Multi-channel Maximum Likelihood Sequence Estimation
نویسنده
چکیده
In mobile radio communications, antenna arrays can be used to improve the quality and/or the capacity of the communication system. The combination of an antenna array and maximum likelihood sequence detection (MLSE) is studied here. Diierent realizations of the multi-channel MLSE are presented. Although equivalent in performance, it is pointed out that one of them, the multi-dimensional matched lter approach, is superior in terms of computational complexity when more than one antenna is used. For completeness, temporally colored noise is included in the formalism.
منابع مشابه
Capacity Analysis of Single-User and Multi-User MIMO with Split MLSE Adaptive Equalization
It is well known that the employment of multiple antennas at both the transmitter and receiver increases the overall system capacity. This paper presents an overview of capacity variation in single-user and multiuser multiple-inputmultiple-output (MIMO) systems in Additive White Gaussian Noise (AWGN) and Rayleigh fading channels under the assumption that channel state information (CSI) is known...
متن کاملMaximum likelihood joint channel and data estimation using genetic algorithms
A batch blind equalization scheme is developed based on maximum likelihood joint channel and data estimation. In this scheme, the joint maximum likelihood optimization is decomposed into a twolevel optimization loop. A micro genetic algorithm is employed at the upper level to identify the unknown channel model, and the Viterbi algorithm is used at the lower level to provide the maximum likeliho...
متن کاملJoint Synchronization, Channel Length Estimation, and Channel Estimation for the Maximum Likelihood Sequence Estimator for High Speed Wireless Communications
The performance of channel-estimation-based maximum likelihood sequence estimator (MLSE) depends on the accuracy of the channel estimate. Conventional least-squares channel estimators preset a fixed length for the channel. For wireless communications, however, the actual length of the channel is environment-dependent and in general unknown. It is therefore desirable to modify conventional chann...
متن کاملBlind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems
A blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of singleinput multiple-output (SIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative optimisation loop. An efficient global optimisation algorithm called the repeated weighted boosting search is employed at the upper level to optimally identify th...
متن کاملGenetic algorithm optimisation for maximum likelihood joint channel and data estimation
A novel blind equalisation scheme is developed based on maximum likelihood (ML) joint channel and data estimation. In this scheme, the joint ML optimisation is decomposed into a two-level optimisation loop. An e cient version of genetic algorithms (GAs), known as a micro GA, is employed at the upper level to identify the unknown channel model and the Viterbi algorithm (VA) is used at the lower ...
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 1997