detection, even with the simplest scheme such as zero forcing detection, with drastically reduced complexity. Copyright © 2011 John Wiley & Sons, Ltd.     

MIMO-OFDM-CDM系统低复杂度Turbo检测

提出了将码分复用(CDM)模块看作系统等效信道的一部分,从而在MIMO-OFDM-CDM系统中引入Turbo迭代检测的措施。使用Turbo迭代检测可以通过解码器和解调器之间软信息的多次迭代提高译码的性能。根据CDM模块的特点,提出了将等效多天线之间的干扰视为高斯噪声,从而降低Turbo迭代检测算法复杂度的措施。仿真结果表明,在系统中使用Turbo迭代检测可以在有限次迭代后达到比传统算法更低的误码率。     

基于软输出固定复杂度球形译码的高效迭代检测算法

该文在软输出固定复杂度球形译码(SFSD)算法的基础上,提出一种低复杂度高性能的MIMO迭代检测方法。该算法利用迭代过程中译码器的反馈信息更新SFSD检测算法的软输出,获得明显的迭代增益,并利用多级比特映射星座图的特点大大降低分支度量的运算次数。针对SFSD算法预处理复杂度较高的问题,该文将检测顺序调整和QR分解两个预处理步骤相结合,从而减少了矩阵求逆运算。在长期演进方案(LTE)下行链路环境中的仿真结果表明,该文提出的算法性能十分接近最优的最大后验概率(MAP)检测,并且实现复杂度相对于MAP有显著的下降。     

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。     

Low-complexity SIC-MMSE for joint multiple-input multiple-output detection

Iterative detection and decoding based on a soft interference cancellation–minimum mean squared error (SIC-MMSE) scheme provides efficient performance for coded MIMO systems. The critical computational burden for a SIC-MMSE detector in a MIMO system lies in the multiple inverse operations of the complex matrix. In this paper, we present a new method to reduce the complexity of the SIC-MMSE scheme based on a MIMO detection scheme that uses a single universal matrix with a non-layer-dependent inversion process. We apply the Taylor series expansion approach and derive a simple non-layer-dependent inverse matrix. The simulation results reveal that the utilization of the universal matrices presented in this paper produces almost the same performance as the conventional SIC-MMSE scheme but with low computational complexity.     

一种低复杂度软入软出迭代检测方案

在MIMO系统中,以软输入软输出方式为基础的迭代检测方式,性能要明显优于基于硬判决的迭代方案。因此基于软信息传递的迭代检测理论具有广泛的应用。但是,其复杂度较高,特别是应用于MIMO系统时,复杂度的限制尤为明显。球形译码是一种近似最大似然检测的低复杂度方案,在这里,引入一种低复杂度的软入软出（SISO）球形译码迭代方案,并给出球形译码中搜索树的删减简化方案。     

Turbo processing for an OFDM-based MIMO system

We consider improving the overall system performance of an orthogonal frequency-division multiplexing-based multiple-input multiple-output (MIMO) wireless local area network system. We use a combined iterative detection/decoding and channel updating method, referred to herein as turbo processing, to improve performance. First, we improve a recently proposed list sphere decoder-based iterative MIMO soft-detector by constraining the value of the a priori information from a soft-in soft-out channel decoder. Second, we propose a channel updating scheme using the decoded packet data to improve the channel estimation accuracy. Simulation results show that turbo processing can be used to significantly improve the performance of the system considered.     

Near-optimum decoding of product codes: block turbo codes

This paper describes an iterative decoding algorithm for any product code built using linear block codes. It is based on soft-input/soft-output decoders for decoding the component codes so that near-optimum performance is obtained at each iteration. This soft-input/soft-output decoder is a Chase decoder which delivers soft outputs instead of binary decisions. The soft output of the decoder is an estimation of the log-likelihood ratio (LLR) of the binary decisions given by the Chase decoder. The theoretical justifications of this algorithm are developed and the method used for computing the soft output is fully described. The iterative decoding of product codes is also known as the block turbo code (BTC) because the concept is quite similar to turbo codes based on iterative decoding of concatenated recursive convolutional codes. The performance of different Bose-Chaudhuri-Hocquenghem (BCH)-BTCs are given for the Gaussian and the Rayleigh channel. Performance on the Gaussian channel indicates that data transmission at 0.8 dB of Shannon's limit or more than 98% (R/C>0.98) of channel capacity can be achieved with high-code-rate BTC using only four iterations. For the Rayleigh channel, the slope of the bit-error rate (BER) curve is as steep as for the Gaussian channel without using channel state information     

COMBINED TRANSMIT ANTENNA SELECTION AND DETECTION OVER SPATIAL CORRELATED MIMO SYSTEMS

In this paper a method that combines transmit antenna selection and reduced-constellation detection in spatially correlated Multi-Input Multi-Output (MIMO) fading channels is presented. To mitigate the performance degradation caused by the use of antenna selection that is based on correlation among columns, an iterative receiver scheme that uses only a subset of the constellation points close to the expected symbol value estimated in the previous iteration is proposed. The size of the subset can adapt to the maximum correlation of the sub-matrix after the simple antenna selection. Furthermore, the error rate performance of the scheme under linear Minimum Mean Square Error (MMSE) or Ordered Successive Interference Cancellation (OSIC) for the first run detection and different interleaver lengths is investigated while the transmit antenna selection is considered. The simulation results show a sig- nificant advantage both for implementation complexity and for error rate performance under a fixed data rate.     

A new class of soft MIMO demodulation algorithms

We propose a new class of soft-input soft-output demodulation schemes for multiple-input multiple-output (MIMO) channels, based on the sequential Monte Carlo (SMC) framework under both stochastic and deterministic settings. The stochastic SMC sampler generates MIMO symbol samples based on importance sampling and resampling techniques, whereas the deterministic SMC approach recursively performs exploration and selection steps in a greedy manner. By exploiting the artificial sequential structure of the existing simple Bell-Labs layered space-time (BLAST) detection method based on ing and cancellation, the proposed algorithms achieve an error probability performance that is orders of magnitude better than the traditional BLAST detection schemes while maintaining a low computational complexity. In fact, the new methods offer performance comparable with that of the sphere decoding algorithm without attendant increase in complexity. More importantly, being soft-input soft-output in nature, both the stochastic and deterministic SMC detectors can be employed as the first-stage demodulator in a turbo receiver in coded MIMO systems. Such a turbo receiver successively improves the receiver performance by iteratively exchanging the so-called extrinsic information between the soft outer channel decoder and the inner soft MIMO demodulator under both known channel state and unknown channel state scenarios. Computer simulation results are provided to demonstrate the performance of the proposed algorithms.     

Joint Frequency-Domain Multiuser Turbo Equalization with Successive Interference Cancellation for Doubly-Selective Fading Channels

A novel multiuser separation and equalization scheme is proposed for single carrier wireless communication systems integrating frequency-domain (FD) multiuser turbo equalization (MUTE) and successive interference cancellation (SIC). The proposed iterative structure consists of multiple layers of detection, and at each layer the user with strongest power is processed by a frequency-domain multiuser equalizer to yield the soft extrinsic information on the coded bits of that user, which is delivered to a channel decoder after deinterleaving. The extrinsic information gleaned by the decoder is fed back to both the current and previous multiuser equalizers for the next iteration as a-priori information. The soft symbols of the current user are evaluated by the a-posteriori information of coded bits provided by the multiuser equalizer, and the interference reconstructed by the current user’s soft symbols is canceled out from the received signals in frequency domain. The interference-canceled signals are fed forward to subsequent layers for detection of other users. The proposed scheme effectively mitigates multiple access interference and intersymbol interference by an iterative (turbo) detection method. Numerical simulation examples demonstrate that the proposed FD MUTE with SIC outperforms the traditional MMSE multiuser equalizer over the severely doubly-selective channels, and the bit-error-rate performance tends to be better with the increase of iterations.     

Simple and Accurate Design of Low-Density Parity-Check Codes for Multi-Input Multi-Output Systems

In this paper we design an irregular low-density parity-check (LDPC) code for multiple-input multiple-output (MIMO) systems, using a simple extrinsic information transfer (EXIT) chart method. The MIMO systems considered are the optimal maximum a posteriori probability (MAP) detector and the suboptimal minimum mean square error soft-interference cancellation (MMSE-SIC) detector. The MIMO detector and the LDPC decoder exchange soft information and form a turbo iterative receiver. The EXIT charts are used to obtain the edge degree distribution of the irregular LDPC code which is optimized for the MIMO detector. It is shown that the performance of the designed LDPC code is better than that of conventional LDPC code which was optimized for either the Additive White Gaussian Noise (AWGN) channel or the MIMO channel without an explicit consideration of the given detector structure.     

基于SSCANL译码器的联合迭代检测译码算法

为了提升基于极化码的稀疏码多址接入（sparse code multiple access,SCMA）系统接收机性能,提出了基于简化软消除列表（simplify soft cancellation list,SSCANL）译码器的循环冗余校验（cyclic redundancy check,CRC）辅助联合迭代检测译码接收机方案。该方案中极化码译码器使用SSCANL译码算法,采用译码节点删除技术对软消除列表（soft cancellation list,SCANL）算法所需要的L次软消除译码（soft cancellation, SCAN）进行简化,通过近似删除冻结位节点,简化节点间软信息更新计算过程,从而降低译码算法的计算复杂度。仿真结果表明,SSCANL算法可获得与SCANL算法一致的性能,其计算复杂度与SCANL算法相比有所降低,码率越低,算法复杂度降低效果越好;且基于SSCANL译码器的CRC 辅助联合迭代检测译码接收机方案相较基于SCAN译码器的联合迭代检测译码（joint iterative detection and decoding based on SCAN decoder, JIDD-SCAN）方案、基于SCAN译码器的CRC辅助联合迭代检测译码（CRC aided joint iterative detection and decoding based on SCAN decoder,C-JIDD-SCAN）方案,在误码率为10^-4时,性能分别提升了约0.65 dB、0.59 dB。     

Reduced-Complexity Turbo Equalization for Turbo Coded MIMO/OFDM Systems

1IntroductionTowards wireless systems Beyondthe3G(B3G),it isa great challenge for the physical layer to support high-speed transmissioninthe mobile environment to providecomfortable Internet access.Multiple Input MultipleOutput(MI MO)technique is effectiv…     

Iterative Soft-Kalman Filter-based Data Detection and Channel Estimation for Turbo Coded MIMO–OFDM Systems

MIMO channels are often assumed to be constant over a block or packet. This assumption of block stationarity is valid for many fixed wireless scenarios. However, for communications in a mobile environment, the stationarity assumption will result in considerable performance degradation. In this paper, we focus on a new channel estimation technique for Turbo coded MIMO systems using OFDM. In the proposed MIMO–OFDM system, pilots are placed on selected subcarriers and used by a pair of Kalman filter (KF) channel estimators at the receiver. The KF channel estimates are then utilized by a MIMO–OFDM soft data detector based on the computationally efficient QRD-M algorithm. The soft detector output is fed back to the Kalman filters to iteratively improve the channel estimates. The extrinsic information generated by the Turbo decoder is also used as a priori information for the soft data detector. The overall receiver thus combines MIMO data detection, KF-based channel estimation, and Turbo decoding in a joint iterative structure yielding computational efficiency and improved bit-error rate (BER) performance. Parts of this paper were presented at ICC’2005, Seoul, Korea. This work was supported in part by NSF Grant No. CCF-0429596. This work was done when he was with the Nokia Research Center in Dallas, USA.     

Low‐Complexity Massive MIMO Detectors Based on Richardson Method

In the uplink transmission of massive (or large‐scale) multi‐input multi‐output (MIMO) systems, large dimensional signal detection and its hardware design are challenging issues owing to the high computational complexity. In this paper, we propose low‐complexity hardware architectures of Richardson iterative method‐based massive MIMO detectors. We present two types of massive MIMO detectors, directly mapped (type1) and reformulated (type2) Richardson iterative methods. In the proposed Richardson method (type2), the matrix‐by‐matrix multiplications are reformulated to matrix‐vector multiplications, thus reducing the computational complexity from O(U²) to O(U). Both massive MIMO detectors are implemented using a 65 nm CMOS process and compared in terms of detection performance under different channel conditions (high‐mobility and flat fading channels). The hardware implementation results confirm that the proposed type1 Richardson method‐based detector demonstrates up to 50% power savings over the proposed type2 detector under a flat fading channel. The type2 detector indicates a 37% power savings compared to the type1 under a high‐mobility channel.     

基于叠加训练的非合作多用户/MIMO信道估计

提出一种基于叠加训练的单载波非合作多用户/MIMO系统的迭代信道估计与检测方案。首先利用变换域方法构造具有零周期互相关特性的训练序列,从而消除多天线间的相互干扰,实现基于一阶统计量的信道估计。然后采用联合符号检测的迭代信道估计方法,利用检测序列作为额外的“训练序列”来降低信息序列自身干扰。与现有的叠加训练信道估计方案比较,新方案中训练序列构造更加灵活,在低信噪比下信道估计均方误差和误码率性能更优,且复杂度更低,仿真结果表明了该方案的有效性。     

MIMO OFDM系统中的Turbo子载波均衡

在MIMO OFDM系统中,为了对抗同天线干扰及由于保护间隔不足而引起的码间干扰和载波间干扰,该文给出了一种基于MMSE的Turbo子载波均衡器。在该算法中,软输入软输出(SISO)的子载波均衡器与软输入软输出(SISO)解码器通过迭代进行软信息交换。仿真结果表明,与非迭代的子载波均衡器相比,该文给出的Turbo子载波均衡器能够有效利用时间和空间分集,使系统性能得到了改善。