Efficient Signal Processing Techniques in Advanced Wireless Systems

Adnan Khan

ISBN 10: 3838374029 / ISBN 13: 9783838374024

Published by LAP LAMBERT Academic Publishing Jul 2010, 2010

About this Item

Neuware -Significant performance gains are achievable in wireless systems using a Multi-Input Multi-Output (MIMO) communication system employing multiple antennas.This architecture is suitable for higher data rate multimedia communications.One of the challenges in building a MIMO system is the tremendous processing power required at the receiver. MIMO Symbol detection involves detecting symbol from a complex signal at the receiver. Nature Inspired techniques for non-linear approximate MIMO detectors with a low complexity near-optimal performance is presented. The approach is particularly attractive as Swarm Intelligence (SI) is well suited for physically realizable, real- time applications, where low complexity and fast convergence is of absolute importance. Application of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms is studied. While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, it is established that Swarm Intelligence optimized MIMO detection algorithms gives near-optimal Bit Error Rate (BER) performance, thereby reducing the ML computational complexity significantlyBooks on Demand GmbH, Überseering 33, 22297 Hamburg 168 pp. Englisch.

Seller Inventory # 9783838374024

Bibliographic Details

• Title: Efficient Signal Processing Techniques in Advanced Wireless Systems
• Publisher: LAP LAMBERT Academic Publishing Jul 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 3838374029
• ISBN 13: 9783838374024
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

Significant performance gains are achievable in wireless systems using a Multi-Input Multi-Output (MIMO) communication system employing multiple antennas.This architecture is suitable for higher data rate multimedia communications.One of the challenges in building a MIMO system is the tremendous processing power required at the receiver. MIMO Symbol detection involves detecting symbol from a complex signal at the receiver. Nature Inspired techniques for non-linear approximate MIMO detectors with a low complexity near-optimal performance is presented. The approach is particularly attractive as Swarm Intelligence (SI) is well suited for physically realizable, real- time applications, where low complexity and fast convergence is of absolute importance. Application of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms is studied. While an optimal Maximum Likelihood (ML) detection using an exhaustive search method is prohibitively complex, it is established that Swarm Intelligence optimized MIMO detection algorithms gives near-optimal Bit Error Rate (BER) performance, thereby reducing the ML computational complexity significantly

About the Author

Dr Adnan A. Khan did PhD from Centre for Advanced Studies in Engineering(CASE)UET Taxila, Pakistan in Wireless Systems.He is working in College of Telecommunication Engineering (NUST).His research interests include Multi-Input Multi-Output (MIMO)-OFDM, Cooperative Communication, Software Defined Radio's (SDR)and Satellite Communication System.