Joint Antenna Selection and Beamforming Algorithms for Physical Layer Multicasting with Massive Antennas
College of Automation and Electrical Engineering, Qingdao University, Qingdao 266071, China
College of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China
Author to whom correspondence should be addressed.
Academic Editor: Tatsuya Akutsu
Received: 12 March 2016 / Revised: 17 May 2016 / Accepted: 20 June 2016 / Published: 22 June 2016
We investigate the problem of minimizing the total power consumption under the constraint of the signal-to-noise ratio (SNR) requirement for the physical layer multicasting system with large-scale antenna arrays. In contrast with existing work, we explicitly consider both the transmit power and the circuit power scaling with the number of antennas. The joint antenna selection and beamforming technique is proposed to minimize the total power consumption. The problem is a challenging one, which aims to minimize the linear combination of
-norm. To our best knowledge, this minimization problem has not yet been well solved. A random decremental antenna selection algorithm is designed, which is further modified by an approximation of the minimal transmit power based on the asymptotic orthogonality of the channels. Then, a more efficient decremental antenna selection algorithm is proposed based on minimizing the
norm. Performance results show that the
norm minimization algorithm greatly outperforms the random selection algorithm in terms of the total power consumption and the average run time.
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MDPI and ACS Style
Wang, X.; Sheng, J. Joint Antenna Selection and Beamforming Algorithms for Physical Layer Multicasting with Massive Antennas. Algorithms 2016, 9, 42.
Wang X, Sheng J. Joint Antenna Selection and Beamforming Algorithms for Physical Layer Multicasting with Massive Antennas. Algorithms. 2016; 9(2):42.
Wang, Xinhua; Sheng, Jinlu. 2016. "Joint Antenna Selection and Beamforming Algorithms for Physical Layer Multicasting with Massive Antennas." Algorithms 9, no. 2: 42.
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