Wireless energy transfer to a pair of energy receivers using signal strength feedback

Abstract

This paper focuses on wireless energy transfer (WET) to a pair of low complex energy receivers (ER), by only utilizing received signal strength indicator (RSSI) values that are fed back from the ERs to the energy transmitter (ET). Selecting the beamformer that maximizes the total average energy transfer between the ET and the ERs, while satisfying a minimum harvested energy criterion at each ER, is studied. This is a nonconvex constrained optimization problem which is difficult to solve analytically. Also, any analytical solution to the problem should only consists of parameters that the ET knows, or the ET can estimate, as utilizing only RSSI feedback values for channel estimation prohibits estimating some channel parameters. Thus, the paper focuses on obtaining a suboptimal solution analytically. It is proven that if the channels between the ET and the ERs satisfy a certain sufficient condition, this solution is in fact optimal. Simulations show that the optimality gap is negligibly small as well. Insights into a system with more than two ERs are also presented. To this end, it is highlighted that if the number of ERs is large enough, it is possible to always find a pair of ERs satisfying the sufficient condition, and hence, a pairwise scheduling policy that does not violate optimality can be used for the WET.

Cluster-based wireless energy transfer for low complex energy receivers

“…All the ERs in the network will harvest energy in the WPB stage. However, we will give priority to the ERs in S ⋆ , as the insights from [16] suggest that the system will do better in terms of WET by focusing on this cluster compared to a random selection of ERs. This makes the algorithm opportunistic.…”

“…The clustering algorithm in this paper stems on the idea presented in [16], where the optimality of WET to a pair of low complex ERs is studied. In particular, [16] highlights that the WET will be more efficient when the two ERs are close to each other in terms of channel phase.…”

“…The clustering algorithm in this paper stems on the idea presented in [16], where the optimality of WET to a pair of low complex ERs is studied. In particular, [16] highlights that the WET will be more efficient when the two ERs are close to each other in terms of channel phase. Along these lines, we group the ERs into clusters using the Lloyd's Algorithm [17] by utilizing the channel phase estimates between the ET and the ERs.…”

“…We pick the cluster that has its members (ERs) closest to its centroid in phase. Although all ERs in the network will harvest energy when performing the WET, we give priority to this selected cluster, as the insights from [16] suggest that the system will do better in terms of WET by focusing on this cluster compared to a random selection of ERs. This makes our scheduling policy opportunistic.…”

Opportunistic Wireless Energy Beamforming using RSSI Feedback

“…WET performed utilizing CSI normally consists of a training stage for channel learning. However, due to tight energy constraints and hardware limitations at the ERs, the conventional pilot-based techniques, where the channel estimation is done at the ERs, lead to many implementation difficulties [2,3]. The authors of [4] sought to estimate the channel at the ET using a one-bit feedback algorithm, where phase perturbations are made based on the feedback bits to obtain a satisfactory beamforming vector for WET.…”