
Energy provision minimisation in large‐scale wireless powered communication networks with throughput demand
Author(s) -
Ge Haijiang,
Yu Zhanwei,
Chi Kaikai,
Mao Keji,
Shao Qike,
Chen Lijian
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0022
Subject(s) - throughput , computer science , mathematical optimization , subgradient method , efficient energy use , wireless , computer network , telecommunications , mathematics , engineering , electrical engineering , machine learning
So far, the research of wireless powered communication networks (WPCNs) mainly considers the scenarios with a single radio‐frequency (RF) energy transmitter (ET) and a single sink. However, in practice, there are many applications where multiple ETs and sinks need to be deployed. This study focuses on large‐scale WPCNs having multiple RF ETs and sinks. Specifically, the authors aim to minimise the total energy provision by optimising ETs' transmit powers with the node‐throughput demand and sum‐throughput demand, respectively. For the node‐throughput demand case, they firstly formulate it to be a convex optimisation problem, then transform it to be a linear programming (LP) problem, and finally present a distributed algorithm to obtain the optimal solution. For the sum‐throughput demand case, they firstly formulate it to be a non‐linear optimisation problem, then prove its convexity and finally propose an efficient dual subgradient algorithm to obtain the optimal solution. Simulation results demonstrate that compared to the sum‐throughput demand, imposing the node‐throughput demand can effectively alleviate the throughput unfairness at the cost of increased energy provision; the proposed optimal algorithms can substantially decrease the total energy provision of ETs; the energy provision reduction percentage achieved by their schemes increases as the number of ETs increases.