Turbo equalization with sequential sequence estimation overmultipath fading channels

We investigate the performance of a turbo equalization scheme over frequency-selective fading channels, where a soft-output sequential algorithm is employed as the estimation algorithm. The advantage of this scheme comes from the low computational complexity of the sequential algorithm, which is only linearly dependent on the channel memory length. Simulation results of an 8-PSK trellis-coded modulation (TCM) system show that the performance of this scheme suffers approximately 2-dB loss compared with that of the turbo max-log maximum a posteriori (MAP) probability equalizer after 5 iterations     

Diversity Combining and Equalization with TCM for Wireless Communications

This paper presents an equalization structure in which antennadiversity, adaptive decision feedback equalization (DFE), interleavingand trellis-coded modulation (TCM) can be effectively combined to combatboth ISI and cochannel interference in cellular mobile radioenvironments. The feedback filter of the DFE can use either tentative orfinal decision symbols of the TCM Viterbi decoding to cancel tail ISIwith the square root Kalman algorithm. A performance bound on theaverage pairwise error probability for TCM under perfect interleavingand equalization is obtained by analysis. Some simulation results whichillustrate the potential of the proposed system will also be given. Inparticular, a performance comparison between the proposed method anduncoded QPSK modulation will be undertaken.     

Iterative Equalization and TCM Decoding with Refined Channel Value

In this correspondence, we present a new method for the iterative equalization and decoding of multilevel trellis coded modulation (TCM) signals over frequency selective channels. Results show that the proposed algorithm achieves better performance compared to the previous work on the MMSE filter- based turbo equalization for a non-binary coded modulation scheme. The performance gain is accomplished by utilizing the combined modulation and coding nature of TCM and passing the refined signal obtained from different paths to the TCM decoder as the channel value in addition to the a priori probabilities.     

Soft input soft output Kalman equalizer for MIMO frequency selective fading channels

We consider the Kalman filter for equalization of a multiple-input multiple-output (MIMO), frequency selective, quasi-static fading channel. More specifically, we consider a coded system, where the incoming bit stream is convolutionally encoded, interleaved and then spatially multiplexed across the transmit antennas. Each substream is modulated into M-ary symbols before being transmitted over a frequency selective channel. At the receiver, we propose to use the Kalman filter as a low complexity MIMO equalizer, as opposed to the trellis based maximum a-posteriori (MAP) equalizer whose computational complexity grows exponentially with the channel memory, the number of transmit antennas and the spectral efficiency (bits/s/Hz) of the system. We modify the structure of the Kalman filter and enable it to process the a-priori (soft) information provided by the channel decoder, thereby allowing us to perform iterative (turbo) equalization on the received sequence. The iterative equalizer structure is designed for general M-ary constellations. We also propose a low complexity version of the above algorithm whose performance is comparable to its full complexity counterpart, but which achieves a significant complexity reduction. We demonstrate via simulations that for higher order constellations, when sufficient number of receive antennas are available (e.g. for a 2 transmitter, 3 receiver system, QPSK), the performance of the proposed algorithms after 4 iterations is within 1.5 dB of the non-iterative MAP algorithm with close to an order of magnitude complexity reduction. By objectively quantifying the complexity of all the considered algorithms we show that the complexity reduction for the proposed schemes becomes increasingly significant for practical systems with moderate to large constellation sizes and a large number of transmit antennas     

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.      

The study of logarithmic image processing model and its applicationto image enhancement

Describes a new implementation of Lee's (1980) image enhancement algorithm. This approach, based on the logarithmic image processing (LIP) model, can simultaneously enhance the overall contrast and the sharpness of an image. A normalized complement transform has been proposed to simplify the analysis and the implementation of the LIP model-based algorithms. This new implementation has been compared with histogram equalization and Lee's original algorithm.     

迭代均衡系统中的一种SNR估计方法

该文首先分析了最大后敛概率(Maximum A posterior Probability, MAP)迭代均衡及其简化算法Max-Log- MAP(MLM)、缩放软信息的Max-Log-MAP算法(Scaled Max-Log-MAP,SMLM)对SNR估计误差的敏感性问题,然后利用SMLM算法对SNR估计误差不敏感的特性,提出了一种基于SMLM的软输出信息估计信道SNR的方法。最后,利用该算法,还提出了一种新的迭代均衡算法,并研究了其性能,结果表明该算法不仅不需要任何导引符号开销,还能获得非常接近具有理想的SNR的MAP算法的误码性能。     

An importance sampling technique for a symbol-by-symbol TCMdecoding/equalization algorithm

An importance sampling simulation technique is used to estimate the bit-error rate (BER) of a symbol-by-symbol trellis-coded modulation (TCM) decoder/equalizer proposed for digital microwave radio applications. To evaluate the performance at a BER smaller than 10^-6, we investigate a randomized bias technique previously developed by the authors. To properly select the bias vectors, the asymptotic (infinite signal-to-noise ratio) decision boundary is first determined. The simulation technique is then extended to the one-shot symbol-by-symbol TCM decoding/equalization algorithm which is equivalent to the recursive symbol-by-symbol detection algorithm of Abend and Fritchman (1970). By using this novel importance sampling technique, we can speed up the simulation and efficiently evaluate the BER performance of the TCM decoder/equalizer     

空时分块编码OFDM系统的Turbo均衡

研究了空时分块编码的OFDM（正交频分复用）系统,对系统进行了Turbo均衡,并讨论了此时系统的译码算法和均衡算法。系统信道编码采用Turbo码,通过对BCJR（Bahl,Cocke,Jelinek,Raviv）算法的简单修改得到SISO（单输入单输出）MAP（最大后验概率）译码算法;均衡器采用SISOMMSE（最小均方差）Turbo均衡算法,并利用OFDM系统的循环前缀特性进一步降低算法复杂度。通过仿真对系统性能进行了比较分析,仿真结果表明,采用迭代均衡的空时分块编码OFDM系统性能要明显优于未空时编码和未迭代均衡的OFDM系统。     

双选信道下OCDM系统低复杂度均衡

正交Chirp复用(OCDM)是近年来提出的一种新的多载波体系,通过菲涅尔变换,获得一组正交Chirp信号,实现了CSS的最大频谱效率。该文介绍了OCDM系统的基本原理,重点研究了OCDM系统的低复杂度均衡算法。双选信道下,传统的MMSE均衡算法性能下降,提出一种基于近似带状矩阵的阻尼LSQR算法,作为求解稀疏矩阵的最小二乘迭代算法。为了缓解快速时变信道中的ICI,提出一种基于近似带状矩阵的LSQR-BDFE算法,结合判决反馈均衡,通过LSQR算法迭代计算。仿真结果表明,双选信道下,OCDM系统比OFDM系统有着更好的BER性能,所提出的LSQR-BDFE算法和带状阻尼LSQR算法,比MMSE均衡算法有着性能优势。     

一种水声通信中的多阵元Turbo均衡算法

Turbo均衡应用在水声通信中的问题主要在于水声信道时间扩展长,多接收阵元处理复杂度较高。该文研究了将时间反转与马尔可夫链蒙特卡罗(MCMC)均衡联合优化算法用于实现Turbo均衡。首先进行时间反转实现多接收阵元较长多径时延的压缩,再利用白化滤波器解决时间反转造成的噪声模型失配问题,最后利用复杂度较低的MCMC均衡器结合软迭代信道估计对时间反转合并后得到的信号进行均衡。结合真实实验信道条件对信道响应估计的误差建立模型,通过仿真比较得出, 该算法在相同条件下相对于多阵元直接自适应Turbo均衡算法复杂度降低67%,且有1.6 dB的误码率性能增益。通过对湖上试验数据进行处理,进一步验证了该算法的优势。     

基于最大比特速率准则的FMT频域均衡算法

针对严格采样滤波多音调制(Filtered Multi-Tone modulation,FMT)系统符号间干扰严重的问题,通过推导严格采样FMT系统的矩阵表示式,提出了一种新的频域均衡算法,该算法以最大化比特速率为目标来确定均衡器的系数。仿真结果表明,在ATTC(Advanced Television Technology Center)E型信道条件下,新算法的可达比特率(Achievable Bit Rate,ABR)性能比最小均方误差准则的线性均衡和判决反馈均衡分别提高了40%和70%,误码率性能在BER为10-4则分别改善了3 dB和5 dB;而在WLAN信道条件下,新算法的ABR性能分别提高了45%和75%,误码率性能在BER为10-4则分别改善了6 dB和10 dB。     

基于FABA-SISO的时变频率选择性衰落信道CPM信号盲均衡

该文针对时变频率选择性衰落信道下高阶连续相位调制(CPM)信号盲均衡中存在的均衡性能较差、复杂度较高以及收敛速度慢等问题,从双向自适应信道均衡的角度出发,将线性调制信号均衡中使用的前后向自适应软输入软输出(FABA-SISO)算法推广,建立一种新的基于FABA-SISO的信道盲均衡方法,并结合逐幸存处理(PSP)思想和Kalman滤波,提出一种适用于高阶CPM信号的自适应盲均衡算法。该算法通过使用FABA-SISO算法,同时利用过去、现在和将来的观察数据进行Kalman滤波信道估计,有效改善了信道估计的精度,同时使用PSP算法来降低系统的复杂度,使得算法具有较好的工程应用性。仿真结果表明所提算法具有良好的盲均衡性能以及收敛性。     

瑞利衰落信道下的Turbo均衡

Turbo均衡是一种将Turbo原理和均衡技术结合起来的技术。他通过反复均衡和信道译码来提高接收机性能。针时瑞利衰落信道，采用基于线性滤波器的软输入／软输出均衡器来消除码间干扰，其系数由最小均方误差准则确定。译码器采用最大后验概率算法时卷积码译码。考虑到瑞利衰落信道为随机信道，用非相干检测时信道进行估计。接收机通过联合均衡和译码以充分利用已经获得的信息，实现信道估计及信道均衡与信道译码的迭代更新。仿真结果表明其性能不仅远远优于非迭代系统．而且在信噪比高于4dB时几乎可以完全消除符号间干扰的影响，与MAPSE相比其复杂度大大降低。     

Prefiltered space-time M-BCJR equalizer for frequency-selectivechannels

This paper addresses the problem of soft equalization for space-time-coded transmissions over frequency-selective fading channels. The structure of the space-time code is embedded in the channel impulse response for efficient joint equalization and decoding. The proposed equalization/decoding approach uses a prefilter to concentrate the effective channel power in a small number of taps followed by a reduced-complexity maximum a posteriori probability (MAP) equalizer/decoder to produce soft decisions. The prefilter introduces residual intersymbol interference which degrades the performance of MAP when applied to the trellis of the shortened channel. However, the shape of the overall shortened channel impulse response allows the M-algorithm to approximate the prefiltered MAP performance with a small number of states. Based on this general framework, we investigate several enhancements such as using different prefilters for the forward and backward recursions, concatenating two trellis steps during decoding, and temporal oversampling. The performance is evaluated through simulations over the EDGE typical urban channel     

基于并行均衡框架的Turbo均衡

为了解决在Turbo均衡中由迭代引起的均衡延迟问题,两种分别对应于最大后验概率(MAP)和线性最小均方误差(LMMSE)均衡算法的并行均衡方案被提出。通过理论分析、仿真验证以及最后的硬件实现复杂度的分析研究表明,对于上述两种并行均衡方案,可以保证在小的硬件实现复杂度开销以及几乎没有性能损失的前提下,大大降低其均衡延迟。     

Decision feedback sequence estimation for unwhitened ISI channelswith applications to multiuser detection

Decision feedback sequence estimation (DFSE), which is a reduced-complexity alternative to maximum likelihood sequence estimation (MLSE), can be used effectively for equalization of intersymbol interference (ISI) as well as for multiuser detection. The algorithm performs very well for whitened (minimum-phase) channels. For nonminimum-phase channels, however, the algorithm is not very effective. Moreover, DFSE requires a noise-whitening filter, which may not be feasible to compute for time-varying channels such as a multiuser direct-sequence code division multiple access (DS-CDMA) channel. Noise-whitening is also cumbersome for applications that involve bidirectional equalization such as the global system for mobile communication (GSM) system. In such conditions, it is desirable to use the Ungerboeck (1974) formulation for sequence estimation, which operates directly on the discrete-time unwhitened statistic obtained from conventional matched filtering. Unfortunately, DFSE based on matched filter statistics is severely limited by untreated interference components. We identify the anticausal interference components, using an error probability analysis. This leads us to a modified unwhitened decision feedback sequence estimator (MUDFSE) in which the components are canceled, using tentative decisions. We obtain approximate error probability bounds for the proposed algorithm. Performance results indicate that the modified algorithm, used on unwhitened channels with relatively small channel correlations, provides similar performance/complexity tradeoffs as the DFSE used on the corresponding whitened minimum-phase channels. The algorithm is especially attractive for multiuser detection for asynchronous DS-CDMA channels with long spreading codes, where it can achieve near-MLSE performance with exponentially lower complexity     

Decoding of trellis-encoded signals in the presence of intersymbolinterference and noise

A novel receiver for data-transmission systems using trellis-coded modulation is investigated. It comprises a whitened-matched filter and a trellis decoder which combines the previously separated functions of equalization and trellis-coded modulation (TCM) decoding. TCM encoder, transmission channel, and whitened-matched filter are modeled by a single finite-state machine with combined intersymbol interference and code states. Using ISI-state truncation techniques and the set-partitioning principles inherent in TCM, a systematic method is then developed for reducing the state complexity of the corresponding ISI and code trellis. A modified branch metric is used for canceling those ISI terms which are not represented by the trellis states. The approach leads to a family of Viterbi decoders which offer a tradeoff between decoding complexity and performance. An adaptive version of the proposed receiver is discussed, and an efficient structure for reduced-state decoding is given. Simulation results are presented for channels with severe amplitude and phase distortion. It is shown that the proposed receiver achieves a significant gain in noise margin over a conventional receiver which uses separate linear equalization and TCM decoding     

一种利用信源冗余的Turbo均衡新算法

为克服无线衰落信道中严重的符号间干扰( ISI)的影响,提出了一种新的利用信源冗余的Turbo均衡算法。该算法将联合信源信道译码技术与Turbo均衡技术结合起来,在均衡、译码、信源之间建立起软信息交互的环路,有效提高了整体接收的性能。外信息传递( EXIT)图分析与计算机仿真均表明,尽管信源冗余给译码器带来的性能提升较为有限,但是将这部分信息反馈回均衡器后,在严重ISI信道,信源冗余度为70%时,整体接收的性能改善约为9.5 dB,基本达到了理想加性高斯白噪声( AWGN)信道下的误码性能。     

一种利用信源冗余的Turbo均衡新算法

为克服无线衰落信道中严重的符号间干扰(ISI)的影响,提出了一种新的利用信源冗余的Turbo均衡算法。该算法将联合信源信道译码技术与Turbo均衡技术结合起来,在均衡、译码、信源之间建立起软信息交互的环路,有效提高了整体接收的性能。外信息传递(EXIT)图分析与计算机仿真均表明,尽管信源冗余给译码器带来的性能提升较为有限,但是将这部分信息反馈回均衡器后,在严重ISI信道,信源冗余度为70%时,整体接收的性能改善约为9.5 dB,基本达到了理想加性高斯白噪声（AWGN）信道下的误码性能。