Distributed Channel Selection for Interference Mitigation in Dynamic Environment: A Game-Theoretic Stochastic Learning Solution

In this paper, we investigate the problem of distributed channel selection for interference mitigation in a canonical communication network. The channel is assumed time-varying, and the active user set is considered dynamically variable due to the specific service requirement. This problem is formul...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on vehicular technology 2014-11, Vol.63 (9), p.4757-4762
Main Authors: Jianchao Zheng, Yueming Cai, Yuhua Xu, Anpalagan, Alagan
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Channels
Communication networks
Dynamics
Games
Heuristic algorithms
Information exchange
Interference
Learning
Manganese
Optimization
Vehicle dynamics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we investigate the problem of distributed channel selection for interference mitigation in a canonical communication network. The channel is assumed time-varying, and the active user set is considered dynamically variable due to the specific service requirement. This problem is formulated as an exact potential game, and the optimality property of the solution to this problem is first analyzed. Then, we design a low-complexity fully distributed no-regret learning algorithm for channel adaptation in a dynamic environment, where each active player can independently and automatically update its action with no information exchange. The proposed algorithm is proven to converge to a set of correlated equilibria with a probability of 1. Finally, we conduct simulations to demonstrate that the proposed algorithm achieves near-optimal performance for interference mitigation in dynamic environments.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2014.2311496