Joint Probabilistic Constrained Robust Beamforming and Antenna Selection

详细信息    查看全文

• 作者：Yong Jin ; Zhentao Hu ; Jinwang Yue ; Xianxing Liu
• 关键词：Robust beamforming ; Probabilistic constrained ; Antenna selection
• 刊名：Wireless Personal Communications
• 出版年：2015
• 出版时间：October 2015
• 年：2015
• 卷：84
• 期：4
• 页码：2385-2396
• 全文大小：943 KB
• 参考文献：1.Mitola, J., & Maguire, J. (1999). Cognitive radio: Making software radios more personal. IEEE Personal Communication Magazine, 6(4), 13-8.CrossRef
  2.Li, W.-C., Chang, T.-H., Lin, C., & Chi, C.-Y. (2013). Coordinated beamforming for multiuser MISO interference channel under rate outage constraints. IEEE Transactions on Signal Processing, 61(5), 1087-103.
  3.Zakhour, R., & Hanly, S. V. (2013). Min–max power allocation in cellular network with coordinated beamforming. IEEE Jounal on Selected Areas in Communication, 31(2), 287-02.CrossRef
  4.Gershman, A. B., Sidiropoulos, N. D., Shahbazpanahi, S., et al. (2010). Convex optimization-based beamforming: From receive to transmit and network designs. IEEE Signal Processing Magazine, 27(2), 62-5.CrossRef
  5.Huang, Y. W., Palomar, D. P., & Zhang, S. Z. (2013). Lorentz-positive maps and quadratic matrix inequalities with applications to robust MISO transmit beamforming. IEEE Transactions on Signal Processing, 61(5), 1121-130.MathSciNet CrossRef
  6.Huang, Y. W., & Palomar, D. P. (2014). Randomized algorithms for optimal solutions of double-sided QCQP with applications in signal processing. IEEE Transactions on Signal Processing, 62(5), 1093-108.MathSciNet CrossRef
  7.Wang, J., & Palomar, D. P. (2009). Worst-case robust MIMO transmission with imperfect channel knowledge. IEEE Transactions on Signal Processing, 57(8), 3086-100.MathSciNet CrossRef
  8.Ma, S., & Sun, D. C. (2013). Chance constrained robust beamforming in cognitive radio networks. IEEE Communications Letters, 17(1), 67-0.CrossRef
  9.Wang, K. Y., Chang, T. H., & Ma, W. K. (2011). Probabilistic SINR constrained robust transmit beamforming: A Bernstein-type inequality based conservative approach. In IEEE International Conference, ICASSP (pp. 3080-083)
  10.Mehanna, O., Sidiropoulos, N. D., & Giannakis, G. B. (2013). Joint beamforming and antenna selection. IEEE Transactions on Signal Processing, 61(10), 2660-674.MathSciNet CrossRef
  11.Candes, E., Wakin, M., & Boyd, S. (2008). Enhancing sparsity by reweighted ? minimization. Journal of Fourier Analysis and Applications, 14(5), 877-05.MATH MathSciNet CrossRef
  12.Luo, Z.-Q., Ma, W.-K., So, A. M.-C., & Ye, Y. (2010). Semidefinite relaxation of quadratic optimization problems. IEEE Signal Processing Magazine, 27(3), 20-4.CrossRef
  13.Chung, P. J., Du, H. Q., & Gondzio, J. (2011). A probabilistic constraint approach for robust transmit beamforming with imperfect channel information. IEEE Transactions on Signal Processing, 59(6), 2773-782.MathSciNet CrossRef
  14.Grant, M. C., & Boyd, S. P. (2014). CVX: Matlab software for disciplined convex programming, version 2.1. http://?cvxr.?com/?cvx/-/span>
  
• 作者单位：Yong Jin (1)
  Zhentao Hu (1)
  Jinwang Yue (1)
  Xianxing Liu (1)
  
  1. Institute of Image Processing and Pattern Recognition, Henan University, Kaifeng, 475001, China
  
• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  Signal,Image and Speech Processing
  Processor Architectures
  
• 出版者：Springer Netherlands
• ISSN：1572-834X

文摘

A novel method is proposed for joint probabilistic constrained robust beamforming and antenna selection used in cognitive radio networks. Assuming complex Gaussian distributed channel state information errors, the Bernstein-type inequalities are introduced to transform no closed-form probabilistic constrained forms into the deterministic forms. Moreover, the ?-norm is used as the closest convex approximation of ?-norm. Thus the original NP-hard optimal problem can be relaxed as a tractable convex optimization problem. A computationally efficient and near-optimal solution is obtained by an iteratively re-weighted algorithm. Simulations show that the proposed algorithm satisfies the predetermined service levels at relatively small excess transmission power in a number of transmitter reduction scenarios. Keywords Robust beamforming Probabilistic constrained Antenna selection