Hybrid analog and digital beamforming (HBF) has been regarded as a key technology for future millimeter wave (mmWave) communication systems due to its ability to obtain a good trade-off between achievable beamforming gain and hardware cost. In this paper, we investigate the channel estimation and hybrid precoding for mmWave MIMO systems with deep learning. We adopt the hierarchical codebook based algorithm for channel estimation as it requires limited number of pilot transmissions, and enhance its performance by proposing a new codebook design algorithm based on manifold optimization (MO). With the estimated channel state information (CSI) as the input, we develop a robust HBF network (HBF-Net) by applying convolutional layers and attention...
In millimeter-wave communications, multiple-input-multiple-output (MIMO) systems use large antenna a...
In this paper, we propose an end-to-end deep learning approach to realize channel state information ...
International audienceThis paper proposes a model-driven deep learning (MDDL)-based channel estimati...
In order to obtain beamforming gains and prevent high pathloss in millimeter wave (mmWave) systems, ...
Hybrid beamformer design plays very crucial role in the next generation millimeter-wave (mm-Wave) ma...
In multi-user millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems, hybrid precodi...
Elbir, Ahmet M./0000-0003-4060-3781; Papazafeiropoulos, Anastasios/0000-0003-1841-6461WOS: 000512550...
Hybrid analog and digital beamforming transceivers are instrumental in addressing the challenge of e...
peer reviewedHybrid analog and digital beamforming transceivers are instrumental in addressing the c...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the la...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
21st IEEE International Workshop on Signal Processing Advances in Wireless Communications (IEEE SPAW...
Communications over millimeter-wave (mmWave) frequencies is a key technology for the fifth generatio...
Communications over millimeter-wave (mmWave) frequencies is a key technology for the fifth generatio...
In millimeter-wave communications, multiple-input-multiple-output (MIMO) systems use large antenna a...
In this paper, we propose an end-to-end deep learning approach to realize channel state information ...
International audienceThis paper proposes a model-driven deep learning (MDDL)-based channel estimati...
In order to obtain beamforming gains and prevent high pathloss in millimeter wave (mmWave) systems, ...
Hybrid beamformer design plays very crucial role in the next generation millimeter-wave (mm-Wave) ma...
In multi-user millimeter wave (mmWave) multiple-input-multiple-output (MIMO) systems, hybrid precodi...
Elbir, Ahmet M./0000-0003-4060-3781; Papazafeiropoulos, Anastasios/0000-0003-1841-6461WOS: 000512550...
Hybrid analog and digital beamforming transceivers are instrumental in addressing the challenge of e...
peer reviewedHybrid analog and digital beamforming transceivers are instrumental in addressing the c...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Millimeter wave (mmWave) cellular systems will enable gigabit-per-second data rates thanks to the la...
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
21st IEEE International Workshop on Signal Processing Advances in Wireless Communications (IEEE SPAW...
Communications over millimeter-wave (mmWave) frequencies is a key technology for the fifth generatio...
Communications over millimeter-wave (mmWave) frequencies is a key technology for the fifth generatio...
In millimeter-wave communications, multiple-input-multiple-output (MIMO) systems use large antenna a...
In this paper, we propose an end-to-end deep learning approach to realize channel state information ...
International audienceThis paper proposes a model-driven deep learning (MDDL)-based channel estimati...