Journal of Siberian Federal University. Engineering & Technologies / Energy Efficient Dynamic Bid Learning Model for Future Wireless Network

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Issue
Journal of Siberian Federal University. Engineering & Technologies. 2019 12 (1)
Authors
Oloyede, Abdulkarim; Faruk, Nasir; Olawoyin, Lukman; Bello, Olayiwola W.
Contact information
Oloyede, Abdulkarim: Department of Telecommunication Science University of Ilorin Ilorin, Nigeria, ; Faruk, Nasir: Department of Telecommunication Science University of Ilorin Ilorin, Nigeria; ; Olawoyin, Lukman: Department of Telecommunication Science University of Ilorin Ilorin, Nigeria; Bello, Olayiwola W.: Department of Information and Communication Science University of Ilorin Ilorin, Nigeria
Keywords
Q Reinforcement Learning; Spectrum Auction; Dynamic Spectrum Access; Bayesian Learning
Abstract

In this paper, an energy efficient learning model for spectrum auction based on dynamic spectrum auction process is proposed. The proposed learning model is based on artificial intelligence. This paper examines and establishes the need for the users to learn their bid price based on information about the previous bids of the other users in the system. The paper shows that using Q reinforcement learning to learn about the bids of the users during the auction process helps to reduce the amount of energy consumed per file sent for the learning users. The paper went further to modify the traditional Q reinforcement learning process and combined it with Bayesian learning because of the deficiencies associated with Q reinforcement learning. This helps the exploration process to converge faster thereby, further reducing the energy consumption by the system

Pages
113-125
Paper at repository of SibFU
https://elib.sfu-kras.ru/handle/2311/71357

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