mmWave communication requires accurate and continuous beam steering to overcome the severe propagation loss user mobility. In this paper, we leverage a self-supervised deep learning approach exploit sub-6 GHz channels propose novel method predict beamforming vectors in band for single access point– link. This complex channel-beam mapping is learned via data issued from DeepMIMO dataset. We then compare our proposed with existing supervised classic reinforcement methods. Our simulations show...

To exploit the large bandwidth available in millimeter wave spectrum, highly directional beams need to be employed compensate for severe pathloss incurred at high frequencies. As a result, of both transmitter and receiver must constantly aligned. In this paper, beam alignment (BA) problem is formulated as an adversarial multi-armed bandit (MAB) problem, yielding distributed BA search between receiver. First, we analyze optimal codebook size that reduces space while insuring good performance...

The key element of enabling millimeter wave communications is the adoption a hybrid beamforming. This architecture requires development new algorithms to estimate mmWave channel. main goal this work jointly estimating channel parameters: angle departure (AOD), arrival (AOA) and path's gain using sparsity in conjunction with criterion test based on diagonality data matrices. results simulation, terms performance, show superiority modified algorithm integrating compared original one.

Accurate beamforming is a critical challenge for mmWave communications. Because of the large training overhead beam at high frequencies, it becomes relevant to exploit available knowledge sub-6GHz predict vectors using deep learning tools. In addition, fully centralized (CL) approaches require over all users data, rising major issues in terms signaling and computational cost. To address these issues, we propose federated (FL) scheme wireless network composed multiple communicating links...

Efficient beam alignment in wireless networks capable of supporting device mobility is currently one the major challenges mmWave communications. In this context, we formulate beam-alignment problem via adversarial multi-armed bandit (MAB) framework, which copes with arbitrary network dynamics including non-stationary or components. Building on well known exponential weights algorithm (EXP3) and by exploiting structure sparsity channel, propose a modified (MEXP3) policy that requires solely...

The large available spectrum in the millimeter wave (mmWave) band represents an attractive alternative for congested sub-6 GHz spectrum. To overcome difficult propagation conditions at high frequencies, directional communications via multiple antenna arrays and high-gain beams can be employed. Nevertheless, these need to well aligned reliably transmit data, which is a challenging task given user mobility unpredictable changes of wireless environment. In this paper, we propose new distributed...

Abstract The purpose of the present work was to provide new elements on localization Salvia officinalis essential oil secretory structures. Anatomical investigations leaves and stems structure were carried out using light microscopy. Non-glandular, peltate four types capitate glandular trichomes, already described in literature, found. In other hand, parenchyma histological study showed occurrence cavities. kinetics hydrodistillation is agreement with presence produced stored endogenous...

The main aim of this paper is to resolve a pilot contamination (PC) problem in multicell Massive MIMO system, where the PC considered as bottleneck such systems caused by lack orthogonality. To address constrained problem, we propose new approach based on beamspace unitary (BU) estimation signal parameters via rotational invariance technique (ESPRIT) for parameter channel estimation. Indeed, mitigation two steps, channels and then reconstruction desired exploiting path gains magnitude....