Receiver diversity combining using evolutionary algorithms in Rayleigh fading channel.

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...

Full description

Bibliographic Details
Published in:Scientific World Journal pp. 128195 - 128196
Main Authors: Akbari, Mohsen, Manesh, Mohsen Riahi, El-Saleh, Ayman A, Reza, Ahmed Wasif
Format: research Journal Article
Published: Wiley-Blackwell 2014
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103835226&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 103835226
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        1537744X
        1BX5
      jtl: Scientific World Journal
      issn: 1537744X
      maglogo: N
    pubinfo:
      dt: 2014
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        103835226
        NLM25045725
        2012655902
        10.1155/2014/128195
        NLM25045725
        PMC4089946
        103835226
      ppf: 128195
      ppct: 1
      formats:
      tig:
        atl: Receiver diversity combining using evolutionary algorithms in Rayleigh fading channel.
      aug:
        au:
          Akbari, Mohsen
          Manesh, Mohsen Riahi
          El-Saleh, Ayman A
          Reza, Ahmed Wasif
        affil: Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia.
      sug:
        subj:
          Algorithms
          Sensitivity and Specificity
          Wireless Communications
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N