Enabling large intelligent surfaces with compressive sensing and deep learning A Taha, M Alrabeiah, A Alkhateeb IEEE access 9, 44304-44321, 2021 | 703 | 2021 |
Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels M Alrabeiah, A Alkhateeb IEEE Transactions on Communications 68 (9), 5504-5518, 2020 | 270 | 2020 |
Deep learning for TDD and FDD massive MIMO: Mapping channels in space and frequency M Alrabeiah, A Alkhateeb 2019 53rd asilomar conference on signals, systems, and computers, 1465-1470, 2019 | 187 | 2019 |
Millimeter wave base stations with cameras: Vision-aided beam and blockage prediction M Alrabeiah, A Hredzak, A Alkhateeb 2020 IEEE 91st vehicular technology conference (VTC2020-Spring), 1-5, 2020 | 167 | 2020 |
Deep learning for large intelligent surfaces in millimeter wave and massive MIMO systems A Taha, M Alrabeiah, A Alkhateeb 2019 IEEE Global communications conference (GLOBECOM), 1-6, 2019 | 154 | 2019 |
Vision-aided 6G wireless communications: Blockage prediction and proactive handoff G Charan, M Alrabeiah, A Alkhateeb IEEE Transactions on Vehicular Technology 70 (10), 10193-10208, 2021 | 123 | 2021 |
Single image dehazing with a generic model-agnostic convolutional neural network Z Liu, B Xiao, M Alrabeiah, K Wang, J Chen IEEE Signal Processing Letters 26 (6), 833-837, 2019 | 101 | 2019 |
DeepSense 6G: A large-scale real-world multi-modal sensing and communication dataset A Alkhateeb, G Charan, T Osman, A Hredzak, J Morais, U Demirhan, ... IEEE Communications Magazine 61 (9), 122-128, 2023 | 98 | 2023 |
ViWi: A deep learning dataset framework for vision-aided wireless communications M Alrabeiah, A Hredzak, Z Liu, A Alkhateeb 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), 1-5, 2020 | 96 | 2020 |
Deep learning for massive MIMO with 1-bit ADCs: When more antennas need fewer pilots Y Zhang, M Alrabeiah, A Alkhateeb IEEE Wireless Communications Letters 9 (8), 1273-1277, 2020 | 83 | 2020 |
Reinforcement learning of beam codebooks in millimeter wave and terahertz MIMO systems Y Zhang, M Alrabeiah, A Alkhateeb IEEE Transactions on Communications 70 (2), 904-919, 2021 | 80 | 2021 |
Deep learning for THz drones with flying intelligent surfaces: Beam and handoff prediction N Abuzainab, M Alrabeiah, A Alkhateeb, YE Sagduyu 2021 IEEE International Conference on Communications Workshops (ICC …, 2021 | 50 | 2021 |
Vision-aided dynamic blockage prediction for 6G wireless communication networks G Charan, M Alrabeiah, A Alkhateeb 2021 IEEE International Conference on Communications Workshops (ICC …, 2021 | 47 | 2021 |
Neural networks based beam codebooks: Learning mmWave massive MIMO beams that adapt to deployment and hardware M Alrabeiah, Y Zhang, A Alkhateeb IEEE Transactions on Communications 70 (6), 3818-3833, 2022 | 45 | 2022 |
Blockage prediction using wireless signatures: Deep learning enables real-world demonstration S Wu, M Alrabeiah, C Chakrabarti, A Alkhateeb IEEE Open Journal of the Communications Society 3, 776-796, 2022 | 41 | 2022 |
Viwi vision-aided mmwave beam tracking: Dataset, task, and baseline solutions M Alrabeiah, J Booth, A Hredzak, A Alkhateeb arXiv preprint arXiv:2002.02445, 2020 | 35 | 2020 |
Learning beam codebooks with neural networks: Towards environment-aware mmWave MIMO Y Zhang, M Alrabeiah, A Alkhateeb 2020 IEEE 21st International Workshop on Signal Processing Advances in …, 2020 | 24 | 2020 |
Deep learning for moving blockage prediction using real mmWave measurements S Wu, M Alrabeiah, A Hredzak, C Chakrabarti, A Alkhateeb ICC 2022-IEEE International Conference on Communications, 3753-3758, 2022 | 17* | 2022 |
Generic model-agnostic convolutional neural network for single image dehazing Z Liu, B Xiao, M Alrabeiah, K Wang, J Chen arXiv preprint arXiv:1810.02862, 2018 | 15 | 2018 |
Persistent feature descriptors for video MRM Alrabeiah, J Chen, D He, LI Liangyan, Q Yingchan, Y Wang, T Yin US Patent 10,534,964, 2020 | 14 | 2020 |