Robust Adaptive Beamforming Based on Worst-Case and Norm Constraint

Li, Hongtao; Wang, Ke; Wang, Chaoyu; He, Yapeng; Zhu, Xiaohua

doi:10.1155/2015/765385

Cited by 11 publications

(6 citation statements)

References 15 publications

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“…SOCP problem ( 18 ) can be solved efficiently in polynomial time using IPM [ 23 ]. There are many well-constructed MATLAB toolboxes, such as CVX [ 24 , 25 ] and SeDuMi [ 26 ], which can be utilized to solve SOCP problems. Here, we use CVX to find the optimal solution, which is denoted by ω SOCP .…”

Section: Proposed Methodsmentioning

confidence: 99%

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Jin

Wang

et al. 2022

Computational Intelligence and Neuroscience

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Strong ground clutter echoes make it difficult to detect low-altitude slow-speed small (LSS) targets. To suppress ground clutter effectively in LSS target detection, a robust transmit beamforming algorithm has been proposed in this paper. Sidelobes in the ground side can be cut down, with the excess energy concentrated on the air side, which would be cleaner and simpler. The objective function is a second-order cone programming problem and can be solved by the convex optimization algorithm. With the consideration of taking full advantage of transmit power, the weight vector is further processed under the unimodular constraint. Numerical experiments are carried out to demonstrate the validity and superiority of the proposed method.

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Section: Proposed Methodsmentioning

confidence: 99%

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Jin

Wang

et al. 2022

Computational Intelligence and Neuroscience

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“…The authors of [27] have proposed CS-based beamforming for the orthogonal frequency division multiplexing (OFDM) systems. In [28] and [29], adaptive beamforming based on the CS technique for a sparse receiving array is proposed. The work [30] has proposed a CS-based channel estimation for massive MIMO systems.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Intelligent Surface-Aided Wireless Communications: Adaptive Beamforming and Experimental Validations

Amri

Tran

Choi³

2021

IEEE Access

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Recently, the fifth generation of cellular mobile communications (5G) network has been deployed and become pervasive. 5G offers a significant increase in terms of bandwidth and data rate compared to the previous generations. In addition, new technologies such as millimeter-wave (mmWave) technology and massive MIMO (mMIMO), have been proposed to meet the demand. However, some inevitable challenges still exist. In mmWave frequency, path loss and shadowing become more severe due to the radio electromagnetic (EM) wave characteristics. In this paper, we propose the utilization of reconfigurable intelligent surface (RIS) to aid wireless communications to overcome path loss and shadowing issues, by using a compressive sensing-based adaptive beamforming algorithm. To validate the theory, hypothesis, and simulation results, we have designed, fabricated, and conducted experiments with a 1-bit RIS testbed. The results show that the bit error rate (BER) and signal-to-noise ratio (SNR) of the received signal are significantly improved when the proposed RIS is employed. Further, we have also demonstrated a video streaming application aided by the proposed RIS as one of the potential RIS deployment scenarios. The video clip for the video streaming by using the RIS can be seen in [1].

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“…It has been widely used in radar, wireless communication, radio astronomy, and many other areas [1][2][3]. The performance of the adaptive antenna beamforming will be severely degraded if the weight vector of an array cannot be able to adapt sufficiently fast to the jammer motion.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Antenna Null Broadening Beamforming against Array Calibration Error Based on Adaptive Variable Diagonal Loading

Zhao

et al. 2017

International Journal of Antennas and Propagation

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An approach for null broadening beamforming is proposed based on adaptive variable diagonal loading (VDL) and combined with the covariance matrix taper (CMT) approach, aiming at improving the robustness of adaptive antenna null broadening beamforming when array calibration error exists. Hence, it is named VDL-CMT. In this novel approach, the signal-to-noise ratio in the tapered sample covariance matrix is estimated and the VDL factor can be obtained adaptively. Then, the covariance matrix of the CMT approach is loaded with the obtained VDL factor. According to simulation results, in the case of array calibration error, robustness of the VDL-CMT is significantly improved and its performance is better than that of the existing adaptive antenna null broadening beamforming approaches.

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Robust Adaptive Beamforming Based on Worst-Case and Norm Constraint

Cited by 11 publications

References 15 publications

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Robust Transmit Beamforming Algorithm for Low-Altitude Slow-Speed Small Target Detection

Reconfigurable Intelligent Surface-Aided Wireless Communications: Adaptive Beamforming and Experimental Validations

Adaptive Antenna Null Broadening Beamforming against Array Calibration Error Based on Adaptive Variable Diagonal Loading

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