A Kronecker product CLMS algorithm for adaptive beamforming

被引:21
|
作者
Kuhn, Eduardo Vinicius [1 ]
Pitz, Ciro Andre [2 ]
Matsuo, Marcos Vinicius [2 ]
Bakri, Khaled Jamal [3 ]
Seara, Rui [3 ]
Benesty, Jacob [4 ]
机构
[1] Univ Tecnol Fed Parana, Dept Elect Engn, LAPSE Elect & Signal Proc Lab, BR-85902490 Toledo, Parana, Brazil
[2] Univ Fed Santa Catarina, Dept Control Automat & Computat Engn, GEPS Elect Signal Proc Grp, BR-89036004 Blumenau, SC, Brazil
[3] Univ Fed Santa Catarina, Dept Elect & Elect Engn, LINSE Circuits & Signal Proc Lab, BR-88040900 Florianopolis, SC, Brazil
[4] Univ Quebec, Energy Mat & Telecommun Res Ctr, INRS EMT Natl Inst Sci Res, Montreal, PQ H5A 1K6, Canada
关键词
Adaptive beamforming; Antenna arrays; CLMS algorithm; Kronecker product; Mobile communications;
D O I
10.1016/j.dsp.2021.102968
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, an adaptive algorithm is derived by considering that the beamforming vector can be decomposed as a Kronecker product of two smaller vectors. Such a decomposition leads to a joint optimization problem, which is then solved by using an alternating optimization strategy along with the steepest-descent method. The resulting algorithm, termed here Kronecker product constrained least-mean-square (KCLMS) algorithm, exhibits (in comparison to the well-known CLMS) improved convergence speed and reduced computational complexity; especially, for arrays with a large number of antennas. Simulation results are shown aiming to confirm the robustness of the proposed algorithm under different operating conditions. (C) 2021 Elsevier Inc. All rights reserved.
引用
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页数:8
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