Maximum likelihood decoding of uncoded and coded PSK signalsequences transmitted over Rayleigh flat-fading channels

The problem of maximum likelihood (ML) detection for uncoded and coded M-PSK signals on Rayleigh fading channels is investigated. It is shown that, if the received signal is sampled at baud-rate, a ML receiver employing per-survivor processing can be implemented. The error rate performance of this receiver is evaluated by means of computer simulations and its limitations are discussed. In addition, it is shown that, on a fast fading channel, the error floor in the BER curve can be appreciably lowered if more than one received signal sample per symbol interval is processed by the receiver algorithm, Finally, a sub-optimum two-stage receiver structure for interleaved coded PSK systems is proposed. Its error rate performance is assessed for simple trellis-coded modulation schemes and compared to that provided by other receiver structures     

Maximum likelihood sequence estimation of differentially encoded PSK signals transmitted over Rayleigh frequency-flat fading channels

The problem of maximum likelihood (ML) detection of differentially encodedM-PSK signals on Rayleigh fading channels is investigated. It is shown that the solution to this problem can be easily related to previous results [1] and leads to the implementation of a receiver structure based on the Viterbi algorithm and employing per-survivor processing. The error rate performance of this receiver is evaluated by means of computer simulations for both coded and uncoded systems.     

Multisampling receivers for uncoded and coded PSK signal sequencestransmitted over Rayleigh frequency-flat fading channels

An algorithm, based on previous work [Vitetta and Taylor 1994, 1995], for the detection of coded and uncoded PSK sequences transmitted on a frequency-flat fading channel is investigated. It is based on the Viterbi algorithm and processes more than one signal sample per signaling interval. Its performance is evaluated by means of computer simulations for both uncoded and coded systems     

Comment on “estimate of channel capacity in Rayleigh fadingenvironment”

Lee (see ibid., vol.39, p.187, no.8, 1990) proposed a very simple and elegant model for estimating the capacity of slowly fading channels. A small error in his paper, however, has led to an inexact picture. We correct that inaccuracy. As a consequence, the loss in capacity of a Rayleigh fading channel with respect to the additive white Gaussian noise (AWGN) channel turns out to be negligible for all values of the signal-to-noise ratio that are of interest. Furthermore, we extend the analytical results to the situation with M-branch diversity and Ricean fading channels. The lower moments of the associated distributions, i.e., of the χ²-distribution (Nakagami with integer m-parameter) and Rice distribution agree when the parameters of the distribution are suitably chosen. With that choice of parameters, the capacities of the M-branch diversity and of the Ricean fading channel become almost identical     

Maximum likelihood decoding of RLL-FEC array codes on partial response channels

A technique for performing maximum likelihood decoding (MLD) of RLL-FEC array codes on partial response channels is introduced. Attention is focused on the (1-D) channel and a (16, 9, 4) code having a maximum runlength constraint of 6. However, the idea is applicable to all partial response channels and RLL-FEC array codes.<>     

Maximum likelihood sequence estimation of CPM signals transmittedover Rayleigh flat-fading channels

A method for the sequential updating of log-likelihood functions for maximum-likelihood sequence estimation is presented. It is shown that, in a general case, this method can be implemented using Kalman filtering techniques. For the special case of Rayleigh flat fading and continuous phase modulation (CPM) signaling, this approach is shown to lead to an attractive receiver structure. This type of receiver, called the linear predictive receiver, can be implemented in the form of the Viterbi algorithm with the trellis updates being computed using a bank of finite pulse response (FIR) filter and square operations. Simulation results are presented that demonstrate the superiority of the linear predictive receiver over receivers employing differential detection, in the presence of fast fading. It is shown that the optimal linear predictive receiver does not possess an irreducible error rate for a class of Rayleigh fading channels used to model terrestrial mobile channels     

Maximum likelihood soft decoding of binary block codes and decodersfor the Golay codes

Maximum-likelihood soft-decision decoding of linear block codes is addressed. A binary multiple-check generalization of the Wagner rule is presented, and two methods for its implementation, one of which resembles the suboptimal Forney-Chase algorithms, are described. Besides efficient soft decoding of small codes, the generalized rule enables utilization of subspaces of a wide variety, thereby yielding maximum-likelihood decoders with substantially reduced computational complexity for some larger binary codes. More sophisticated choice and exploitation of the structure of both a subspace and the coset representatives are demonstrated for the (24, 12) Golay code, yielding a computational gain factor of about 2 with respect to previous methods. A ternary single-check version of the Wagner rule is applied for efficient soft decoding of the (12, 6) ternary Golay code     

Maximum likelihood decoding of certain Reed - Muller codes (Corresp.)

We present an efficient maximum likelihood decoding algorithm for the punctured binary Reed-Muller code of order(m - 3)and length2^{m} - 1, M geq 3, and we give formulas for the weight distribution of coset leaders of such codes.     

一种LFM信号最大似然估计模型与参数估计快速算法

从最大似然估计模型入手,提出了一种适合在一般高斯噪声环境（包括色噪声）下LFM信号目标的参数估计模型和基于此估计模型的调频斜率和初始频率估计的快速算法。此方法获得了最大似然方法估计精度高的优点,且运算量比传统的最大似然方法大大降低。另外推导出了一般高斯环境下的LFM参数估计的CRB界,为一般高斯环境下的估计的参数的方差提供实际下界。     

Comment on the “Unnecessary assumption of statisticalindependence between reference signal and filter weights in feedforwardadaptive systems”

Minkoff (see IEEE Trans. Signal Processing, vol.45, p.2993-3004, 1997) presented a formulation in which the time-evolving weight-iteration equation for random signals is derived without the necessity of invoking the usual unsatisfactory assumption that is customarily made, namely, that the weights W and the reference signal X the weight-iteration equation are statistically independent. Minkoff neglected, however, to give a physical argument for it. That is, in this derivation, it is not necessary for W to be independent of X but only of XX which does not contain the phase information of X. The off-diagonal terms of XX contain only phase differences, which could be produced by an infinite number of different, arbitrary Xs     

Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks

In this paper, we revisit the problem of fusing decisions transmitted over fading channels in a wireless sensor network. Previous development relies on instantaneous channel state information (CSI). However, acquiring channel information may be too costly for resource constrained sensor networks. In this paper, we propose a new likelihood ratio (LR)-based fusion rule which requires only the knowledge of channel statistics instead of instantaneous CSI. Based on the assumption that all the sensors have the same detection performance and the same channel signal-to-noise ratio (SNR), we show that when the channel SNR is low, this fusion rule reduces to a statistic in the form of an equal gain combiner (EGC), which explains why EGC is a very good choice with low or medium SNR; at high-channel SNR, it is equivalent to the Chair-Varshney fusion rule. Performance evaluation shows that the new fusion rule exhibits only slight performance degradation compared with the optimal LR-based fusion rule using instantaneous CSI.     

Maximum likelihood estimation and MUSIC in array localization signal processing: A review

Algorithms to treat the maximum likelihood (ML) estimation problem in array localization signal processing are reviewed, including the alternating projection method, the iterative quadratic maximum likelihood method and the expectation-maximization method. The relationship of ML estimators and the MUSIC algorithm is presented. The Cramer-Rao bounds for the deterministic and stochastic models in array localization are summarized. Finally, the problem of the estimation of the number of sources is discussed.     

Comments on “Minimum Duration Outages in Rayleigh Fading Channels“

Closed-form expressions are derived for the minimum duration outage and the probability of outage considered by Lai and Mandayam in the above paper.     

Error performance of multiple-symbol differential detection of PSKsignals transmitted over correlated Rayleigh fading channels

The error performance of multiple-symbol differential detection of uncoded QPSK signals transmitted over correlated Rayleigh fading channels is studied. The optimal detector is presented, along with an exact expression for the corresponding pairwise error event probability. It is shown that multiple-symbol differential detection is a very effective strategy for eliminating the irreducible error floor associated with a conventional differential detector. In all of the cases investigated, a detector with an observation interval as small as two symbols is sufficient for this purpose. It is also found that the error performance of a multiple-symbol differential detector is not sensitive to the mismatch between the decoding metric and the channel fading statistics     

Comment on “Error rate performance of the projectioncode”

For original paper see ibid., vol.44, p.413-15 (1996 April). The present authors provide counterexamples to the expressions for the minimum Hamming distance of the projection codes in the original paper of Li et al     

Turbo decoding as an instance of Pearl's “beliefpropagation” algorithm

We describe the close connection between the now celebrated iterative turbo decoding algorithm of Berrou et al. (1993) and an algorithm that has been well known in the artificial intelligence community for a decade, but which is relatively unknown to information theorists: Pearl's (1982) belief propagation algorithm. We see that if Pearl's algorithm is applied to the “belief network” of a parallel concatenation of two or more codes, the turbo decoding algorithm immediately results. Unfortunately, however, this belief diagram has loops, and Pearl only proved that his algorithm works when there are no loops, so an explanation of the experimental performance of turbo decoding is still lacking. However, we also show that Pearl's algorithm can be used to routinely derive previously known iterative, but suboptimal, decoding algorithms for a number of other error-control systems, including Gallager's (1962) low-density parity-check codes, serially concatenated codes, and product codes. Thus, belief propagation provides a very attractive general methodology for devising low-complexity iterative decoding algorithms for hybrid coded systems     

Maximum likelihood signal processing techniques to detect a steppattern of change in multitemporal SAR images

In this paper, we address the problem of deriving adequate detection and classification schemes to fully exploit the information available in a sequence of SAR images. In particular, we address the case of detecting a step reflectivity change pattern against a constant pattern. Initially we propose two different techniques, based on a maximum likelihood approach, that make different use of prior knowledge on the searched pattern. They process the whole sequence to achieve optimal discrimination capability between regions affected and not affected by a step change. The first technique (KSP-detector) assumes a complete knowledge of the pattern of change, While the second one (USP-detector) is based on the assumption of a totally unknown pattern. A fully analytical expression of the detection performances of both techniques is obtained, which shows the large improvement achievable using longer sequences instead of only two images. By comparing the two techniques it is also apparent that KSP achieves better performance, but the USP-detector is more robust. As a compromise solution, a third technique is then developed, assuming a partial knowledge of the pattern of change, and its performance is compared to the previous ones. The practical effectiveness of the technique on real data is shown by applying the USP-detector to a sequence of 10 ERS-1 SAR images of forest and agricultural areas, which is also used to validate the theoretical results     

Comment on “Text compression as rule-based patternrecognition”; “Text compression using rule basedencoder”

The original authors have designed rule based compression algorithms (RBE) and compared them with the well known Lempel Ziv family of algorithms (LZ) [1992/1993]. They concluded that their algorithms are superior to LZs (from 50 to 230% better). This comparison is unfair. The reasons for this conclusion are given