title: Receiver diversity combining using evolutionary algorithms in Rayleigh fading channel.
abstract: In diversity combining at the receiver, the output signal-to-noise ratio (SNR) is often maximized by using the maximal ratio combining (MRC) provided that the channel is perfectly estimated at the receiver. However, channel estimation is rarely perfect in practice, which results in deteriorating the system performance. In this paper, an imperialistic competitive algorithm (ICA) is proposed and compared with two other evolutionary based algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA), for diversity combining of signals travelling across the imperfect channels. The proposed algorithm adjusts the combiner weights of the received signal components in such a way that maximizes the SNR and minimizes the bit error rate (BER). The results indicate that the proposed method eliminates the need of channel estimation and can outperform the conventional diversity combining methods.
authors.affiliation: Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Mohsen
authors.initials: M
authors.lastname: Akbari
authors.affiliation: Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Mohsen Riahi
authors.initials: MR
authors.lastname: Manesh
authors.affiliation: Faculty of Engineering, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia.
authors.forename: Ayman A
authors.identifier: 0000-0003-4754-9271
authors.initials: AA
authors.lastname: El-Saleh
authors.affiliation: Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Ahmed Wasif
authors.identifier: 0000-0003-4321-5880
authors.initials: AW
authors.lastname: Reza
mesh_terms: D000465:Algorithms; D059629:Signal-To-Noise Ratio; D059015:Wireless Technology