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Zhu Han

Researcher at University of Houston

Publications -  1649
Citations -  61568

Zhu Han is an academic researcher from University of Houston. The author has contributed to research in topics: Computer science & Wireless network. The author has an hindex of 109, co-authored 1407 publications receiving 48725 citations. Previous affiliations of Zhu Han include University of British Columbia & University of Maryland University College.

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High Performance Cooperative Transmission Protocols Based on Multiuser Detection and Network Coding

TL;DR: In this paper, a multiuser detection (MUD) and network coding-based cooperative transmission protocol with high spectral efficiency, diversity order, and coding gain is developed, where the improvement of one user's link can also benefit the other users.
Proceedings ArticleDOI

Machine Learning-Based Hybrid Precoding with Robust Error for UAV mmWave Massive MIMO

TL;DR: This paper proposes a low-cost and energy-efficient hybrid precoding architecture for UAVs, where the antenna part is realized by lens array and results show that the proposed scheme can achieve higher sum rate and energy efficiency.
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Auction Design for Edge Computation Ofloading in SDN-based Ultra Dense Networks

TL;DR: A second-price auction scheme for ensuring the fair bidding for spectrum rent is proposed, which enables the MBS edge cloud and SBS edge clouds to occupy the channel in cooperative and competitive modes and experimental results validate the effectiveness of the proposed scheme in SDN-based ultra dense networks.
Proceedings ArticleDOI

Power allocation using Vickrey auction and sequential first-price auction games for physical layer security in cognitive relay networks

TL;DR: This work considers a cognitive radio network in which multiple pairs of secondary users communicate by a one-way relay node over orthogonal channels with the existence of an eavesdropper close to the destination, and introduces two multi-object auctions to perform this power allocation problem.
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Game Theory for Big Data Processing: Multileader Multifollower Game-Based ADMM

TL;DR: Both analytical and simulation results verify that the proposed method reaches a hierarchical social optimum and converges linearly, which indicates that the MLMF game-based ADMM can be used in very large networks, such as highly virtualized communication networks with two-layer hierarchies, for big data processing.