Placement Optimization of Energy and Information Access Points in Wireless Powered Communication Networks

TL;DR

This paper proposes optimized placement strategies for energy and information access points in wireless powered communication networks to minimize deployment costs while ensuring performance requirements.

Contribution

It introduces novel algorithms for joint placement of separate and co-located access points, reducing costs and improving efficiency in WPCNs.

Findings

Optimized placement reduces deployment costs.

Proposed algorithms meet energy and communication performance.

Joint optimization outperforms separate placement strategies.

Abstract

The applications of wireless power transfer technology to wireless communications can help build a wireless powered communication network (WPCN) with more reliable and sustainable power supply compared to the conventional battery-powered network. However, due to the fundamental differences in wireless information and power transmissions, many important aspects of conventional battery-powered wireless communication networks need to be redesigned for efficient operations of WPCNs. In this paper, we study the placement optimization of energy and information access points in WPCNs, where the wireless devices (WDs) harvest the radio frequency energy transferred by dedicated energy nodes (ENs) in the downlink, and use the harvested energy to transmit data to information access points (APs) in the uplink. In particular, we are interested in minimizing the network deployment cost with minimum number of ENs and APs by optimizing their locations, while satisfying the energy harvesting and communication performance requirements of the WDs. Specifically, we first study the minimum-cost placement problem when the ENs and APs are separately located, where an alternating optimization method is proposed to jointly optimize the locations of ENs and APs. Then, we study the placement optimization when each pair of EN and AP are co-located and integrated as a hybrid access point, and propose an efficient algorithm to solve this problem. Simulation results show that the proposed methods can effectively reduce the network deployment cost and yet guarantee the given performance requirements, which is a key consideration in the future applications of WPCNs.