Search Results for author: Wenqiang Yi

Found 7 papers, 0 papers with code

Knowledge-aided Federated Learning for Energy-limited Wireless Networks

no code implementations25 Sep 2022 Zhixiong Chen, Wenqiang Yi, Yuanwei Liu, Arumugam Nallanathan

Inspired by this, we define a new objective function, i. e., the weighted scheduled data sample volume, to transform the inexplicit global loss minimization problem into a tractable one for device scheduling, bandwidth allocation, and power control.

Federated Learning Scheduling

DRL Enabled Coverage and Capacity Optimization in STAR-RIS Assisted Networks

no code implementations1 Sep 2022 Xinyu Gao, Wenqiang Yi, Yuanwei Liu, Jianhua Zhang, Ping Zhang

Moreover, in order to improve the performance of the MO-PPO algorithm, two update strategies, i. e., action-value-based update strategy (AVUS) and loss function-based update strategy (LFUS), are investigated.

Dynamic Task Software Caching-assisted Computation Offloading for Multi-Access Edge Computing

no code implementations15 Aug 2022 Zhixiong Chen, Wenqiang Yi, Atm S. Alam, Arumugam Nallanathan

To this end, this work considers dynamic task software caching at the MEC server to assist users' task execution.

Edge-computing

Intelligent Trajectory Design for RIS-NOMA aided Multi-robot Communications

no code implementations3 May 2022 Xinyu Gao, Xidong Mu, Wenqiang Yi, Yuanwei Liu

The goal is to maximize the sum-rate of whole trajectories for the multi-robot system by jointly optimizing trajectories and NOMA decoding orders of robots, phase-shift coefficients of the RIS, and the power allocation of the AP, subject to predicted initial and final positions of robots and the quality of service (QoS) of each robot.

Efficient Wireless Federated Learning with Partial Model Aggregation

no code implementations20 Apr 2022 Zhixiong Chen, Wenqiang Yi, Arumugam Nallanathan, Geoffrey Ye Li

On this basis, we maximize the scheduled data size to minimize the global loss function through jointly optimize the device scheduling, bandwidth allocation, computation and communication time division policies with the assistance of Lyapunov optimization.

Federated Learning Scheduling

Coverage and Capacity Optimization in STAR-RISs Assisted Networks: A Machine Learning Approach

no code implementations13 Apr 2022 Xinyu Gao, Wenqiang Yi, Alexandros Agapitos, Hao Wang, Yuanwei Liu

Coverage and capacity are the important metrics for performance evaluation in wireless networks, while the coverage and capacity have several conflicting relationships, e. g. high transmit power contributes to large coverage but high inter-cell interference reduces the capacity performance.

BIG-bench Machine Learning

Multi-cell NOMA: Coherent Reconfigurable Intelligent Surfaces Model With Stochastic Geometry

no code implementations3 Mar 2021 Chao Zhang, Wenqiang Yi, Yuanwei Liu, Qiang Wang

Numerical results indicate that 1) although the interference from other cells is enhanced via the RISs, the performance of the RIS-aided user still enhances since the channel quality is strengthened more obviously; and 2) the SIC order can be altered by employing the RISs since the RISs improve the channel quality of the aided user.

Information Theory Information Theory

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