VLSI implementation of MIMO detection using the sphere decoding algorithm

Multiple-input multiple-output (MIMO) techniques are a key enabling technology for high-rate wireless communications. This paper discusses two ASIC implementations of MIMO sphere decoders. The first ASIC attains maximum-likelihood performance with an average throughput of 73 Mb/s at a signal-to-noise ratio (SNR) of 20 dB; the second ASIC shows only a negligible bit-error-rate degradation and achieves a throughput of 170 Mb/s at the same SNR. The three key contributing factors to high throughput and low complexity are: depth-first tree traversal with radius reduction, implemented in a one-node-per-cycle architecture, the use of the /spl lscr//sup /spl infin//-instead of /spl lscr//sup 2/-norm, and, finally, the efficient implementation of the enumeration approach recently proposed in . The resulting ASICs currently rank among the fastest reported MIMO detector implementations.     

New MIMO ARQ protocols and joint detection via sphere decoding

In this paper, we develop some new automatic repeat request (ARQ) protocols for multiple-input multiple-out (MIMO) flat-fading channels which adapt the bit-to-symbol mapping of each ARQ retransmission. We begin by defining a model for distinctly mapped transmissions through flat-fading MIMO channels. We characterize the effect that such a mapping diversity has on an integrated receiver utilizing sphere decoding. Varying the symbol mapping complicates the sphere decoding process, particularly for the enumeration of candidate solutions within the sphere. A technique that enables quick candidate enumeration is presented, utilizing concepts from existing closest point search schemes. The advantage of mapping diversity, in reducing bit error rate and reducing computational complexity, is presented along with simulation examples.     

Tree pruning for MIMO sphere detection based on MMSE detection

Tree pruning is an effective algorithm to reduce the complexity of sphere detection(SD) for multiple-input multiple-output(MIMO) communication systems.How to determine the tree pruning rule,as well as by what the tradeoff between the performance and the complexity can be achieved,is still an open problem.In this paper,a tree pruning algorithm is proposed based on minimum mean square error(MMSE) detection.The proposed algorithm first preforms MMSE detection since the complexity of MMSE detection is very low.Then the pruning constraints will be set according to the scaled path metrics of the MMSE solution.The choice of the scale factors and their influences on the complexity and performance are also discussed.Through analysis and simulations,it is shown that the complexity is reduced significantly with negligible performance degradation and additional computations.     

Approaching MIMO capacity using bitwise Markov Chain Monte Carlo detection

This paper examines near capacity performance of Markov Chain Monte Carlo (MCMC) detectors for multipleinput and multiple-output (MIMO) channels. The proposed MCMC detector (Log-MAP-tb b-MCMC) operates in a strictly bit-wise fashion and adopts Log-MAP algorithm with table look-up. When concatenated with an optimized low-density parity-check (LDPC) code, Log-MAP-tb b-MCMC can operate within 1.2-1.8 dB of the capacity of MIMO systems with 8 transmit/receive antennas at spectral efficiencies up to n = 24 bits/channel use (b/ch). This result improves upon best performance achieved by turbo coded systems using list sphere decoding (LSD) detector by 2.3-3.8 dB, leading to nearly 50% reduction in the capacity gap. Detailed comparisons of the Log- MAP-tb b-MCMC with LSD based detectors demonstrate that MCMC detector is indeed the detector of choice for achieving channel capacity both in terms of performance and complexity.     

MIMO信道容量的研究与仿真

MIMO技术可以在不增加带宽和发射功率的情况下提高信道容量和频谱利用率。本文使用MATLAB建立SISO、SIMO、MISO、MIMO等无线信道,进行综合仿真并分析。通过仿真,我们得知,MIMO不但能有效地提高信道的容量,同时可以改善信道的平均信道容量和中断信道容量。     

MIMO系统中球形译码算法的研究

针对多输入多输出（MIMO）通信系统中球形译码检测算法在较低信噪比和较高的调制阶数时复杂度仍然很高的问题,提出一种不影响检测性能同时又能大大降低其复杂度的方案。首先,对传统的球形译码算法进行研究;其次,介绍改进的球形译码算法;最后,通过仿真结果对其进行验证。     

Approaching the capacity of the MIMO Rayleigh flat-fading channel with QAM constellations, independent across antennas and dimensions

In this study we consider the challenge of reliable communication over a wireless Rayleigh flat-fading channel using multiple transmit and receive antennas. Since modern digital communication systems employ signal sets of finite cardinality, we examine the use of the quadrature amplitude modulation (QAM) constellation to approach the capacity of this channel. By restricting the channel input to the M-QAM subset of the complex-plane, the maximum achievable information rate (C/sub M-QAM/) is strictly bounded away from the channel capacity (C). We utilize a modified version of the Arimoto-Blahut algorithm to determine C/sub M-QAM/ and the probability distribution over the channel input symbols that achieves it. The results of this optimization procedure numerically indicate that the optimal input symbol distribution factors into the product of identical distributions over each real dimension of the transmitted signal. This is shown to vastly reduce the computational complexity of the optimization algorithm. Furthermore, we utilize the computed optimal channel input probability mass function (pmf) to construct capacity approaching trellis codes. These codes are implemented independent across all antennas and symbol dimensions and, if used as inner codes to outer low-density parity check (LDPC) codes, can achieve arbitrarily small error rates at signal-to-noise ratios very close to the channel capacity C/sub M-QAM/. Examples are given for a 2-transmit/2-receive antenna (2 /spl times/ 2) system.     

Combined simplified maximum likelihood and sphere decoding algorithm for MIMO system

In this article, a new system model for sphere decoding （SD） algorithm is introduced. For the 2 × 2 multipleinput multiple-out （MIMO） system, a simplified maximum likelihood （SML） decoding algorithm is proposed based on the new model. The SML algorithm achieves optimal maximum likelihood （ML） performance, and drastically reduces the complexity as compared to the conventional SD algorithm. The improved algorithm is presented by combining the sphere decoding algorithm based on Schnorr-Euchner strategy （SE-SD） with the SML algorithm when the number of transmit antennas exceeds 2. Compared to conventional SD, the proposed algorithm has low complexity especially at low signal to noise ratio （SNR）. It is shown by simulation that the proposed algorithm has performance very close to conventional SD.     

基于信道容量的单光子探测研究

单光子探测技术对于量子密钥分配乃至量子信息技术都有重要的意义.文章引入了信道容量作为量度指标评价单光子雪崩光电二极管(SPADs)的性能,经研究表明,在综合考虑器件结构、工作电压、倍增层材料等各种因素的基础上,信道容量的引入可以使SPADs的性能从理论上达到最优.     

New compound upper bound on MIMO channel capacity

MIMO channel capacity may be severely degraded due to correlation between individual sub-channels of the matrix channel. Several models, which are limited to some specific scenarios, have been developed to date to account for this effect. In this letter, we derive a new upper bound on the mean (ergodic) MIMO capacity, which is not limited to a particular scenario and accounts for both transmit (Tx) and receive (Rx) end correlations in such a way that their impact can be estimated separately and compared. Thus, a conclusion can be made as to which end contributes more to capacity reduction. In general, the higher correlated end has a dominant effect on the capacity     

Beneficial impact of channel correlations on MIMO capacity

The potential beneficial impact of channel correlations on the capacity of MIMO systems is investigated. In contrast to most previous work, the present analysis is based on a comprehensive model of the channel correlation structure. It is therefore illustrated that fading cross-correlations may increase the ergodic capacity, sometimes even beyond the supposedly ideal case of independent channels. Starting from considerations on an analytical upper bound of the capacity, the study is then supported by simulation results of the actual ergodic capacity in arbitrary MIMO channels using a simple geometry-based stochastic model.     

"Turbo DPSK" using soft multiple-symbol differential sphere decoding

Coded interleaved differential M-ary phase-shift keying (M-DPSK) with iterative decoding, the so-called "Turbo DPSK," is known as a power-efficient transmission format. Due to the rotational invariance of DPSK, it particularly enables detection without channel state information (CSI). However, the soft-input soft-output (SISO) component decoder for DPSK is the computational bottleneck if performance close to the ideal case of perfect CSI is desired. In this paper, we take a fresh look at SISO decoding without CSI and apply sphere decoding (SD) to reduce complexity. In particular, we devise a maximum a posteriori probability (MAP) multiple-symbol differential sphere decoder (MSDSD) which efficiently solves the high-dimensional search problem inherent to detection without CSI. Together with a soft-output generation device the MAP-MSDSD algorithm forms a new SISO-MSDSD module for iterative decoding. We analyze the extrinsic information transfer (EXIT) characteristic of the novel module, by means of which we are able to design powerful encoder and decoder structures. For, respectively, the additive white Gaussian noise (AWGN) and the continuously time-varying Rayleigh-fading channel without CSI these designs operate within 1.7-1.9 and 2.3-2.5 dB of channel capacity assuming perfect CSI. These figures compare favorably with results available in the literature, especially for reasonably high data rates of 1-2 bit/channel use. Simulation studies of the average and the maximum complexity required by SISO-MSDSD demonstrate the advantageous performance versus complexity tradeoff of our approach.     

基于软门限LDPC码的中继信道容量实现

LDPC（Lowdensity parity code）码是逼近香农界的信道码。为了逼近香农界,其优化一般采用硬门限准则。但当信道容量小于编码码率时,LDPC无法正确译码。因此,提出从软门限的角度优化LDPC码,使得在码率超过信道容量时,接收端仍可以部分译码,并将该LDPC码用于单中继信道中,解决使用解码前传（DF,decode and forward）的中继信道容量瓶颈问题,进而提高信道容量。还考虑中继节点使用Slepian-Wolf信源编码,降低中继节点到目的节点的信道质量要求的同时,仍能保证无失真译码。     

Low complexity scalable MIMO sphere detection through antenna detection reordering

This paper describes a novel low complexity scalable multiple-input multiple-output (MIMO) detector that does not require preprocessing and the optimal squared l ²-norm computations to achieve good bit error (BER) performance. Unlike existing detectors such as Flexsphere that use preprocessing before MIMO detection to improve performance, the proposed detector instead performs multiple search passes, where each search pass detects the transmit stream with a different permuted detection order. In addition, to reduce the number of multipliers required in the design, we use l ¹-norm in place of the optimal squared l ²-norm. To ameliorate the BER performance loss due to l ¹-norm, we propose squaring then scaling the l ¹-norm. By changing the number of parallel search passes and using norm scaling, we show that this design achieves comparable performance to Flexsphere with reduced resource requirement or achieves BER performance close to exhaustive search with increased resource requirement.     

Low complexity MIMO scheduling with channel decomposition using capacity upperbound

In multiuser MIMO systems, the base station schedules transmissions to a group of users simultaneously. Since the data transmitted to each user are different, in order to avoid the inter-user interference, a transmit preprocessing technique which decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO channels can be used. When the number of users is larger than the maximum that the system can support simultaneously, the base station selects a subset of users who have the best instantaneous channel quality to maximize the system throughput. Since the exhaustive search for the optimal user set is computationally prohibitive, a low complexity scheduling algorithm which aims to maximize the capacity upper bound is proposed. Simulation results show that the proposed scheduling algorithm achieves comparable total throughput as the optimal algorithm with much lower complexity.     

RNN based MIMO channel prediction

A new hybrid PSO-EA-DEPSO algorithm based on particle swarm optimization (PSO), evolutionary algorithm (EA), and differential evolution (DE) is presented for training a recurrent neural network (RNN) for multiple-input multiple-output (MIMO) channel prediction. This algorithm is shown to outperform RNN predictors trained off-line by PSO, EA, and DEPSO as well as a linear predictor trained by the Levinson–Durbin algorithm. To explore the effects of channel prediction error at the receiver, new expressions for the received SNR, array gain, and average probability of error are derived and analyzed. These expressions differ from previous results which assume the prediction error is Gaussian and/or independent of the true CSI. The array gain decays with increasing signal-to-noise ratio and is slightly larger for spatially correlated systems. As the prediction error increases in the non-saturation region, the coding gain decreases and the diversity gain remains unaffected.     

Downlink capacity of interference-limited MIMO systems with joint detection

The capacity of downlink cellular multiple-input multiple-output (MIMO) systems, where co-channel interference is the dominant channel impairment, is investigated in this paper, mainly from a signal-processing perspective. Turbo space-time multiuser detection (ST MUD) is employed for intracell communications and is shown to closely approach the ultimate capacity limits in Gaussian ambient noise for an isolated cell. Then, it is combined with various multiuser detection methods for combating intercell interference. Among various multiuser detection techniques examined, linear minimum-mean-square-error (MMSE) MUD and successive interference cancellation are shown to be feasible and effective. Based on these two multiuser detection schemes, one of which may outperform the other for different settings, an adaptive detection scheme is developed, which together with a Turbo ST MUD structure offers substantial performance gain over the well-known V-BLAST techniques with coding in this interference-limited cellular environment. The obtained multiuser capacity is excellent in the high to medium signal-to-interference ratio scenario. Nonetheless, numerical results also indicate that a further increase in system complexity, using base-station cooperation, could lead to further significant increases of the system capacity. The asymptotic multicell MIMO capacity with linear MMSE MUD preprocessing is also derived, and this analysis agrees well with the simulation results.     

MIMO Ricean channel capacity: an asymptotic analysis

This paper presents asymptotic bounds and limits for the mean channel capacity of MIMO systems under Ricean channel conditions. It is shown that the mean capacity per dimension decreases as the K factor increases in value and approaches a value equal to that of the underlying scattering channel when the number of antennas are large and the specular matrix has unit rank. The accuracy of the bounds is verified by simulations. In addition, a variety of results for the MIMO Ricean channel are brought together to give an overview of the current knowledge in this area. We also show that the variance of the capacity for a Ricean channel approaches that of the scattering channel for large numbers of antennas.     

航空图像回传系统中MIMO信道的容量分析

多入多出技术同时采用多天线发射和多天线接收,能够大大提高无线通信系统的容量和频谱利用率。在空一地无线传输MIMO信道模型的基础上,讨论了在航空图像传输链路中应用MIMO系统的理论基础,结合数值模拟分析的方法对MIMO信道的平均容量和容量互补累积分布函数进行了分析。研究表明:在不相关Ricean信道中MIMO系统的容量随着天线数目的增加渐近线性增加;而在相关情况下渐近对数增加。     

On MIMO channel capacity: an intuitive discussion

For a general MIMO communication channel, the use of the linear minimum mean-squared-error (LMMSE) estimator followed by the separate substream decoding is not a capacity-wise optimal scheme. In this paper, the author presents analytical computations of the MIMO channel capacity. The article relates the capacity to the covariance matrix of the LMMSE estimate that provides a clear interpretation of the concept of capacity as well some optimal transceiver design schemes that aim to achieve channel capacity.