References of "You, Lei"
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See detailLoad Coupling and Energy Optimization in Multi-Cell and Multi-Carrier NOMA Networks
Lei, Lei UL; You, Lei; Yang, Yang et al

in IEEE Transactions on Vehicular Technology (2019)

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See detailLearning-Assisted Optimization for Energy-Efficient Scheduling in Deadline-Aware NOMA Systems
Lei, Lei UL; You, Lei; He, Qing et al

in IEEE Transactions on Green Communications and Networking (2019)

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See detailLoad Coupling and Energy Optimization in Multi-Cell and Multi-Carrier NOMA Networks
Lei, Lei UL; You, Lei; Yang, Yang et al

in IEEE Transactions on Vehicular Technology (2019)

Detailed reference viewed: 99 (13 UL)
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See detailPower and Load Optimization in Interference-Coupled Non-Orthogonal Multiple Access Networks
Lei, Lei UL; You, Lei; Yang, Yang UL et al

in IEEE Global Communications Conference (GLOBECOM) 2018 (2018, December)

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See detailEfficient Minimum-Energy Scheduling with Machine-Learning based Predictions for Multiuser MISO Systems
Lei, Lei UL; Vu, Thang Xuan UL; You, Lei et al

in 2018 IEEE International Conference on Communications (ICC) (2018, July)

Detailed reference viewed: 75 (7 UL)
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See detailResource Optimization With Load Coupling in Multi-Cell NOMA
You, Lei; Yuan, Di; Lei, Lei UL et al

in IEEE Transactions on Wireless Communications (2018)

Detailed reference viewed: 80 (6 UL)
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See detailEfficient Resource Optimization in Wireless Networks: A Deep-Learning Assisted Approach
Lei, Lei UL; You, Lei; Yuan, Di et al

in 2018 INFORMS Telecommunications Conference (2018, May)

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See detailA Framework for Optimizing Multi-cell NOMA: Delivering Demand with Less Resource
You, Lei; Lei, Lei UL; Yuan, Di et al

in 2017 IEEE Global Communications Conference (GLOBECOM) (2017, December)

Non-orthogonal multiple access (NOMA) allows multiple users to simultaneously access the same time-frequency resource by using superposition coding and successive interference cancellation (SIC). Thus far ... [more ▼]

Non-orthogonal multiple access (NOMA) allows multiple users to simultaneously access the same time-frequency resource by using superposition coding and successive interference cancellation (SIC). Thus far, most papers on NOMA have focused on performance gain for one or sometimes two base stations. In this paper, we study multi-cell NOMA and provide a general framework for user clustering and power allocation, taking into account inter-cell interference, for optimizing resource allocation of NOMA in multi-cell networks of arbitrary topology. We provide a series of theoretical analysis, to algorithmically enable optimization approaches. The resulting algorithmic notion is very general. Namely, we prove that for any performance metric that monotonically increases in the cells’ resource consumption, we have convergence guarantee for global optimum. We apply the framework with its algorithmic concept to a multi-cell scenario to demonstrate the gain of NOMA in achieving significantly higher efficiency. [less ▲]

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See detailA Deep Learning Approach for Optimizing Content Delivering in Cache-Enabled HetNet
Lei, Lei UL; You, Lei; Dai, Gaoyang et al

in IEEE International Symposium on Wireless Communication Systems (ISWCS), Bologna, Aug. 2017 (2017, August 31)

Detailed reference viewed: 249 (14 UL)