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Chen Wei
Tsinghua University
278Publications
23H-index
1,833Citations
Publications 278
Newest
Published in IEEE Communications Magazine 10.36
Khaled Ben Letaief60
Estimated H-index: 60
,
Chen Wei23
Estimated H-index: 23
+ -3 AuthorsYing-Jun Angela Zhang
Published on Jun 1, 2019
Hoshyar Mohammed (THU: Tsinghua University), Zhijie Chen (Stanford University)+ 0 AuthorsWei Chen (THU: Tsinghua University)
Content caching provides a rare trade-off opportunity between low-cost memory and energy consumption, yet finding the optimal causal policy with low computational complexity remains a challenge. In this paper, we formulate the problem of joint pushing and caching at end users in a Markov decision process (MDP) framework with the aim of minimizing energy cost under causal knowledge of the user request delay information and strict delay constraint. We put forth a novel approach to decouple the inf...
Published on Jan 1, 2019in IEEE Transactions on Wireless Communications 6.39
Wei Huang , Chen Wei23
Estimated H-index: 23
,
H. Vincent Poor99
Estimated H-index: 99
Proactively pushing content to users has emerged as a promising approach to improve the spectrum usage in off-peak times for fifth-generation mobile networks. However, owing to the uncertainty of future user demands, base stations (BSs) may not receive payments for the pushed files. To motivate content pushing, providing economic incentives to BSs becomes essential. Based on request delay information (RDI) that characterizes the users’ request time for content files, this paper studies the profi...
Xiaomin Liu (NPU: Northwestern Polytechnical University), Lixin Li3
Estimated H-index: 3
(NPU: Northwestern Polytechnical University)
+ -3 AuthorsWenjun Xu10
Estimated H-index: 10
(Beijing University of Posts and Telecommunications)
Published on May 1, 2019 in ICC (International Conference on Communications)
Yawei Lu2
Estimated H-index: 2
(THU: Tsinghua University),
Chen Wei23
Estimated H-index: 23
(THU: Tsinghua University),
H. Vincent Poor99
Estimated H-index: 99
(Princeton University)
Published on May 1, 2019 in ICC (International Conference on Communications)
Huan Ren , Lixin Li3
Estimated H-index: 3
(NPU: Northwestern Polytechnical University)
+ 2 AuthorsZhu Han69
Estimated H-index: 69
(UH: University of Houston)
Published on May 1, 2019 in ICC (International Conference on Communications)
Yawei Lu2
Estimated H-index: 2
(THU: Tsinghua University),
Chen Wei23
Estimated H-index: 23
(THU: Tsinghua University),
H. Vincent Poor99
Estimated H-index: 99
(Princeton University)
Published on May 1, 2019 in ICC (International Conference on Communications)
Meng Wang11
Estimated H-index: 11
(RPI: Rensselaer Polytechnic Institute),
Chen Wei23
Estimated H-index: 23
(THU: Tsinghua University),
Anthony Ephremides49
Estimated H-index: 49
(UMD: University of Maryland, College Park)
Published in IEEE Transactions on Communications 5.69
Chen Wei23
Estimated H-index: 23
(THU: Tsinghua University),
H. Vincent Poor99
Estimated H-index: 99
(Princeton University)
In this paper, storage efficient caching based on time domain buffer sharing is considered. The caching policy allows a user’s device to determine whether and how long it should cache a content item according to the prediction of the user’s random request time, also referred to as the request delay information (RDI). In particular, the aim is to maximize the caching gain for communications while limiting its storage cost. To achieve this goal, a queueing theoretic model for caching with infinite...
Published on Apr 1, 2019in IEEE Wireless Communications Letters 3.55
Di Han (THU: Tsinghua University), Chen Wei23
Estimated H-index: 23
(THU: Tsinghua University),
Fang Yuguang62
Estimated H-index: 62
(UF: University of Florida)
The idle computing resources of parked vehicles could be utilized to improve performance by assisting task executions in mobile edge computing (MEC) systems. As a result, the owner of a vehicle could be compensated, resulting in a win-win situation. A dynamic pricing strategy is proposed to minimize the average cost of the MEC system under the constraints on quality of service by adjusting the price constantly based on the current system state. To do so, a cost minimization problem is solved to ...
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