Distributed Robust Beamforming Based on Low-Rank and Cross-Correlation Techniques: Design and Analysis

被引:8
|
作者
Ruan, Hang [1 ]
de Lamare, Rodrigo C. [2 ,3 ]
机构
[1] Univ York, Dept Elect, York YO10 5DD, N Yorkshire, England
[2] Pontifical Catholic Univ Rio de Janeiro, CETUC, BR-22451900 Rio De Janeiro, Brazil
[3] Univ York, Commun Grp, Dept Elect Engn, York YO10 5DD, N Yorkshire, England
基金
巴西圣保罗研究基金会;
关键词
Robust distributed beamforming; SINR maxi-mization; subspace projection techniques; RELAY NETWORKS;
D O I
10.1109/TSP.2019.2954519
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 work, we present a novel robust distributed beamforming (RDB) approach based on low-rank and cross-correlation techniques. The proposed RDB approach mitigates the effects of channel errors in wireless networks equipped with relays based on the exploitation of the cross-correlation between the received data from the relays at the destination and the system output and low-rank techniques. The relay nodes are equipped with an amplify-and-forward (AF) protocol and the channel errors are modeled using an additive matrix perturbation, which results in degradation of the system performance. The proposed method, denoted low-rank and cross-correlation RDB (LRCC-RDB), considers a total relay transmit power constraint in the system and the goal of maximizing the output signal-to-interference-plus-noise ratio (SINR). We carry out a performance analysis of the proposed LRCC-RDB technique along with a computational complexity study. The proposed LRCC-RDB does not require any costly online optimization procedure and simulations show an excellent performance as compared to previously reported algorithms.
引用
收藏
页码:6411 / 6423
页数:13
相关论文
共 50 条
  • [1] ROBUST ADAPTIVE BEAMFORMING BASED ON LOW-RANK AND CROSS-CORRELATION TECHNIQUES
    Ruan, Hang
    de Lamare, Rodrigo C.
    2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2015, : 854 - 858
  • [2] Robust Adaptive Beamforming Based on Low-Rank and Cross-Correlation Techniques
    Ruan, Hang
    de Lamare, Rodrigo C.
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2016, 64 (15) : 3919 - 3932
  • [3] Robust Distributed Beamforming Based on Cross-Correlation and Subspace Projection Techniques
    Ruan, Hang
    de Lamare, Rodrigo C.
    2017 22ND INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2017,
  • [4] Low-rank covariance matrix tapering for robust adaptive beamforming
    Ruebsamen, Michael
    Gerlach, Christian
    Gershman, Alex B.
    2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, : 2333 - 2336
  • [5] Cross-Domain Object Representation via Robust Low-Rank Correlation
    Shen, Xiangjun
    Zhou, Jinghui
    Ma, Zhongchen
    Bao, Bingkun
    Zha, Zhengjun
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2021, 17 (04)
  • [6] PERFORMANCE ANALYSIS OF A ROBUST LOW-RANK STAP FILTER IN LOW-RANK GAUSSIAN CLUTTER
    Ginolhac, G.
    Forster, P.
    2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 2746 - 2749
  • [7] Cross-spectral palmprint recognition with low-rank canonical correlation analysis
    Qi Zhu
    Nuoya Xu
    Zheng Zhang
    Donghai Guan
    Ran Wang
    Daoqiang Zhang
    Multimedia Tools and Applications, 2020, 79 : 33771 - 33792
  • [8] Cross-spectral palmprint recognition with low-rank canonical correlation analysis
    Zhu, Qi
    Xu, Nuoya
    Zhang, Zheng
    Guan, Donghai
    Wang, Ran
    Zhang, Daoqiang
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (45-46) : 33771 - 33792
  • [9] DISTRIBUTED PRINCIPAL COMPONENT ANALYSIS BASED ON RANDOMIZED LOW-RANK APPROXIMATION
    Wang, Xinjue
    Chen, Jie
    2020 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (IEEE ICSPCC 2020), 2020,
  • [10] Robust adaptive beamforming for cylindrical uniform conformal arrays based on low-rank covariance matrix reconstruction
    Fu, Mingcheng
    Zheng, Zhi
    Wang, Wen-Qin
    Xiang, Min
    SIGNAL PROCESSING, 2025, 227