Title
Reduced Complexity Optimum Detector For Block Data Transmission Systems
Abstract
Block Data Transmission Systems (BDTS) are used in high-speed wireless communication systems with time dispersive channel characteristics. In such systems, blocks of data are separated by zeros to mitigate the effect of Inter-Symbol-Interference (ISI) between the blocks. An optimal detection process employs the Maximum Likelihood Block Detection (MLBD) technique on each block individually in the presence of ISI and Gaussian noise based on the Euclidean distance as an objective function. The detection process is computationally expensive therefore Genetic Algorithms have been used to reduce the overall design complexity. In this work, three types of Genetic Algorithms have been incorporated in the detection process i.e. the conventional GA, Micro GA(mu GA), and Hybrid mu GA to reduce computational load. In particular, a novel training method for Hybrid mu GA has been proposed. Simulation results at 10 dB channel SNR for the BDTS with Hybrid mu GA executes as low as 3,750 number of objective functions evaluation for a block size of 20. The Bit Error Rate (BER) performance of this system is relatively good i.e. around 1 dB inferior to the BDTS using the Exhaustive Search method that requires as many as 2(20) number of objective functions evaluation.
Year
DOI
Venue
2009
10.1587/elex.6.1649
IEICE ELECTRONICS EXPRESS
Keywords
Field
DocType
Block Transmission, Inter Symbol Interference, dispersive channels, genetic algorithms, additive white gaussian noise
Block size,Brute-force search,Computer science,Block (data storage),Communication channel,Electronic engineering,Gaussian noise,Additive white Gaussian noise,Genetic algorithm,Bit error rate
Journal
Volume
Issue
ISSN
6
23
1349-2543
Citations 
PageRank 
References 
5
0.75
3
Authors
3
Name
Order
Citations
PageRank
SPK. Babu150.75
M. F. M. Salleh2204.37
Farid Ghani383.31