Efficient Signal Processing Techniques by Khan Adnan (4 results)

Taschenbuch. Condition: Neu. 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.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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 significantly 168 pp. Englisch.

Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khan AdnanDr 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-In.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.