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Minjian Zhao

Researcher at Zhejiang University

Publications -  208
Citations -  2587

Minjian Zhao is an academic researcher from Zhejiang University. The author has contributed to research in topics: MIMO & Optimization problem. The author has an hindex of 21, co-authored 194 publications receiving 1587 citations. Previous affiliations of Minjian Zhao include University of Toronto.

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Joint Offloading and Trajectory Design for UAV-Enabled Mobile Edge Computing Systems

TL;DR: This paper addresses a UAV-aided mobile edge computing system, where a number of ground users are served by a moving UAV equipped with computing resources, and develops a simplified ${l}_{0}$ -norm algorithm with much reduced complexity.
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Dual-UAV-Enabled Secure Communications: Joint Trajectory Design and User Scheduling

TL;DR: This paper investigates a novel unmanned aerial vehicle (UAV)-enabled secure communication system where one UAV moves around to communicate with multiple users on the ground using orthogonal time-division multiple access while the other UAV in the area jams the eavesdroppers to protect communications of the desired users.
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Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization

TL;DR: In this paper, a two-timescale (TTS) transmission protocol was proposed to maximize the achievable average sum-rate for an IRS-aided multiuser system under the general correlated Rician channel model.
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Multiple Access for Mobile-UAV Enabled Networks: Joint Trajectory Design and Resource Allocation

TL;DR: This paper transforms the original problems for UAV communications with the OMA and NOMA modes into more tractable forms and develops novel algorithms based on penalty dual-decomposition technique to solve them, which outperform the benchmarks.
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Adaptive Reduced-Rank Receive Processing Based on Minimum Symbol-Error-Rate Criterion for Large-Scale Multiple-Antenna Systems

TL;DR: Simulation results are presented for time-varying wireless environments and show that the proposed JPDF minimum-SER receive processing strategy and algorithms achieve a superior performance than existing methods with a reduced computational complexity.