A game theoretic approach to wireless body area networks interference control

Alabdel Abass, Ahmed A.; Alshaheen, Hisham; Takruri, Haifa

Abstract

In this paper we consider a scenario where there are two wireless body area networks (WBANs) interfere with each other from a game theoretic perspective. In particular, we envision two WBANs playing a potential game to enhance their performance by decreasing interference to each other. Decreasing interference extends the sensors' batteries life time and reduces the number of re‐transmissions. We derive the required conditions for the game to be a potential game and its associated the Nash equilibrium (NE). Specifically, we formulate a game where each WBAN has three strategies. Depending on the payoff of each strategy, the game can be designed to achieve a desired NE. Furthermore, we employ a learning algorithm to achieve that NE. In particular, we employ the Fictitious play (FP) learning algorithm as a distributed algorithm that WBANs can use to approach the NE. The simulation results show that the NE is mainly a function of the power cost parameter and a reliability factor that we set depending on each WBAN setting (patient). However, the power cost factor is more dominant than the reliability factor according to the linear cost function formulation that we use throughout this work.

Citation

Alabdel Abass, A. A., Alshaheen, H., & Takruri, H. (in press). A game theoretic approach to wireless body area networks interference control. IET Wireless Sensor Systems, https://doi.org/10.1049/wss2.12077

• Journal Article Type: Article
• Acceptance Date: Mar 23, 2024
• Online Publication Date: Apr 7, 2024
• Deposit Date: Apr 11, 2024
• Publicly Available Date: Apr 15, 2024
• Journal: IET Wireless Sensor Systems
• Print ISSN: 2043-6386
• Electronic ISSN: 2043-6394
• Publisher: Institution of Engineering and Technology (IET)
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1049/wss2.12077
• Keywords: network coding, power control, body area networks, interference suppression, game theory, decision theory, biomedical communication, body sensor networks