Resource allocation for MIMO-OFDMA downlink based cognitive radio systems with imperfect channel learning  

作　　者：LI XiuWen GAO JinChun LIU YuanAn XIE Gang MAO JunLing DENG PanLiang 

机构地区：[1]School of Electronic Engineering, Beijing University of Posts and Telecommunications [2]Key Laboratory of Universal Wireless Communication,Ministry of Education [3]School of Information and Communication Engineering, Beijing University of Posts and Telecommunications

出　　处：《Science China(Information Sciences)》2013年第10期67-80,共14页中国科学（信息科学）（英文版）

基　　金：supported in part by Canada-China Scientifc and Technological Cooperation(Grant No.2010DFA11320);the Fundamental Research Funds for the Central Universities(Grant Nos.G470209,2009RC0308);the National Natural Science Foundation of China(Grant Nos.60802033,60873190)

摘　　要：This paper is concerned with the resource allocation for multiple input multiple output and orthogo- nal frequency division multiplexing access （MIMO-OFDMA） downlink cognitive radio systems where a cognitive radio MIMO-OFDMA system is under spectrum sharing with an existing primary radio （PR） network. We use the channel learning scheme to estimate the channel information from cognitive radio transmitter （CR-TX） to PR and then make beamforming to transmit signal. Considering the interference from CR-TX to PR caused by the imperfect channel learning, we intend to maximize CR throughput under the interference power constraint at PR and CR transmit power constraint. A nearly optimal subcarrier and power allocation algorithm with linear complexity is proposed. The proposed algorithm is global optimal when the maximum transmit power is beyond certain threshold. Simulation results show that the proposed algorithm has a good performance very close to the global optimal algorithm.This paper is concerned with the resource allocation for multiple input multiple output and orthogo- nal frequency division multiplexing access （MIMO-OFDMA） downlink cognitive radio systems where a cognitive radio MIMO-OFDMA system is under spectrum sharing with an existing primary radio （PR） network. We use the channel learning scheme to estimate the channel information from cognitive radio transmitter （CR-TX） to PR and then make beamforming to transmit signal. Considering the interference from CR-TX to PR caused by the imperfect channel learning, we intend to maximize CR throughput under the interference power constraint at PR and CR transmit power constraint. A nearly optimal subcarrier and power allocation algorithm with linear complexity is proposed. The proposed algorithm is global optimal when the maximum transmit power is beyond certain threshold. Simulation results show that the proposed algorithm has a good performance very close to the global optimal algorithm.

关 键 词：cognitive radio MIMO OFDMA imperfect channel learning resource allocation 

分 类 号：TN919.3[电子电信—通信与信息系统]