实验室简介
浙江大学“智能计算与网络实验室(iCAN)”依托信息与电子工程学院，成立于2008年。主要从事下一代智能计算与通信网络的前沿理论和关键技术研究，目前聚焦5G通信关键技术、边缘云计算、B5G/6G核心理论和技术、人工智能与无线网络交叉技术等前沿课题。
实验室现有教授2名，博士后1名，硕博研究生十余名，已培养了十余名博士和硕士研究生进入“双一流”高校以及阿里巴巴、华为、英特尔等公司，多名学生获得浙江大学竺可桢奖学金(最高学生荣誉)以及中国电子学会、浙江省优秀博士/硕士学位论文。实验室承担了国家重大专项、国家重点基础研究发展计划(973)、国家自然科学基金、浙江省重点研发计划等科研项目，与华为、中国移动、诺基亚等公司展开紧密合作。近五年来，实验室在IEEE Trans. Wireless Commun., IEEE J. Sel. Area Commun., IEEE Commun. Mag.等期刊和会议上发表80余篇学术论文，授权近10项中国发明专利。
研究项目介绍
人工智能与无线网络交叉研究
随着无线网络的结构越来越复杂，节点规模越来越庞大，业务越来越多样化，网络优化变得更加复杂。利用人工智能技术，尤其是深度学习方法，可以大大提高无线网络优化算法的性能和速度。
[1] M. Lee, G. Yu, and G. Y. Li, Learning to branch: Accelerating resource allocation in wireless networks, IEEE Trans. Veh. Technol., submitted.
[2] M. Lee, G. Yu, and G. Y. Li, Graph embedding based wireless link scheduling with few training samples, IEEE Trans. Wireless Commun., submitted.
[3] J. Ren, G. Yu, and G. Ding, Accelerating DNN training in wireless federated edge learning system, IEEE Trans. Wireless Commun., submitted.
[4] M. Lee, Y. Xiong, G. Yu, and G. Y. Li, Deep neural networks for linear sum assignment problems, IEEE Wireless Commun. Lett., vol. 7, no. 6, pp. 962 – 965, Dec. 2018.
边缘计算与边缘智能
将云计算功能部署在蜂窝网络的边缘侧，包括移动基站和终端等，可以有效提升计算能力，降低通信时延，减轻核心网的传输负担。边缘计算和边缘智能是下一代车联网、无人驾驶、虚拟/增强现实的重要使能技术。
[1] Y. He, J. Ren, G. Yu, and Y. Cai, Optimizing the learning performance in mobile augmented reality systems with CNN, IEEE Trans. Wireless Commun., submitted.
[2] J. Ren, Y. He, G. Huang, G. Yu, Y. Cai, and Z. Zhang, An edge-computing based architecture for mobile augmented reality, IEEE Netw., vol. 33, no. 4, pp. 162 - 169, Aug. 2019.
[3] J. Ren, G. Yu, Y. He, and G. Li, Collaborative cloud and edge computing for latency minimization, IEEE Trans. Veh. Technol., vol. 68, no. 5, pp. 5031 - 5044, May 2019.
[4] Q. Hu, Y. Cai, G. Yu, Z. Qin, M. Zhao, and G. Y. Li, Joint offloading and trajectory design for UAV-enabled mobile edge computing systems, IEEE Internet Things J., vol. 6, no. 2, pp. 1879 - 1892, Apr. 2019.
[5] J. Ren, Y. Ruan, and G. Yu, Data transmission in mobile edge networks: Whether and where to compress? IEEE Commun. Lett., vol. 23, no. 3, pp. 490-493, Mar. 2019.
[6] Y. He, J. Ren, G. Yu, and Y. Cai, D2D communications meet mobile edge computing for enhanced computation capacity in cellular networks, IEEE Trans. Wireless Commun., vol. 18, no. 3, pp. 1750-1763, Mar. 2019.
[7] J. Ren, G. Yu, Y. Cai, and Y. He, Latency optimization for resource allocation in mobile-edge computation offloading, IEEE Trans. Wireless Commun., vol. 17, no. 8, pp. 5506 - 5519, Aug. 2018.
毫米波异构网络技术
5G将支持更宽的带宽和更高的传输速率，6GHz以下微波频谱的可用频段资源已经十分有限，因此，28-73GHz的毫米波频段成为了5G的重要频谱资源。毫米波通信对5G异构组网、用户接入、资源管理等技术带来了新的挑战。
[1] R. Liu, Q. Chen, G. Yu, and G. Y. Li, Joint user association and resource allocation for multi-band millimeter-wave heterogeneous networks, IEEE Trans. Commun., to appear.
[2] R. Liu, G. Yu, and G. Y. Li, User association for ultra-dense mmWave networks with multi-connectivity: A multi-label classification approach, IEEE Wireless Commun. Lett., to appear.
[3] G. Yu, R. Liu, Q. Chen, and Z. Tang, A hierarchical SDN architecture for ultra-dense millimeter-wave cellular networks, IEEE Commun. Mag., vol. 56, no. 6, pp. 79 - 85, Jun. 2018.
5G新频谱共享和异构组网技术
电磁频谱是提高无线通信系统容量的重要资源保证，下一代蜂窝网络将工作在更高的频点，比如5.8GHz免许可频段等，并采用更加先进的频谱共享和异构组网技术，比如蜂窝网络与WiFi网络的异构共存和融合。
[1] Y. Wang, J. Yuan, G. Yu, Q. Chen, and R. Yin, Minority game for distributed user association in unlicensed heterogenous networks, IEEE Trans. Wireless Commun., to appear.
[2] S. Liu, R. Yin, and G. Yu, Hybrid adaptive channel access for LTE-U systems, IEEE Trans. Veh. Technol., to appear.
[3] Q. Chen, G. Yu, and Z. Ding, Enhanced LAA for unlicensed LTE deployment based on TXOP contention, IEEE Trans. Commun., vol. 67, no. 1, pp. 417 - 429, Jan. 2019.
[4] J. Yuan, A. Huang, H. Shan, T. Q. S. Quek, and G. Yu, Design and analysis of random access for standalone LTE-U systems, IEEE Trans. Veh. Technol., vol. 67, no. 10, pp. 9347 - 9361, Oct. 2018.
[5] Q. Chen, G. Yu, H. M. Elmaghraby, J. Hamalainen, and Z. Ding, Embedding LTE-U within Wi-Fi bands for spectrum efficiency improvement, IEEE Netw., vol. 31, no. 2, pp. 72 - 79, Mar. 2017.
[6] Q. Chen, G. Yu, and Z. Ding, Optimizing unlicensed spectrum sharing for LTE-U and WiFi network coexistence, IEEE J. Sel. Areas Commun., vol. 34, no. 10, pp. 2562 - 2574, Oct. 2016.
[7] R. Yin, G. Yu, A. Maaref, and G. Y. Li, LBT-based adaptive channel access for LTE-U systems, IEEE Trans. Wireless Commun., vol. 15, no. 10, pp. 6585 - 6597, Oct. 2016.
[8] R. Yin, G. Yu, A. Maaref, and G. Y. Li, A framework for co-channel interference and collision probability tradeoff in LTE licensed-assisted access networks, IEEE Trans. Wireless Commun., vol. 15, no. 9, pp. 6078 - 6090, Sep. 2016.
[9] Q. Chen, G. Yu, A. Maaref, G. Y. Li, and A. Huang, Rethinking mobile data offloading for LTE in unlicensed spectrum, IEEE Trans. Wireless Commun., vol. 15, no. 7, pp. 4987 - 5000, Jul. 2016.
[10] Q. Chen, G. Yu, H. Shan, A. Maaref, G. Y. Li, and A. Huang, Cellular meets WiFi: Traffic offloading or resource sharing? IEEE Trans. Wireless Commun., vol. 15, no. 5, pp. 3354 - 3367, May 2016.
终端直通通信技术
终端直通通信是4.5G/5G网络中的一项重要技术，它允许距离相近的设备不通过基站中继而直接进行通信，同时复用蜂窝网络的频谱资源，从而提高频谱利用率和网络吞吐量，是车联网的重要使能技术。
[1] R. Yin, C. Zhong, G. Yu, Z. Zhang, K. -K. Wong, and X. Chen, Joint spectrum and power allocation for D2D communications underlaying cellular networks, IEEE Trans. Veh. Technol., vol. 65, no. 4, pp. 2182 - 2195, Apr. 2016.
[2] D. Feng, G. Yu, C. Xiong, Y. Yuan-Wu, G. Y. Li, G. Feng, and S. Li, Mode switching for energy-efficient device-to-device communications in cellular networks, IEEE Trans. Wireless Commun., vol. 14, no. 12, pp. 6993 - 7003, Dec. 2015.
[3] R. Yin, G. Yu, H. Zhang, Z. Zhang, and G. Y. Li, Pricing-based interference coordination for D2D communications in cellular networks, IEEE Trans. Wireless Commun., vol. 14, no. 3, pp. 1519 - 1532, Mar. 2015.
[4] G. Yu, L. Xu, D. Feng, R. Yin, G. Y. Li, and Y. Jiang, Joint mode selection and resource allocation for device-to-device communications, IEEE Trans. Commun., vol. 62, no. 11, pp. 3814 - 3824, Nov. 2014.
绿色通信技术
随着移动业务的迅猛发展，超密集基站的部署造成了网络能耗的急剧上升，对移动产业的环保和节能减排造成了很大的压力。另外，终端的绿色和节能通信也是提升用户服务体验的重要手段。
[1] C.-L. I, G. Yu, S. Han, and G. Y. Li, Green and software-defined wireless networks: From theory to practice, Cambridge University Press, ISBN: 9781108417327, May 2019.
[2] D. Wen, G. Yu, R. Li, Y. Chen, and G. Y. Li, Results on energy- and spectral- efficiency tradeoff in cellular networks with full-duplex enabled base stations, IEEE Trans. Wireless Commun., vol. 16, no. 3, pp. 1494 - 1507, Mar. 2017.
[3] Q. Chen, G. Yu, R. Yin, and G. Y. Li, Energy-efficient user association and resource allocation for multistream carrier aggregation, IEEE Trans. Veh. Technol., vol. 65, no. 8, pp. 6366 - 6376, Aug. 2016.
[4] Q. Chen, G. Yu, R. Yin, A. Maaref, G. Y. Li, and A. Huang, Energy efficiency optimization in licensed-assisted access, IEEE J. Sel. Areas Commun., vol. 34, no. 4, pp. 723 - 734, Apr. 2016.
[5] L. Xu, G. Yu, and Y. Jiang, Energy-efficient resource allocation in single-cell OFDMA systems: Multi-objective approach, IEEE Trans. Wireless Commun., vol. 14, no. 10, pp. 5848 - 5858, Oct. 2015.
[6] G. Yu, Y. Jiang, L. Xu, and G. Y. Li, Multi-objective energy-efficient resource allocation for multi-RAT heterogeneous networks, IEEE J. Sel. Areas Commun., vol. 33, no. 10, pp. 2118 - 2127, Oct. 2015.
[7] G. Yu, Q. Chen, R. Yin, H. Zhang, and G. Y. Li, Joint downlink and uplink resource allocation for energy-efficient carrier aggregation, IEEE Trans. Wireless Commun., vol. 14, no. 6, pp. 3207 - 3218, Jun. 2015.
[8] Y. Mao, G. Yu, and Z. Zhang, On the optimal transmission policy in hybrid energy supply wireless communication systems, IEEE Trans. Wireless Commun., vol. 13, no. 11, pp. 6422 - 6430, Nov. 2014.