Relay Selection Techniques in Cooperative Communication Using Game Theory

  • Authors:
  • Mohsin Nazir;Nandana Rajatheva

  • Affiliations:
  • -;-

  • Venue:
  • CICSYN '10 Proceedings of the 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks
  • Year:
  • 2010

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Abstract

In this paper, the optimized routing or relay selection is discussed for the Cooperative Communication wireless networks. The whole network system performance or Quality of Service (QoS) can not be achieved without the optimal selection of the relay nodes. For this paper, the network performance is analyzed for m number of relays for n number of source nodes. The simulation results are measured by considering four nodes only in half duplex mode. The mentioned techniques can further be applied to more than four nodes in full duplex mode. So, by considering the optimal performance routing for a subset of problem, which can be further applied to whole wireless network. There have been a lot of works in this domain taking advantages from the traditional techniques and algorithms from Game Theory and Algorithms. This paper discusses the scenario of three types of nodes (Source, Relay & Destination). There are many common scenarios in which the additional relay selection or route leads to degrade in the system performance [Braesss Paradox]. And these type of scenarios can be analyzed by using techniques from traditional traffic engineering domain. Dynamic relay selection plays an important role for the increase in system performance. The greedy approach in the wireless network approach leads toward the Nash Equilibrium which may be suboptimal but not optimal. The relay selection procedure can be optimized with application of game theoretic approach to increase the system performance, as a whole. So, the main objective is to present and algorithmic approach to solving the Relay Selection in Cooperative Communication using techniques from Optimization and Game Theory for amplify-and-forward case. The results shows the bandwidth allocation and Nash Equilibrium among the competing users represented as buyer/seller in the open competition market.