Space–Time Turbo Equalization With Successive Interference Cancellation for Frequency-Selective MIMO Channels

This paper addresses the issue of iterative space–time equalization for multiple-input–multiple-output (MIMO) frequency-selective fading channels. A new soft equalization concept based on successive interference cancellation (SIC) is introduced for a space–time bit-interleaved coded modulation (STBICM) transmission. The proposed equalizer allows us to separate intersymbol interference (ISI) and multiantenna interference (MAI) functions. Soft ISI is successively suppressed using a low-complexity suboptimum minimum mean square error (MMSE) criterion. The decoupling of ISI and MAI offers more flexibility in the design of the whole space–time equalizer. Different multiantenna detection criteria can be considered, ranging from simple detectors to the optimal maximum a posteriori (MAP) criterion. In particular, we introduce two soft equalizers, which are called SIC/SIC and SIC/MAP, and we show that they can provide a good performance-to-complexity tradeoff for many system configurations, as compared with other turbo equalization schemes. This paper also introduces an MMSE-based iterative channel state information (CSI) estimation algorithm and shows that attractive performance can be achieved when the proposed soft SIC space–time equalizer iterates with the MMSE-based CSI estimator.      

一种基于QR分解的稳健干扰对齐算法

大多数干扰对齐算法都假定发送端可以获得理想的信道状态信息(CSI),由于信道估计误差、反馈延迟等原因,实际通信系统中CSI往往是有误差的。为此,该文提出一种基于QR分解的稳健干扰对齐算法。对含有误差的联合接收信号进行基于QR分解的预处理,消除一半有误差的干扰;然后在有误差的等效信道联合矩阵下,充分考虑信道误差和干扰的影响,通过最小化发送端泄漏到非目标接收端的干扰信号功率来设计预编码矩阵,并基于最小均方误差(MMSE)准则来设计干扰抑制矩阵。最后,在理想CSI和误差CSI的情况下,通过实验仿真,证明了该算法有效地提高了系统性能。     

一种基于最大化Rayleigh熵的稳健干扰对齐算法

干扰对齐在消除干扰方面具有独到的优势,但需要完美的信道状态信息(CSI),这在实际中很难实现。该文分析了传统稳健干扰对齐方案的优缺点,在此基础上,提出一种最大化Rayleigh熵的稳健干扰对齐算法,并对收敛性,自由度和频谱效率等进行了分析。不同于MAX-SINR算法,该文通过最大化信号的Rayleigh熵,求得干扰抑制矩阵。在正向通信中,考虑到数据流之间的相关性取干扰抑制矩阵为原始干扰抑制矩阵的酉矩阵形式,并采用注水功率分配实现用户数据流间的最佳功率分配;基于信道的互惠性,在反向通信时,做类似的处理。通过迭代计算,逐渐将干扰压缩。最后,在完美CSI和误差CSI时,仿真表明该算法显著地提高了系统的性能。     

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。     

范数有界信道误差的权值可调鲁棒干扰对齐算法

针对传统干扰对齐算法需要理想的信道状态信息，且对信道误差敏感的问题，本文基于范数有界信道误差模型，提出了一种权值可调的鲁棒干扰对齐算法。该算法同时考虑干扰和期望信号在相应子空间投影的功率，采用极大极小值方法，最大化二者的最小加权和，而且将权值设计为SNR的指数函数，可随SNR变化自动可调，有效克服不同SNR下噪声的影响。仿真结果表明，在信道误差范数有界时，所提算法具有较好的鲁棒性，并且在中低信噪比区域，权值可调算法较固定权值算法具有更好的鲁棒性。      

多小区MIMO系统中干扰对齐算法分析

干扰对齐技术是解决无线通信系统中同频干扰的重要手段,与传统干扰管理方法相比可获得更大的信道复用增益,提高系统容量。基于工程应用实现的考虑,重点研究了多小区MIMO系统中干扰对齐技术的实现,对求闭式解的经典算法和分布式迭代典型算法在系统容量、收敛性等方面的性能进行了分析比较。针对未来Massive MIMO技术的应用,同时仿真分析了算法在空间相关信道下性能,并分析总结了算法的适用情况。仿真结果表明,基于矩阵投影距离的分布式迭代干扰对齐算法综合性能最优,且具有更好的工程适用性。     

Space-time turbo equalization in frequency-selective MIMO channels

A computationally efficient space-time turbo equalization algorithm is derived for frequency-selective multiple-input-multiple-output (MIMO) channels. The algorithm is an extension of the iterative equalization algorithm by Reynolds and Wang (see Signal Processing, vol.81, no.5, p.989-995, 2001) for frequency-selective fading channels and of iterative multiuser detection for code-division multiple-access (CDMA) systems by Wang and Poor (see IEEE Trans. Commun., vol.47, p.1046-1061, 1999). The proposed algorithm is implemented as a MIMO detector consisting of a soft-input-soft-output (SISO) linear MMSE detector followed by SISO channel decoders for the multiple users. The detector first forms a soft replica of each composite interfering signal using the log likelihood ratio (LLR), fed back from the SISO channel decoders, of the transmitted coded symbols and subtracts it from the received signal vector. Linear adaptive filtering then takes place to suppress the interference residuals: filter taps are adjusted based on the minimum mean square error (MMSE) criterion. The LLR is then calculated for adaptive filter output. This process is repeated in an iterative fashion to enhance signal-detection performance. This paper also discusses the performance sensitivity of the proposed algorithm to channel-estimation error. A channel-estimation scheme is introduced that works with the iterative MIMO equalization process to reduce estimation errors.     

非对称MIMO双向中继干扰信道的干扰对齐算法

针对非对称的多用户MIMO双向中继干扰信道,本文提出了一种简化的基于最大信干噪比的干扰对齐算法,给出了干扰对齐的可行性条件和干扰抑制方案,并分析了系统容量和自由度。本文算法的中继节点不必做复杂的信号处理,大大降低了整个系统的信号处理复杂度;同时,本文算法是基于最大信干噪比方案,与现有文献的中继迫零方案比较,大大提高了系统在中低信噪比时的容量;进一步,通过仿真验证表明,基于本文算法的K用户对双向中继干扰网络可以达到。      

MIMO干扰信道下低复杂度的分布式干扰对齐算法

干扰对齐技术可以有效地提高干扰信道容量和抑制干扰,其问题归结为求得闭式解。传统的干扰对齐方案根据信道的互易性,采用迭代的方法（分布式）来逼近闭式解,但带来了较大的计算开销。本文在K用户MIMO干扰信道系统中提出一种低复杂度的分布式干扰对齐算法,通过对用户K的干扰协方差矩阵进行基于修正的Gram-Schmidt方法使用排序QR分解,选出酉矩阵Q最后的dk列作为用户近似的干扰抑制滤波矩阵,和传统分布式干扰对齐方案相比,在基本保持系统容量和迭代收敛速度的同时,系统的复杂度明显降低。仿真结果验证了算法的有效性。      

非理想信道环境下的多小区干扰对齐技术研究

由于普遍采用频率复用因子为1的方式组网,多小区干扰已成为限制无线通信系统容量的主要因素。为了有效抑制小区间干扰提高小区边缘吞吐量,近年提出了干扰对齐技术,其优势在于可以获得干扰信道的最高自由度。一般的干扰对齐研究仅限于理想信道,研究通过非理想信道环境下的多小区干扰对齐技术,分析了时延信道信息对干扰系统容量的影响。结果表明,信道状态信息的时延大大降低了系统容量,特别是在高信噪比条件下对系统性能的影响更大。     

Interference alignment based on optimizing bit allocation with limited feedback in interfering MIMO-MAC networks

A novel limited feedback for interference alignment algorithm was proposed based on the disadvantages of traditional limited feedback interference alignment schemes for MIMO uplink.Unlike the traditional linear interference alignment,an iterative scheme was presented.The pre-coder was designed through maximizing the target signal to the interference leakage and noise ratio,and interference suppression matrix was designed by maximizing the signal to interference plus noise ratio for each data stream,which can come over rate loss in low SNR.In addition,the bit allocation of traditional limited feedback schemes were based on the mean of interference leakage,which were not perfect and make the total number of the effective bits less than the bits provided by system.Thus,a novel bit allocation scheme was provided that improving bit utilize and decreasing quantization error.Theoretical analysis and simulation experiments show that compare to the existed classical algorithms,the algorithm was a stepwise enhancement of signal quality for iterative search in perfect CSI which was better than linear algorithm and has a larger space with no need for strictly align interference in limited feedback CSI which reduces the influence of quantization error more.The effective bit distribution and bit utilization are improved by bit allocation,resulting in improved performance in limited feedback.     

Interference alignment scheme for massive MIMO system

The performance of massive multiple-input multiple-output （MIMO） system is limited by pilot contamination. To reduce the pilot contamination, uplink and downlink precoding algorithms are put forward based on interference alignment criterion. In the uplink receiving processing, the target function aligns the pilot contamination and the interference signals to the same null space and acquires the maximal space degree of the desired signals. The uplink receiving precoding matrix is solved on maximal signal to interference plus noise ratio （SINR） criterion considering the impact of the pilot contamination on channel estimations. The uplink receiving precoding matrix is used as the downlink transmitting precoding matrix. Exploiting the channel reciprocity, it is proved that, if the uplink receiving precoding matrix achieves maximal S1NR, the identical precoding matrix can be used in the downlink transmission and acquires maximal signal to leakage plus noise ratio （SLNR）. Simulations show that the spectrum efficiency of the proposed algorithm can reach about 1.5 times higher than that of popular matched filtering （MF） precoding algorithm, and about 1.1 times higher than multi-cell minimum mean square error （MMSE） precoding algorithm. The performance of the proposed algorithm can be improved approximately linearly with the increasing of the number of antennas.     

V-BLAST系统中采用发射功率分配的MMSE迭代软干扰抵消算法

作为一种软输入软输出的MIMO检测算法,MMSE迭代软干扰抵消算法在MIMO Turbo接收机中得到广泛的关注。为了进一步改善系统性能,采用链路自适应方案是很好的选择。该文给出变发射功率的MMSE迭代软干扰抵消算法,并采用了一种有效的发射功率分配方案,只需要很少的控制信令,就可以获得较大的误码率性能改善。通过没有信道编译码的链路仿真,在4发4收QPSK调制的V-BLAST系统中,如果误码率要求为BER=10-3,MMSE迭代软干扰抵消检测算法迭代次数为2时,采用推荐的发射功率分配方案比不采用发射功率分配方案的系统性能提高了约2dB,如果调制方式为16QAM,系统性能提高了约6dB。     

互信息量最大化和低复杂度的全双工中继网络自干扰消除和干扰对齐算法

该文针对多用户全双工中继干扰信道,同时考虑全双工中继自干扰消除及用户端干扰消除问题。首先,提出了基于最大化全局互信息量的自干扰消除和干扰对齐算法,并具体给出了自干扰消除矩阵的具体求解算法和方案。进一步,给出了信号对齐和干扰抑制的可行性条件,并分析了系统的互信息量和所受干扰噪声功率,以及系统的自由度。理论分析和仿真结果显示,与现有的典型全双工中继方案相比,该文算法可以提高系统互信息量和自由度,并有较低误码率;另外,该文算法的中继只需进行简单的功率约束,不需做复杂的信号处理,降低了整个系统的信号处理复杂度。     

Minimum mean squared error equalization using a priori information

A number of important advances have been made in the area of joint equalization and decoding of data transmitted over intersymbol interference (ISI) channels. Turbo equalization is an iterative approach to this problem, in which a maximum a posteriori probability (MAP) equalizer and a MAP decoder exchange soft information in the form of prior probabilities over the transmitted symbols. A number of reduced-complexity methods for turbo equalization have been introduced in which MAP equalization is replaced with suboptimal, low-complexity approaches. We explore a number of low-complexity soft-input/soft-output (SISO) equalization algorithms based on the minimum mean square error (MMSE) criterion. This includes the extension of existing approaches to general signal constellations and the derivation of a novel approach requiring less complexity than the MMSE-optimal solution. All approaches are qualitatively analyzed by observing the mean-square error averaged over a sequence of equalized data. We show that for the turbo equalization application, the MMSE-based SISO equalizers perform well compared with a MAP equalizer while providing a tremendous complexity reduction     

A reconfigurable iterative algorithm for the K-user MIMO interference channel

Interference alignment (IA) is a recently proposed transmission technique for the K  -user interference channel (IFC), which is proven to achieve a sum-rate multiplexing gain of K/2$K/2$ at the high interference regime. Motivated by our recent work [1] that showed how the sum-rate scaling can range between K/2$K/2$ and K for moderate-to-low interference conditions, in this paper we present a novel iterative algorithm for the K-user multiple-input multiple-output (MIMO) IFC with arbitrary number of transceiver antennas. The proposed algorithm automatically adjusts itself to the interference regime at hand, in the above sense, as well as to the wireless channel in order to achieve the appropriate sum-rate scaling. Our reconfigurable algorithm combines the system-wide mean squared error minimization criterion with the single-user waterfilling solution to maximize each user's transmission rate according to the interference levels and channel conditions. Extensive computer simulation results for the sum-rate performance of the proposed reconfigurable algorithm over various Ricean fading channels are presented. It is shown that, in the interference-limited regime, the proposed algorithm reconfigures itself so as to achieve the IA scaling whereas, in the moderate-to-low interference regime, it chooses interference-myopic MIMO transmissions for all K communication pairs.     

Interference Alignment Algorithm Based on Feedback Concentration in D2D Communications

This paper proposed an effective interference alignment algorithm based on channel state feedback concentration (FCIA) for device-to-device (D2D) communications. The algorithm iteratively calculates the precoding matrix by using the global channel state information. Furthermore, as D2D discovery is the premise of the D2D communications, an effective interference alignment algorithm based on D2D discovery is also proposed. Simulation results show that, the proposed FCIA algorithm reduces the feedback overhead for transmission coordination compared with the existing full feedback based algorithm. The proposed interference alignment scheme based on D2D discovery feedback is compared with the existing D2D discovery scheme: it is found that although the discovery time slots has increased by about 6.2%, the sum rate achieved by interference alignment is improved by almost 50%.

     

多用户认知网络中基于Grassmann流形梯度法的干扰对齐算法

针对多个主用户和多个次用户的MIMO认知网络,本文给出了一种不依赖信道互惠性和不需要前后向链路交替式迭代的干扰对齐方法。对于次用户,首先,通过对其进行编码,建立了消除主次用户间相互干扰后的等效模型。然后,在等效模型的基础上,以最大化总容量为目标函数设计预编码矩阵,并采用基于Grassmann流形上的梯度法对目标函数进行求解得到预编码。最后,在接收端以最大信干噪比准则来设计接收滤波器矩阵。仿真结果显示,在低信噪比时,本文算法与现有典型算法性能相同,而在高信噪比时本文算法性能更优。      

Iterative (turbo) soft interference cancellation and decoding forcoded CDMA

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached     

一种高效的短波高速数传迭代合并均衡算法

针对电离层信道深衰落导致的短波高速率数据通信误码率急剧升高的问题,利用最小均方误差准则提出一种迭代合并均衡快速算法.算法根据串行高速数据波形的传输特点,构造了基于块处理的合并均衡器,通过增加软信息转换模块,实现了与译码器的软信息迭代.由于充分利用了时域和空域信息,算法获得了较大的性能增益.仿真结果表明:所提算法的误码率比原有均衡算法相比明显下降而计算量与之相当,因而能更好地适用于实际系统.