一种短波信道自适应均衡算法的研究

基于逐幸存路径处理(PSP)的思想,研究了一种减少状态序列估计(RSSE)的短波信道自适应均衡算法.该算法首先通过训练序列估计信道的参数,然后利用RLS算法对信道参数和输入数据的估计值同时进行逐幸存路径地更新.数值仿真表明,在短波信道环境下,RSSE-PSP算法在减小计算复杂度的同时最大限度地保持了性能增益,其性能明显优于其他均衡算法.     

一种新的半盲联合信道数据估计算法

提出一种新的半盲联合信道估计与数据检测器,通过将递归-EM信道估计算法嵌入Turbo均衡器中,根据接收信号进行逐符号信道估计,不但能够适应时变信道,而且有效提高了联合信道数据估计收敛速度。仿真表明本算法对初始信道响应估计精度要求很低,从而大大降低了对训练序列长度的要求,使用很短的训练序列就能够达到较好性能,有效提高了频谱利用率。     

基于PSP均衡技术的CPM检测算法

针对时变频率选择性衰落信道,研究了连续相位调制（CPM）信号的逐幸存检测算法。该算法在未知信道状态的条件下,利用训练序列对信道参数进行初始估计。在对CPM信号进行Viterbi解调过程中,采用PSP技术实现信道的无延时跟踪。基于频域均衡的CPM检测算法虽然可以有效抗多径干扰且计算复杂度较低,但不能对时变信道进行跟踪。仿真结果表明,在时变多径信道下,基于PSP均衡的CPM检测算法能有效地进行信道参数估计,比频域均衡算法具有更好的误码性能。     

基于逐幸存路径处理的空时格形码自适应解码器

本文探讨了无线移动信道中空时格形码的一种自适应解码技术.通过分析无周期间插正交导引信号下空时格形码的最大似然序列检测,指出可利用逐幸存路径处理得到该情形下可实用的最大似然序列检测算法;以此为依据,结合利用自调整LMS算法实现的信道跟踪,本文提出一种空时格形码的自适应解码器,该解码器具有所采用信道跟踪参数与信道衰落速度无关的优点;文章最后给出计算机仿真结果.     

莱斯信道的MLSD技术研究

主要研究在时变多径衰落信道下,基于Viterbi算法的最大似然序列检测技术（MLSD）.为了解决MLSD信道估计问题,使均衡器能够及时跟踪信道的变化,提出了基于逐幸存处理（PSP）和最小存活路径（MSP）的MLSD算法.在莱斯信道环境下,对上述算法进行了仿真.仿真结果表明,将RLS-MSP算法与减状态MLSD算法相结合的信道均衡技术具有对复杂信道的强跟踪能力,同时保证了较高的均衡性能和合理的复杂度.     

自适应减少复杂度的盲最大似然序列估计

 基于逐幸存路径处理原理和自适应选择幸存路径的思想,本文提出了一种自适应减少计算复杂度的盲最大似然序列估计新算法.通过分析和推导,给出了一种近似估计网格图最小欧式距离的方法,并利用该估计值对幸存路径进行取舍,在网格搜索中仅保留少数幸存路径来进行信道参数和发送符号序列的联合盲估计.理论分析和计算机仿真结果表明,对严重符号干扰信道,在较高信噪比条件下,本文提出的新算法具有较理想的误符号率性能和较低的计算复杂度.     

时变多径MIMO信道中一种带自适应信道追踪的序列检测方法

该文针对时变多径MIMO信道,各MISO子系统首先分别采用混合MLSE(H-MLSE)处理,然后结合-幸存状态选择,提出了一种复杂度可控的、带自适应信道追踪的序列检测方法。与传统的MLSE算法相比,该方法具有3个显著特征:通过参数选择,可实现对算法复杂度的可控调节;通过嵌入的判决导向/LMS(DD/LMS)算法,对各幸存状态转移对应的幸存路径上的信道参数可实现接近零时延追踪;可部分采用并行处理技术来实现。对具有两条多径的2X4 MIMO时变信道通过数值仿真表明:当2时,该方法可获得满意的检测性能。     

数字移动通信中的适应均衡技术

分析了移动通信的信道模型，论述了用于时变信道快速收敛的自适应均衡器结构，算法和它们的比较，给出了研究自适应均衡的计算机模拟方法，并对均衡器中主要设计参数进行了讨论。     

数字移动通信中的自适应均衡技术

分析了移动通信的信道模型，论述了用于时变信道快速收敛的自适应均衡器结构、算法和它们的比较，给出了研究自应用均衡的计算机模拟方法，并对均衡器中主要设计参数进行了讨论。     

基于双向逐幸存路径处理的空时格形码软判决自适应解码

本文提出一种针对TDMA下行链路的空时格形码自适应解码算法.为充分利用下行链路相邻时隙前导序列中的正交导引信号,该解码算法采用了双向逐幸存路径处理技术——正向处理利用基于当前时隙前导序列的自适应信道估计实现正向解码,并将软判决结果传递给反向处理模块;以正向软判决为先验知识,反向处理利用基于下一时隙前导序列的自适应信道估计实现反向解码,并将反向软判决作为最终结果输出.计算机仿真结果表明:在存在卷积外码的情况下,与基于最大似然序列检测的单向硬判决解码相比,基于所提出算法的软判决解码在多普勒频移小于60赫兹的时变信道中可提供1～2dB的增益.     

A continuously adaptive MLSE receiver for mobile communications:algorithm and performance

The paper presents a Euclidean distance maximum likelihood sequence estimation (MLSE) receiver, based on the Viterbi algorithm (VA), suitable for fading and noisy communications channels, as that specified by the Group Special Mobiles (GSM). In a mobile cellular system, the fast varying channel characteristics, due to the fading and Doppler effects, require adaptive methods to update the channel coefficients to the MLSE receiver. The proposed technique continuously estimates the channel characteristics directly within the metric calculation of the VA. At each step of the VA, the sequence associated to the path with the best metric value (minimum-survivor method) among the survivor paths is used to update the channel estimate (employing conventional adaptive algorithms) throughout the entire informative sequence. However, the detection of the transmitted data sequence is performed by the VA only at the end of each burst. The proposed technique allows simpler receiver implementation and the simulation results show a good performance of this adaptive MLSE receiver in typical GSM environments     

Block adaptive techniques for channel identification and datademodulation over band-limited channels

A new approach to the problem of data detection for communications over band-limited channels with unknown parameters is introduced. We propose a new way to implement the Viterbi algorithm (VA) for maximum-likelihood data sequence estimation (MLSE) in a known channel environment and utilize it to derive block adaptive techniques for joint channel and data estimation, when the channel-impulse response (CIR) is unknown. We show, via simulations, that we can achieve a probability of error very close to that of the known channel environment and nearly reach a mean-square error in the channel estimate as predicted by analytical bounds, operating on static channels, which exhibit deep nulls in their magnitude response and nonlinear phase. The proposed schemes accomplish channel acquisition after processing a few hundred symbols while operating without a training sequence, whereas linear blind equalizers, such as Sato's (1975) algorithm, fail to converge at all. The application of block processing to adaptive MLSE is also investigated for time-varying frequency-selective Rayleigh-fading channels, which are used for modeling mobile communication systems. In such environments it is shown that the proposed scheme exhibits improved performance compared to the conventional adaptive MLSE receiver using tentative delayed decisions     

抑制DS-UWB多径干扰的RAKE-MLSE接收机

为达到高数据速率，直接序列超宽带（DS-UWB）系统通常使用低扩频增益，在密集多径信道中这可能会增强多径干扰（MPI）从而降低系统的性能。文中将最大序列似然估计（MLSE）引入DS-UWB接收机结构中来抑制MPI。推导了DS-UWB信号的MLSE公式，作为MLSE算法的近似提出采用RAKE-MLSE接收机结构来降低计算复杂度。使用Viterbi算法实现了该接收机，并在IEEE802．15．3a建议的室内信道中对一个DS-UWB系统进行仿真。仿真结果表明该接收机较一般RAKE接收机性能有很大提高。     

Error performance of innovations-based MLSE for Rayleigh fadingchannels

Error performance of maximum likelihood sequence estimation (MLSE) of digital signals transmitted over Rayleigh fading channels is studied in this paper. The application of the innovations approach provides us not only with a general MLSE receiver structure, but also with a tool for analyzing the performance of the receiver. We show that the sequence pairwise error probability of the MLSE receiver is determined by the eigenvalues of a matrix generated from the autocorrelation function of the received signal. For any practical applications, the MLSE for Rayleigh fading channels exhibits an irreducible error floor that depends on the channel characteristics such as the Doppler frequency bandwidth and frequency selectivity. An upper bound on bit error probability can be calculated by using the sequence pairwise error probability. Also, it is shown that diversity reception can significantly improve the MLSE error performance     

Clustering-Based Adaptive Channel Estimator for Optical Fiber Communication Systems

In this letter, a new clustering-based adaptive channel estimator is proposed for optical fiber communication systems with the maximum-likelihood sequence estimation (MLSE) receiver. The estimator is very effective in estimating the key channel parameters needed by the Viterbi processor without assuming that the channel memory length is known a priori to the receiver. Moreover, the application of the proposed channel estimator can induce a complexity-reduced MLSE receiver.     

Adaptive maximum-likelihood sequence estimation by means ofcombined equalization and decoding in fading environments

This paper proposes an adaptive maximum-likelihood sequence estimation (MLSE) by means of combined equalization and decoding, i.e., adaptive combined MLSE, which employs separate channel estimation for respective states in the Viterbi algorithm. First, an approximate metric including channel estimation is derived analytically for this proposed adaptive combined MLSE. Secondly, procedures to accomplish blind equalization are investigated for the proposed MLSE. Finally, its excellent BER performance on fast time-varying fading channels is confirmed by computer simulation, when the proposed MLSE operates as a blind equalizer     

Comparison of DFE and MLSE Receiver Performance on HF Channels

Data communication at rates near or above 2 kbits/s on 3 kHz-baadwidth HF radio channels is subject to impairment from severe linear dispersion, rapid channel time variation, and severe fading. In this investigation, recorded 2.4 kbit/s QPSK signals received from HF channels were processed to extract a time-varying estimate of the channel impulse response. From the estimated channel impulse responses, performance-related parameters were computed for ideal matched filter reception, maximum-likelihood sequence-estimation (MLSE), and decision feedback equalization (DFE). The results indicated that the simpler DFE receiver suffered only a small theoretical performance degradation relative to the more complex MLSE receiver. Other HF channel impulse response statistics were also obtained to shed light on equalization and filter adaptation techniques.     

A Maximum-Likelihood Sequence Estimator with Decision-Feedback Equalization

A decision-feedback equalizer (DFE) is proposed as a prefilter which limits the complexity of a maximum-likelihood sequence estimator (MLSE) implemented by the Viterbi algorithm (VA) for channels having a long impulse response. By imbedding a DFE into the structure of the MLSE, the overall impulse response of the system is truncated to a short duration. With this practical receiver, a compromise may be made between performance and complexity by properly choosing the duration of a desired impulse response. A technique is also developed to estimate the performance of the receiver numerically, taking into account the effect of incorrect decision feedback on the VA. Analysis and computer simulation over a single-pole channel show that the proposed scheme can reduce the complexity of the MLSE while retaining much of its performance advantages.     

Adaptive combined DFE/MLSE techniques for ISI channels

By embedding a decision-feedback equalizer (DFE) into the structure of a maximum-likelihood sequence estimator (MLSE), an adaptive combined DFE/MLSE scheme is proposed. In this combined DFE/MLSE, the embedded DFE has three functions: (i) prefiltering the received signals and truncating the equivalent channel response into the desired one, (ii) compensating for channel distortions, and (iii) providing the MLSE detector with predicted values of input signals. Since the embedded MLSE detector operates on the predicted signals the detected symbols at the output of the DFE/MLSE do not suffer any delay and can be directly fed back into the embedded DFE so that the error propagation, which usually takes place in a conventional DFE, can be greatly reduced. Analytical and simulation results indicate that the performance is significantly improved by the DFE/MLSE compared to the conventional DFE while its computation complexity is much less than that of the conventional MLSE receiver. The combined DFE/MLSE can use different adaptive structures (block-updating, sliding window updating or symbol-by-symbol updating) to meet different performance objectives. Moreover, the proposed DFE/MLSE provides a trade-off between performance and complexity with a parameter m representing the MLSE detection depth as well as the number of predicting steps of the embedded DFE. For some particular values of m, this scheme is capable of emulating the conventional DFE, MLSE-VA, adaptive LE-MLSE equalizer, adaptive DDFSE, and adaptive BDFE without detection delay