Results 11 to 20 of about 2,822,972 (301)
Quadratic Matrix Inequality Approach to Robust Adaptive Beamforming for General-Rank Signal Model [PDF]
IEEE Trans. Signal Processing, vol. 68, pp. 2244-2255, 2020, 2019 The worst-case robust adaptive beamforming problem for general-rank signal model is considered. This is a nonconvex problem, and an approximate version of it (obtained by introducing a matrix decomposition on the presumed covariance matrix of the desired signal) has been well studied in the literature.
Yongwei Huang, S. Vorobyov, Z. Luo
arxiv +3 more sources
RIS-Aided Wireless Communications: Prototyping, Adaptive Beamforming, and Indoor/Outdoor Field Trials [PDF]
IEEE Transactions on Communications, 2021 The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid wireless communication systems have recently received much attention from academia and industry.
Xilong Pei +7 more
semanticscholar +1 more source
A Novel Realistic Approach of Adaptive Beamforming Based on Deep Neural Networks
IEEE Transactions on Antennas and Propagation, 2022 A new deep neural network (NN) approach applied to antenna array adaptive beamforming is presented in this article. A recurrent NN (RNN) based on the gated recurrent unit (GRU) architecture is used as a beamformer in order to produce proper complex ...
Ioannis Mallioras +3 more
semanticscholar +1 more source
IEEE Access, 2022 The goal of this paper is to evaluate the performance of an adaptive beamforming approach in fifth-generation millimeter-wave multicellular networks, where massive multiple-input multiple-output configurations are employed in all active base stations of ...
S. Lavdas +5 more
semanticscholar +1 more source
Simultaneously Intelligent Sensing and Beamforming Based on an Adaptive Information Metasurface
Advancement of science, 2023 Due to its ability to adapt to a variety of electromagnetic (EM) environments, the sensing‐enabled metasurface has garnered significant attention. However, large‐scale EM‐field sensing to obtain more information is still very challenging.
Ruizhe Jiang +6 more
semanticscholar +1 more source
IEEE Access, 2021 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
Muhammad Miftahul Amri +2 more
semanticscholar +1 more source
Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment [PDF]
IEEE Journal on Selected Areas in Communications, 2020 This paper proposes a deep learning approach to the adaptive and sequential beamforming design problem for the initial access phase in a mmWave environment with a single-path channel.
Foad Sohrabi, Zhilin Chen, Wei Yu
semanticscholar +1 more source
International Journal of Satellite Communications and Networking, EarlyView., 2023 The performance limitation in multiple‐input multiple‐output (MIMO) feeder links due to time and phase misalignment of the ground stations is investigated. Time and phase distribution over optical fiber is considered as an approach to achieve the synchronization requirements.
Eriserdi Mollaymeri +2 more
wiley +1 more source
IET Communications, Volume 17, Issue 2, Page 171-182, January 2023., 2023 Abstract In this article, robust beamforming (BF) and artificial noise (AN) design method is proposed for multiuser broadcast secure transmission under secrecy outage probability (SOP) constraints. A special scenario is assumed that the transmitter cannot obtain the accurate channel state information (CSI) of the users' channel, and different users ...
Li Yao +3 more
wiley +1 more source
A Hybrid Adaptive Beamforming Algorithm for SINR Enhancement in Massive MIMO Systems [PDF]
Radioengineering, 2023 With the extreme density of devices and fast change of their directions in massive MIMO networks, a fast adaptive beamforming algorithm is required to provide high directivity and an enhanced signal-to-interference and noise ratio (SINR).
H. Manai +2 more
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