M
Mugen Peng
Researcher at Beijing University of Posts and Telecommunications
Publications - 554
Citations - 16681
Mugen Peng is an academic researcher from Beijing University of Posts and Telecommunications. The author has contributed to research in topics: Relay & Resource allocation. The author has an hindex of 51, co-authored 501 publications receiving 12800 citations. Previous affiliations of Mugen Peng include Peking University & Chinese Ministry of Education.
Papers
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Journal ArticleDOI
Recent advances in Industrial Internet: insights and challenges
Wei Qin,Siqi Chen,Mugen Peng +2 more
TL;DR: This paper comprehensively surveys the recent advances of the Industrial Internet, including reference architectures, key technologies, relative applications and future challenges.
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Reinforcement Learning-Based Microgrid Energy Trading With a Reduced Power Plant Schedule
TL;DR: This scheme designs a deep RL-based energy trading algorithm to address the supply–demand mismatch problem for a smart grid with a large number of MGs without relying on the renewable energy generation and power demand models of other MGs.
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On the Design of Computation Offloading in Fog Radio Access Networks
TL;DR: This paper studies the design of computation offloading in F-RANs to minimize the total cost with respect to the energy consumption and the offloading latency, and designs an iterative algorithm to solve this non-linear and non-convex problem.
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A Non-Orthogonal Multiple Access-Based Multicast Scheme in Wireless Content Caching Networks
TL;DR: A non-orthogonal multiple access-based multicast (NOMA-MC) scheme is proposed in this paper, where pushing and multicasting content objects can be accomplished simultaneously, and thus the spectrum efficiency can be improved significantly.
Journal ArticleDOI
Hierarchical Radio Resource Allocation for Network Slicing in Fog Radio Access Networks
TL;DR: Simulation results show that there exists a tradeoff between the performance of slices, and the low complexity algorithms achieve close performance to that of exhaustive search and outperform other baselines significantly.