A game-theoretical paradigm for collaborative and distributed power control in wireless networks

The wireless revolution requires future wireless networks the capability of intelligently optimizing the spectrum by collaborating and using autonomy to determine not just the best use of the spectrum for its own system, but the best use of spectrum for other systems that share the same spectrum ban...

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Vydáno v:Annales des télécommunications Ročník 79; číslo 1-2; s. 1 - 14
Hlavní autoři: Ta, Duc-Tuyen, Nguyen-Thanh, Nhan, Nguyen, Duy H. N., Nguyen, Van-Tam
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 01.02.2024
Springer Nature B.V
Témata:
Algorithms
Approximation
Circuits
Collaboration
Communications Engineering
Communications systems
Computer Communication Networks
Convergence
Energy efficiency
Engineering
Frequencies
Game theory
Games
Information and Communication
Information Systems and Communication Service
Networks
Optimization
Power control
R & D/Technology Policy
Receivers & amplifiers
Signal,Image and Speech Processing
Spectrum allocation
Transmitters
Utility functions
Wireless networks
ISSN:0003-4347, 1958-9395
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Shrnutí:The wireless revolution requires future wireless networks the capability of intelligently optimizing the spectrum by collaborating and using autonomy to determine not just the best use of the spectrum for its own system, but the best use of spectrum for other systems that share the same spectrum bands. How to develop the wireless paradigm of collaboration, therefore, is a crucial question. In this paper, we discuss how to model collaborative power control in a wireless interference network, where users share the same frequency band. By collaborating with other users, each user exchanges information to maximize not only its own performance but also others’ performances. A game theory framework is developed to determine the optimal power allocation. The proposed framework possesses several advantages over conventional methods, such as low complexity and fast converging algorithmic solutions, distributed implementation, and better user fairness. Simulation results state the proposed approach provides better fairness between users’ data rates, higher performance in the aggregate rate, and lower convergence time.
Bibliografie:ObjectType-Article-1
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ISSN:0003-4347
1958-9395
DOI:10.1007/s12243-023-00976-5