Approximate Maximum Likelihood Sequence Detection
نویسنده
چکیده
The problem of multiuser detection in asynchronous Direct-Sequence Code-Division Multiple-Access systems with residual errors in timing and amplitude estimation is addressed. Prior work has shown that the maximum-likelihood (ML) solution is sensitive to timing errors as small as a fraction of a chip period. In this paper, residual errors in both synchronization and fading coeecient estimation are assumed. A modiied ML metric is derived with the knowledge of the assumed statistics of the residual errors. As a closed-form solution does not exist, an approximate ML metric is derived based on perturbation theory. A recursive implementation scheme for the approximate formulation is proposed with the aim of reducing the complexity and facilitating dynamic updates of the receiver parameters. Performance is investigated via simulation and analytical bounds for both Gaussian and at Rayleigh fading channels.
منابع مشابه
Turbo Decoding as an Approximative Iterative Solution to Maximum Likelihood Sequence Detection
Despite the considerable research effort towards the analysis and understanding of the nature of turbo decoding, a clear identification of the underlying optimization problem the turbo decoder attempts to solve is still missing. In this paper, we link the turbo decoding algorithm to maximum likelihood (ML) sequence detection by demonstrating how the turbo decoder can be systematically derived s...
متن کاملHopfield Neural Network for UWB Multiuser Detection
-The Hopfield neural network (HNN) is introduced in the paper and is proposed as an effective multiuser detection in direct sequence-ultra-wideband (DS-UWB) systems. It can approximate to maximum likelihood (ML) detector by mathematical analysis. According to the HNN-based technique, the computer simulation results show that they have good performances and much lower computational complexity in...
متن کاملAnalysis of Hybrid Censored Data from the Lognormal Distribution
The mixture of Type I and Type II censoring schemes, called the hybrid censoring. This article presents the statistical inferences on lognormal parameters when the data are hybrid censored. We obtain the maximum likelihood estimators (MLEs) and the approximate maximum likelihood estimators (AMLEs) of the unknown parameters. Asymptotic distributions of the maximum likelihood estimators are used ...
متن کاملRates of nucleotide substitution and mammalian nuclear gene evolution. Approximate and maximum-likelihood methods lead to different conclusions.
Rates and patterns of synonymous and nonsynonymous substitutions have important implications for the origin and maintenance of mammalian isochores and the effectiveness of selection at synonymous sites. Previous studies of mammalian nuclear genes largely employed approximate methods to estimate rates of nonsynonymous and synonymous substitutions. Because these methods did not account for major ...
متن کاملBearing Fault Detection Based on Maximum Likelihood Estimation and Optimized ANN Using the Bees Algorithm
Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estima...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1999