Premium
Spectrum trading algorithm based on memory in cognitive radio network
Author(s) -
Zhang Shibing,
Zhang Guodong,
Bao Zhihua,
Zhang Xiaoge
Publication year - 2015
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.2830
Subject(s) - cognitive radio , computer science , common value auction , spectrum (functional analysis) , idle , margin (machine learning) , nash equilibrium , mathematical optimization , computer network , algorithm , microeconomics , telecommunications , economics , mathematics , wireless , physics , quantum mechanics , machine learning , operating system
In cognitive radio networks, the most important goal of spectrum sharing is to benefit both the seller and buyer. In order to increase the total benefits generated in spectrum sharing, this paper introduces a memory mechanism between the spectrum agent and multi‐primary service providers (PSPs) and proposes a spectrum trading algorithm based on the mechanism. In this algorithm, all PSPs compete with each other and sell their idle spectrum resource to the agent to maximise their own profits. Then, the agent auctions the spectrum resources obtained in multi‐secondary users. Finally, a new auction pricing function is designed to decrease the auction trading prices and increase the benefits of secondary users. Nash equilibrium is considered to be the optimal result. Simulation results show that the proposed algorithm provides 10–15% margin over the conventional algorithm both in the price and spectrum quantity. Copyright © 2014 John Wiley & Sons, Ltd.