RDRL A Recurrent Deep Reinforcement Learning Scheme for Dynamic Spectrum Access in Reconfigurable Wireless Networks

2021 ◽  
pp. 1-1
Author(s):  
Miaojiang Chen ◽  
Anfeng Liu ◽  
Wei Liu ◽  
Kaoru Ota ◽  
Mianxiong Dong ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Reinforcement Learning ◽  
Dynamic Spectrum Access ◽  
Dynamic Spectrum ◽  
Spectrum Access ◽  
Learning Scheme

Reinforcement learning based dynamic spectrum access in cognitive Internet of Vehicles

2021 ◽  
Vol 18 (7) ◽  
pp. 58-68
Author(s):  
Xin Liu ◽  
Can Sun ◽  
Mu Zhou ◽  
Bin Lin ◽  
Yuto Lim
Keyword(s):  
Reinforcement Learning ◽  
Dynamic Spectrum Access ◽  
Dynamic Spectrum ◽  
Spectrum Access ◽  
Internet Of Vehicles

Game Theory for Resource Allocation in Wireless Networks

2011 ◽  
pp. 335-352 ◽  
Author(s):  
Danda B. Rawat ◽  
Chandra Bajracharya ◽  
Gongjun Yan
Keyword(s):  
Game Theory ◽  
Resource Allocation ◽  
Wireless Networks ◽  
Dynamic Spectrum Access ◽  
Optimal Allocation ◽  
Optimization Technique ◽  
Dynamic Spectrum ◽  
Spectrum Access ◽  
Wireless Technologies ◽  
Service Areas

Wireless technologies and devices are becoming increasingly ubiquitous in modern society. Wireless resources are natural and fixed, whereas wireless technologies and devices are increasing day-by-day, resulting in spectrum scarcity. As a consequence, efficient use of limited wireless resources has become an issue of vital importance in wireless systems. As demand increases, management of limited wireless resources for optimal allocation becomes crucial. Optimal allocation of limited wireless resources results in quick and reliable dissemination of information to larger service areas. Recently, game theory has emerged as an efficient tool to help optimally allocate wireless resources. Game theory is an optimization technique based on strategic situations and decision-making, and has found its application in numerous fields. The first part of this chapter presents a review of game theory and its application in resource allocation at different layers of the protocol stack of the network model. As shown by a recent study, static assignment of frequency spectrum by governmental bodies, such as FCC (Federal Communications Commission) in the United States, is inefficient since the licensed systems do not always fully utilize their frequency bands. In such a scenario, unlicensed secondary (cognitive radio) users can identify the idle spectrum bands and use them opportunistically. In order to access the licensed spectrum dynamically and opportunistically, the dynamic spectrum access functionality needs to be incorporated in the next generation (XG) wireless networks. Different game theory approaches for dynamic spectrum access are discussed in the second part of the chapter.

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