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

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• 作者：XiuWen Li (1) (3)
  JinChun Gao (1) (3)
  YuanAn Liu (1) (3)
  Gang Xie (2) (3)
  JunLing Mao (1) (3)
  PanLiang Deng (1) (3)
  
• 关键词：cognitive radio ; MIMO ; OFDMA ; imperfect channel learning ; resource allocation
• 刊名：SCIENCE CHINA Information Sciences
• 出版年：2013
• 出版时间：October 2013
• 年：2013
• 卷：56
• 期：10
• 页码：1-14
• 全文大小：516KB
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• 作者单位：XiuWen Li (1) (3)
  JinChun Gao (1) (3)
  YuanAn Liu (1) (3)
  Gang Xie (2) (3)
  JunLing Mao (1) (3)
  PanLiang Deng (1) (3)
  
  1. School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  3. Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing, 100876, China
  2. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, China
  
• ISSN：1869-1919

文摘

This paper is concerned with the resource allocation for multiple input multiple output and orthogonal 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.