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| Cluster-based multicast transmission for device-to-device (D2D) communication B Peng, T Peng, Z Liu, Y Yang, C Hu 2013 IEEE 78th Vehicular Technology Conference (VTC Fall), 1-5, 2013 | 70 | 2013 |
| A resource allocation scheme for D2D multicast with QoS protection in OFDMA-based systems B Peng, C Hu, T Peng, Y Yang, W Wang 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and …, 2013 | 52 | 2013 |
| Deep reinforcement learning-based power allocation for rate-splitting multiple access in 6G LEO satellite communication system J Huang, Y Yang, L Yin, D He, Q Yan IEEE Wireless Communications Letters 11 (10), 2185-2189, 2022 | 48 | 2022 |
| Machine learning enabling analog beam selection for concurrent transmissions in millimeter-wave V2V communications Y Yang, Z Gao, Y Ma, B Cao, D He IEEE Transactions on Vehicular Technology 69 (8), 9185-9189, 2020 | 47 | 2020 |
| Energy efficiency maximization for device-to-device communication underlaying cellular networks on multiple bands Y Zhang, Y Yang, L Dai IEEE Access 4, 7682-7691, 2016 | 37 | 2016 |
| Optimal femtocell density for maximizing throughput in 5G heterogeneous networks under outage constraints T Mir, L Dai, Y Yang, W Shen, B Wang 2017 IEEE 86th vehicular technology conference (VTC-Fall), 1-5, 2017 | 31 | 2017 |
| Deep reinforcement learning-based dynamic spectrum access for D2D communication underlay cellular networks J Huang, Y Yang, G He, Y Xiao, J Liu IEEE Communications Letters 25 (8), 2614-2618, 2021 | 28 | 2021 |
| An FPGA-based LSTM acceleration engine for deep learning frameworks D He, J He, J Liu, J Yang, Q Yan, Y Yang Electronics 10 (6), 681, 2021 | 28 | 2021 |
| Multi-agent deep reinforcement learning-based power control and resource allocation for D2D communications H Xiang, Y Yang, G He, J Huang, D He IEEE Wireless Communications Letters 11 (8), 1659-1663, 2022 | 27 | 2022 |
| Dynamic spectrum access for D2D-enabled Internet of Things: A deep reinforcement learning approach J Huang, Y Yang, Z Gao, D He, DWK Ng IEEE Internet of Things Journal 9 (18), 17793-17807, 2022 | 18 | 2022 |
| Machine learning inspired codeword selection for dual connectivity in 5G user-centric ultra-dense networks Y Yang, X Deng, D He, Y You, R Song IEEE Transactions on Vehicular Technology 68 (8), 8284-8288, 2019 | 18 | 2019 |
| Transmission capacity of device-to-device communication under heterogeneous networks with cellular users assisted Y Yang, Z Liu, Z Fu, T Peng, W Wang 2013 IEEE Globecom Workshops (GC Wkshps), 635-341, 2013 | 17 | 2013 |
| Optimal spectrum access and power control of secondary users in cognitive radio networks Y Yang, L Dai, J Li, S Mumtaz, J Rodriguez EURASIP Journal on Wireless Communications and Networking 2017, 1-15, 2017 | 8 | 2017 |
| ACCsiNet: Asymmetric convolution-based autoencoder framework for massive MIMO CSI feedback B Cao, Y Yang, P Ran, D He, G He IEEE Communications Letters 25 (12), 3873-3877, 2021 | 7 | 2021 |
| Optimal spectrum reuse of V2V communications for maximizing average throughput in vehicular ad hoc networks Y Yang, H Xiang, G He, J Huang, Q Yan 2021 IEEE/CIC International Conference on Communications in China (ICCC …, 2021 | 6 | 2021 |
| Codeword selection for concurrent transmissions in UAV Networks: a machine learning approach Y Yang, Z Gao, Y Zhang, Q Yan, D He IEEE Access 8, 26583-26590, 2020 | 6 | 2020 |
| Machine learning based analog beam selection for 5G mmWave small cell networks Y Yang, Y He, D He, Z Gao, Y Luo 2019 IEEE Globecom Workshops (GC Wkshps), 1-5, 2019 | 6 | 2019 |
| Transmission capacity analysis of relay-assisted device-to-device communication in cellular networks T Zhou, L Liu, Y Zhang, Y Yang 2016 IEEE/CIC International Conference on Communications in China (ICCC), 1-6, 2016 | 6 | 2016 |
| Optimal Resource Allocation Scheme for Satisfying the Data Rate Requirement in Hybrid Network of D2D-Cellular. W Liu, Y Yang, T Peng, W Wang J. Comput. 9 (5), 1218-1225, 2014 | 5 | 2014 |
