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Adaptive power control and beam-forming joint optimization in cognitive radio networks

Adaptive power control and beam-forming joint optimization in cognitive radio networks
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摘要 A novel adaptive power control and beam-forming joint optimization algorithm is proposed in cognitive radio (CR) underlay networks, where cognitive network share spectrum with primary network which spectrum is licensed. In this paper, both primary base station (PBS) and cognitive base station (CBS) are all equipped with multi antennas, while each primary user (PU) and cognitive user (CU) has only one antenna. Different from traditional algorithms, an adaptive weight factor generating solution is supplied to different access users (both PUs and CUs) in this paper, and the different priority of users is also considered, because PUs have higher priority, the weight factor of PUs is fixed as constant and signal-to-interference and noise ratio (SINR) threshold is unchanged, while for CUs, it is set adaptively and SINR threshold is also changed accordingly. Using this algorithm, the transmit power is decreased, which relax the strict requirements for power amplifier in communication systems. And moreover, owing to PUS has fixed SINR threshold, the calculated SINR at receiver is nearly unchanged, but for CUs, the S1NR is changing with the adaptive weight factor. Under the assurance of quality of service (QoS) of PUs, the solution in this paper can enable CRs access to the CR network according to adaptive SINR threshold, therefore which supplies higher spectrum utilization efficiency. A novel adaptive power control and beam-forming joint optimization algorithm is proposed in cognitive radio (CR) underlay networks, where cognitive network share spectrum with primary network which spectrum is licensed. In this paper, both primary base station (PBS) and cognitive base station (CBS) are all equipped with multi antennas, while each primary user (PU) and cognitive user (CU) has only one antenna. Different from traditional algorithms, an adaptive weight factor generating solution is supplied to different access users (both PUs and CUs) in this paper, and the different priority of users is also considered, because PUs have higher priority, the weight factor of PUs is fixed as constant and signal-to-interference and noise ratio (SINR) threshold is unchanged, while for CUs, it is set adaptively and SINR threshold is also changed accordingly. Using this algorithm, the transmit power is decreased, which relax the strict requirements for power amplifier in communication systems. And moreover, owing to PUS has fixed SINR threshold, the calculated SINR at receiver is nearly unchanged, but for CUs, the S1NR is changing with the adaptive weight factor. Under the assurance of quality of service (QoS) of PUs, the solution in this paper can enable CRs access to the CR network according to adaptive SINR threshold, therefore which supplies higher spectrum utilization efficiency.
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2012年第4期49-55,共7页 中国邮电高校学报(英文版)
基金 supported by the National Basic Research Program of China (2009CB320401) the Next Generation Broadband Wireless Mobile Communication Network of Major Special Projects(2010ZX03003-001,2012ZX03004-002) the National Natural Science Foundation of China (61171100)
关键词 cognitive radio power control BEAM-FORMING joint optimization primary user cognitive user cognitive radio, power control, beam-forming, joint optimization, primary user, cognitive user
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  • 1Spectrum policy task force. FCC 02-155. Washington, DC, USA: Federal Communications Commission (FCC), 2002. 被引量:1
  • 2Mitola J, Maguire G Q. Cognitive radio: making software radios more personal. IEEE Personal Communications, 1999, 6(4): 13-18. 被引量:1
  • 3Farrokhi F R, Tassiulas L, Liu K R. Joint optimal powercontrol and beamforrning in wireless networks using antenna arrays. IEEE Transactions on Communications, 1998, 46(10): 1313-1324. 被引量:1
  • 4Farrokhi F R, Liu K R, Tassinlas L. Transmit beamforming and power control for cellular wireless systems. IEEE Journal on Selected Area in Communications, 1998, 16(8): 1437-1450. 被引量:1
  • 5Zheng G, Ng T S, Wong K K. Joint power control and beamforming for sum-rate maximization in multiuser MIMO downlink channels. Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM'06), Nov 27-Dec 1, 2006, San Francisco, CA, USA. Piscataway, NJ, USA: IEEE, 2006: 5p. 被引量:1
  • 6Islam M H, Liang Y C, Hoang A T. Joint power control and beamforrning for cognitive radio networks. IEEE Transactions on Wireless Commtmications, 2008, 7(7): 2415-2419. 被引量:1
  • 7Zhang L, Liang Y C, Xin Y. Joint beamforming and power allocation for multiple access channels in cognitive radio networks. IEEE Journal on Selected Areas in Commtmications, 2008, 26(1): 38-51. 被引量:1
  • 8Boche H, Schubert M. Optimal multi-user interference balancing using transmit beamforming. Wireless Personal Communications, 2003, 26(4): 305-324. 被引量:1
  • 9Yang J H, Bjornson E, Bengtsson M. Receive beamforming design based on a multiple-state interference model. Proceedings of the IEEE International Conference on Communications (ICC'11), Jun 5-9, 2011, Kyoto, Japan. Piscataway, NJ, USA: IEEE, 2011 : 6p. 被引量:1
  • 10Schubert M, Boche H. Solution of the multiuser downlink beamforming problem with individual SINR constraints. IEEE Transactions on Vehicular Technology, 2004, 53(1): 18-28. 被引量:1

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