Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers

Research Article

Cooperation Gain in Incremental LMS Adaptive Networks with Noisy Links

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  • @INPROCEEDINGS{10.1007/978-3-319-11629-7_16,
        author={Azam Khalili and Wael Bazzi and Amir Rastegarnia},
        title={Cooperation Gain in Incremental LMS Adaptive Networks with Noisy Links},
        proceedings={Signal Processing and Information Technology. Second International Joint Conference, SPIT 2012, Dubai, UAE, September 20-21, 2012, Revised Selected Papers},
        proceedings_a={SPIT},
        year={2014},
        month={11},
        keywords={adaptive networks cooperation gain incremental step-size},
        doi={10.1007/978-3-319-11629-7_16}
    }
    
  • Azam Khalili
    Wael Bazzi
    Amir Rastegarnia
    Year: 2014
    Cooperation Gain in Incremental LMS Adaptive Networks with Noisy Links
    SPIT
    Springer
    DOI: 10.1007/978-3-319-11629-7_16
Azam Khalili1,*, Wael Bazzi2,*, Amir Rastegarnia1,*
  • 1: Malayer University
  • 2: American University in Dubai
*Contact email: a.khalili@ieee.org, wbazzi@aud.edu, a_rastegar@ieee.org

Abstract

In this paper, we study the influence of noisy links on the effectiveness of cooperation in incremental LMS adaptive network (ILMS). The analysis reveals the important fact that under noisy communication, cooperation among nodes may not necessarily result in better performance. More precisely, we first define the concept of cooperation gain and compute it for the ILMS algorithm with ideal and noisy links. We show that the ILMS algorithm with ideal links outperforms the non-cooperative scheme for all values of step-size (cooperation gain is always bigger than 1). On the other hand, in the presence of noisy links, cooperation gain is not always bigger than 1 and based on the channel and data statistics, for some values of step-size, non-cooperative scheme outperforms the ILMS algorithm. We presented simulation results to clarify the discussions.