Add to ORKGmmWave communication requires accurate and continuous beam steering to overcome the severe propagation loss and user mobility. In this paper, we leverage a self-supervised deep learning approach to exploit sub-6 GHz channels and propose a novel method to predict beamforming vectors in the mmWave band for a single access point-user link. This complex channel-beam mapping is learned via dat
This paper investigates the applicability of deep and machine learning techniques to perform beam se...
Abstract Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves), wher...
Millimeter-wave (MmWave) vehicular communication enables massive sensor data sharing and various eme...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
Huge overhead of beam training imposes a significant challenge in millimeter-wave (mmWave) wireless ...
In this paper, motivated by the inter-base station (BS) channel dependence due to the shared wireles...
In this paper, we propose a deep learning-based beam tracking method for millimeter-wave (mmWave)com...
We consider a machine learning approach to perform best beam prediction in Non-Standalone Millimeter...
This paper investigates how angle-of-arrival (AoA) information can be exploited by deep-/machine-lea...
This paper investigates the applicability of deep and machine learning techniques to perform beam se...
Future wireless systems will range from sub-6 GHz to above 60 GHz so that large bandwidths could be ...
Future wireless systems will range from sub-6 GHz to above 60 GHz so that large bandwidths could be ...
This paper investigates the applicability of deep and machine learning techniques to perform beam se...
Abstract Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves), wher...
Millimeter-wave (MmWave) vehicular communication enables massive sensor data sharing and various eme...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
mmWave communication requires accurate and continuous beam steering to overcome the severe propagati...
Huge overhead of beam training imposes a significant challenge in millimeter-wave (mmWave) wireless ...
In this paper, motivated by the inter-base station (BS) channel dependence due to the shared wireles...
In this paper, we propose a deep learning-based beam tracking method for millimeter-wave (mmWave)com...
We consider a machine learning approach to perform best beam prediction in Non-Standalone Millimeter...
This paper investigates how angle-of-arrival (AoA) information can be exploited by deep-/machine-lea...
This paper investigates the applicability of deep and machine learning techniques to perform beam se...
Future wireless systems will range from sub-6 GHz to above 60 GHz so that large bandwidths could be ...
Future wireless systems will range from sub-6 GHz to above 60 GHz so that large bandwidths could be ...
This paper investigates the applicability of deep and machine learning techniques to perform beam se...
Abstract Future 5G/6G wireless networks will be increasingly using millimeter waves (mmWaves), wher...
Millimeter-wave (MmWave) vehicular communication enables massive sensor data sharing and various eme...