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Multi-relay selection in energy-harvesting cooperative wireless networks: game-theoretic modeling and analysis

Author

Listed:
  • Mohammed W. Baidas

    (Kuwait University)

  • Emad Alsusa

    (University of Manchester)

  • Motasem Alfarra

    (King Abdullah University of Science and Technology)

  • Mubarak Al-Mubarak

    (Ohio State University)

Abstract

This paper studies distributed multi-relay selection in energy-harvesting cooperative wireless networks and models it as an Indian Buffet Game (IBG). Particularly, the IBG is utilized to model the multi-relay selection decisions of network source nodes, while accounting for negative network externality. Two scenarios are considered: (1) constrained selections (CS), and (2) unconstrained selections (US). In the former scenario, each source is constrained to a maximum number of relay selections; while in the latter scenario, the source nodes can select as many relays as possible. Since the relays are energy-harvesting—and thus intermittently harvest random amounts of energy—the accumulated energy at each relay is unknown to the source nodes, leading to uncertain relays’ energy states. In turn, a non-Bayesian learning (NBL) algorithm is devised for the source nodes to learn the relays’ energy states. After that, two distributed best-response (BR) recursive algorithms, namely BR-CS and BR-US, are proposed to allow the source nodes to make multi-relay selection decisions, while guaranteeing subgame perfect Nash equilibrium. Simulation results are presented to verify the efficacy of the proposed distributed NBL and multi-relay selection algorithms. Specifically, the NBL is shown to efficiently learn the true relays’ energy states. More importantly, the BR-CS algorithm is shown to be comparable to the centralized multi-relay selection—and superior to other relay selection schemes—in terms of network sum-rate improvement (and utility). Lastly, the number of relay selections of the BR-CS algorithm must be constrained to the minimum so as to reduce complexity and fully exploit diversity gains.

Suggested Citation

  • Mohammed W. Baidas & Emad Alsusa & Motasem Alfarra & Mubarak Al-Mubarak, 2020. "Multi-relay selection in energy-harvesting cooperative wireless networks: game-theoretic modeling and analysis," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 73(2), pages 289-311, February.
  • Handle: RePEc:spr:telsys:v:73:y:2020:i:2:d:10.1007_s11235-019-00611-6
    DOI: 10.1007/s11235-019-00611-6
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    References listed on IDEAS

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    1. Lina Zheng & Chao Zhai & Ju Liu, 2018. "Alternate energy harvesting and information relaying in cooperative AF networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(3), pages 523-533, July.
    2. Buonocore, Aniello & Pirozzi, Enrica & Caputo, Luigia, 2009. "A note on the sum of uniform random variables," Statistics & Probability Letters, Elsevier, vol. 79(19), pages 2092-2097, October.
    3. Admoon Andrawes & Rosdiadee Nordin & Mahamod Ismail, 2019. "Wireless Energy Harvesting with Cooperative Relaying under the Best Relay Selection Scheme," Energies, MDPI, vol. 12(5), pages 1-22, March.
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