Abstract
In multiuser optical wireless communications (OWC), the multiuser interference becomes significant as the number of users increases. This would lead to a poor quality of service with a low signal-to-interference-plus-noise-ratio (SINR) or even a failure of service. In this paper, we consider coordination among multiple users to maximize the capacity in a multiple-input single-output (MISO) interference-limited discrete-time Poisson channel from a game-theoretic perspective. With power constraints imposed, the resource allocation problem can be interpreted as a downlink beamforming game. To improve the capacity in a power- and interference-limited channel, we model the problem as a cooperative game and propose an altruistic algorithm using the Nash bargaining, where each self-interested user attempts to maximize its capacity through cooperation. Moreover, to compare the performance with a non-game-theoretic approach, a convex optimization framework is developed. It is shown that the proposed Nash bargaining yields significant performance improvement when compared with the Nash equilibrium in the non-cooperative game. It is also found that in a power- and interference-limited channel, self-interested but cooperative users can provide a significant performance improvement over the convex optimization based non-game-theoretic approach.
Highlights
Complementing existing radio frequency technologies, optical wireless communication (OWC) systems with wavelengths ranging from ultraviolet to visible to infrared, offer low-cost solutions with virtually unlimited spectrum, miniaturized transceivers, and high scalability [1]
To improve the capacity in a power- and interference-limited channel, we model the problem as a cooperative game and propose an altruistic algorithm using the Nash bargaining, where each self-interested user attempts to maximize its capacity through cooperation
We propose a game-theoretic approach to maximize the capacity per user using Nash bargaining in a power- and interference-limited optical wireless communications (OWC) system
Summary
Complementing existing radio frequency technologies, optical wireless communication (OWC) systems with wavelengths ranging from ultraviolet to visible to infrared, offer low-cost solutions with virtually unlimited spectrum, miniaturized transceivers, and high scalability [1]. A supervised learning-based ANN framework for the blind signal detection technique for the indoor OWC system was reported [8]. The complex and tedious supervised learning models based on ANN rely heavily on past data to make correct decisions. In power-limited multiuser OWC systems, all users compete for resources and can interfere with other users. The implementation of interference cancellation technique is not easy in a system where the users are not aware of the coding and modulation schemes of the interfering transmitters. Motivated by these shortcomings, we propose a game-theoretic approach to maximize the capacity per user using Nash bargaining in a power- and interference-limited OWC system. It is assumed that there is no attempt to decode or cancel the interference
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