DocumentCode :
717537
Title :
A Novel Power Control Algorithm for Massive MIMO Cognitive Radio Systems Based on Game Theory
Author :
Manman Cui ; Bin-Jie Hu ; Xiaohuan Li ; Hongbin Chen
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
fYear :
2015
fDate :
11-14 May 2015
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, a novel system model named as massive multiple-input multiple-output (MIMO) cognitive radio system (CRS) is built and an efficient uplink power control algorithm based on noncooperative game theory with a self-adaptive power threshold scheme is proposed to improve the power efficiency. And then, we give an analytical model for the massive MIMO CRS and the detail of the self-adaptive power threshold scheme. Moreover, we prove the existence of the Nash Equilibrium and the convergence of the proposed algorithm. To evaluate the performance of the proposed algorithm, we do simulations and compare the system performance with two other classical power control algorithms. Simulation results demonstrate that the proposed algorithm can achieve a preferable performance in signal-to-noise-plus interference ratio (SINR) and a higher utility with lower transmission power and faster convergence. It implies that the novel way can achieve higher power efficiency and a better overall system performance.
Keywords :
MIMO communication; cognitive radio; game theory; power control; radiofrequency interference; telecommunication control; MIMO cognitive radio systems; Nash equilibrium; SINR; multiple-input multiple-output cognitive radio system; noncooperative game theory; power control algorithm; self-adaptive power threshold scheme; signal-to-noise-plus interference ratio; Algorithm design and analysis; Fading; Game theory; Interference; MIMO; Power control; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st
Conference_Location :
Glasgow
Type :
conf
DOI :
10.1109/VTCSpring.2015.7145634
Filename :
7145634
Link To Document :
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