Predictive beamforming
WebDec 11, 2024 · The realization of practical intelligent reflecting surface (IRS)-assisted multi-user communication (IRS-MUC) systems critically depends on the proper beamforming design exploiting accurate channel state information (CSI). However, channel estimation (CE) in IRS-MUC systems requires a significantly large training overhead due to the … WebJul 21, 2024 · In this paper, we investigate a radar-assisted predictive beamforming design for vehicle-to-infrastructure (V2I) communication by exploiting the dual-functional radar-communication (DFRC) technique.
Predictive beamforming
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WebJan 1, 2024 · Abstract. This paper investigates deep learning techniques to predict transmit beamforming based on only historical channel data without current channel information … WebSep 26, 2024 · Predictive beamforming design is an essential task in realizing high-mobility integrated sensing and communication (ISAC), which highly depends on the accuracy of …
WebNov 23, 2024 · With the proposed predictive approach, we can avoid full-scale CSI estimation and facilitate low-dimensional CE for transmit beamforming design such that the signaling overhead is reduced by a scale of 1/N, where N is the number of IRS elements. WebApr 26, 2024 · To this end, a location-aware convolutional long short-term memory network (LA-CLNet) is first developed to facilitate predictive beamforming at IRS, where the convolutional and recurrent units are jointly adopted to exploit both the spatial and temporal features of channels simultaneously.
WebSep 16, 2024 · In this letter, we propose a deep learning -based location-aware predictive beamforming scheme to track the beam for UAV communications in a dynamic scenario. Specifically, a long short-term memory (LSTM)-based recurrent neural network (LRNet) is designed for UAV location prediction. Based on the predicted location, a predicted angle … WebThe development of dual-functional radar-communication (DFRC) systems, where vehicle localization and tracking can be combined with vehicular communication, will lead to more efficient future vehicular networks. In this paper, we develop a predictive beamforming scheme in the context of DFRC systems.
WebJul 21, 2024 · Beamforming is a signal processing method for enhancing signal given multiple signal receivers (antenna, ... (e.g. CGMM) to estimate it, or we can train a neural network to predict the mask. Even more, we can combine the mask prediction network with the beamforming method to make the whole beamforming process differentiable.
Webenabled predictive beamforming design in V2I networks. In [6], an extended Kalman filtering framework for predictive beamforming is proposed. First, the state parameters (e.g., … the mata mataWebIn this study, we use singlechannel speech enhancement deep networks to form masks that can be used for noise spatial covariance estimation, which steers the MVDR beamforming toward the speech. We analyze how mask prediction affects performance and also discuss various ways to use masks to obtain the speech and noise spatial covariance ... the matale and sandral affairWebNov 19, 2024 · We investigate sensing-assisted predictive beamforming schemes for vehicle-to-infrastructure (V2I) communication by exploiting the integrated sensing and … thema tafel pasenWebAug 26, 2024 · Then, by exploiting the penalty method, a versatile unsupervised DL-based predictive beamforming design framework is developed to address the formulated design … tiffany 1990 watchesWebMay 15, 2024 · The development of dual-functional radar-communication (DFRC) systems, where vehicle localization and tracking can be combined with vehicular communication, … thematafelsWeba predictive beamforming matrix for the next time slot is preset in advance, thus bypassing the real-time channel tracking or motion parameter prediction to further reduce the signaling overhead compared with existing works, e.g., [19]–[23]. themata for allWebAug 13, 2016 · 2.3 Predictive beamforming. After modeled on the Grassmannian manifold \(G_{n,1}\), the channel direction vectors can be predicted by exploiting differential geometry tools such as geodesic. Here, the geodesic is defined as the shortest path between two points on a curved space. tiffany 1988