Distributed Channel selection in multilink MISO networks: Stochastic learning under time-varying channel states

• Published in: 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC) pp. 1036 - 1040
• Main Authors: Li-Chuan Tseng, Feng-Tsun Chien, Chang, Ronald Y.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-09-2014
• Subjects: Convergence; Distributed channel selection; Games; Interference; Multilink MISO; Potential game; Receivers; Stochastic learning; Stochastic processes; Time-varying channels; Transmitters
• ISSN: 2166-9570
• DOI: 10.1109/PIMRC.2014.7136319

In this paper, we study the channel selection problem for selfish and altruistic precoding in multilink multiple-input single-output (MISO) networks from a distributed game-theoretic perspective. Our goal is to find for each link a proper channel selection strategy that is robust against time-varying channel states. This motivates the development of stochastic learning that finds Nash equilibrium (NE) of an expected game. The convergence properties of the proposed learning algorithm are theoretically and numerically verified. The proposed algorithm demonstrates good sum-rate performance in the system-level simulation of a multilink MISO network based on the 3GPP-LTE model.