TR2010-094

Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View


    •  Shah, V., Mehta, N.B., Yim, R., "Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View", IEEE Transactions on Wireless Communications, Vol. 9, No. 4, pp. 1525-1535, April 2010.
      BibTeX TR2010-094 PDF
      • @article{Shah2010apr,
      • author = {Shah, V. and Mehta, N.B. and Yim, R.},
      • title = {Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View},
      • journal = {IEEE Transactions on Wireless Communications},
      • year = 2010,
      • volume = 9,
      • number = 4,
      • pages = {1525--1535},
      • month = apr,
      • issn = {1536-1276},
      • url = {https://www.merl.com/publications/TR2010-094}
      • }
  • Research Area:

    Communications

Abstract:

Relay selection for cooperative communications promises significant performance improvements, and is, therefore, attracting, considerable attention. While several criteria have been proposed for selecting one or more relays, distributed mechanisms that perform the selection have received relatively less attention. In this paper, we develop a novel, yet simple, asymptotic analysis of a splitting-based multiple access selection algorithm to find the single best relay. The analysis leads to simpler and alternate expressions for the average number of slots required to find the best user. By introducing a new 'contention load' parameter, the analysis shows that the parameter settings used in the existing literature can be improved upon. New and simple bounds are also derived. Furthermore, we propose a new algorithm that addresses the general problem of selecting the best Q greater-than-or-equal 1 relays, and analyze and optimize it. Even for a large number of relays, the scalable algorithm selects the best two relays within 4.406 slots and the best three within 6.491 slots, on average. We also propose a new and simple scheme for the practically relevant case of discrete metrics. Altogether, our results develop a unifying perspective about the general problem of distributed selection in cooperative systems and several other multi-node systems.

 

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