Spectrum sharing via hybrid cognitive players evaluated by an M/D/1 queuing model

Khashayar Kotobi, Sven G. Bilén

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

We consider a cognitive wireless network in which users adopt a spectrum sharing strategy based on cooperation constraints. The majority of cognitive radio schemes bifurcate the role of players as either cooperative or non-cooperative. In this work, however, we modify this strategy to one in which players are hybrid, i.e., both cooperative and non-cooperative. Using a Stackelberg game strategy, we evaluate the improvement in performance of a cognitive radio network with these hybrid cognitive players using an M/D/1 queuing model. We use a novel game strategy (which we call altruism) to “police” a wireless network by monitoring the network and finding the non-cooperative players. Upon introduction of this new player, we present and test a series of predictive algorithms that shows improvements in wireless channel utilization over traditional collision-detection algorithms. Our results demonstrate the viability of using this strategy to inform and create more efficient cognitive radio networks. Next, we study a Stackelberg competition with the primary license holder as the leader and investigate the impact of multiple leaders by modeling the wireless channel as an M/D/1 queue. We find that in the Stackelberg game, the leader can improve its utility by influencing followers’ decisions using its advertised cost function and the number of followers accepted in the network. The gain in utility monotonically increases until the network is saturated. The Stackelberg game formulation shows the existence of a unique Nash equilibrium using an appropriate cost function. The equilibrium maximizes the total utility of the network and allows spectrum sharing between primary and secondary cognitive users.

Original languageEnglish (US)
Article number85
JournalEurasip Journal on Wireless Communications and Networking
Volume2017
Issue number1
DOIs
StatePublished - Dec 1 2017

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All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Science Applications
  • Computer Networks and Communications

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