Robust Transmissions in Wireless Powered Multi-Relay Networks with Chance Interference Constraints

In this paper, we consider a wireless powered multi-relay network in which a multi-antenna hybrid access point underlaying a cellular system transmits information to distant receivers. Multiple relays capable of energy harvesting are deployed in the network to assist the information transmission. The hybrid access point can wirelessly supply energy to the relays, achieving multi-user gains from signal and energy cooperation. We propose a joint optimization for signal beamforming of the hybrid access point as well as wireless energy harvesting and collaborative beamforming strategies of the relays. The objective is to maximize network throughput subject to probabilistic interference constraints at the cellular user equipment. We formulate the throughput maximization with both the time-switching and power-splitting schemes, which impose very different couplings between the operating parameters for wireless power and information transfer. Although the optimization problems are inherently non-convex, they share similar structural properties that can be leveraged for efficient algorithm design. In particular, by exploiting monotonicity in the throughput, we maximize it iteratively via customized polyblock approximation with reduced complexity. The numerical results show that the proposed algorithms can achieve close to optimal performance in terms of the energy efficiency and throughput.Comment: 14 pages, 8 figure

Simultaneous Wireless Information and Power Transfer for Decode-and-Forward Multi-Hop Relay Systems in Energy-Constrained IoT Networks

This paper studies a multi-hop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) system where a source sends data to a destination with the aid of multi-hop relays which do not depend on an external energy source. To this end, we apply power splitting (PS) based SWIPT relaying protocol so that the relays can harvest energy from the received signals from the previous hop to reliably forward the information of the source to the destination. We aim to solve two optimization problems relevant to our system model. First, we minimize the transmit power at the source under the individual quality-of-service (QoS) threshold constraints of the relays and the destination nodes by optimizing PS ratios at the relays. The second is to maximize the minimum system achievable rate by optimizing the PS ratio at each relay. Based on convex optimization techniques, the globally optimal PS ratio solution is obtained in closed-form for both problems. By setting the QoS threshold constraint the same for each node for the source transmit power problem, we discovered that either the minimum source transmit power or the maximum system throughput can be found using the same approach. Numerical results demonstrate the superiority of the proposed optimal SWIPT PS design over conventional fixed PS ratio schemes.Comment: 14 pages, 14 figures, Accepted for Publication in IEEE Internet of Things Journa

Robust Transceiver Design for SWIPT DF MIMO Relay Systems With Time-Switching Protocol

In this article, we investigate a dual-hop simultaneous wireless information and power transfer decode-and-forward multiple-input and multiple-output relay communication system, in which the relay node harvests energy based on the radio frequency (RF) signal transmitted from the source node through the time-switching (TS) protocol to decode and forward the re-encoded information to the destination node. With the consideration of the channel estimation error, the joint optimization of the TS factor and source and relay precoding matrices is proposed with robustness against the channel state information mismatch to maximize the mutual information (MI) between the source and destination nodes. We derive the optimal structure of the source and relay precoding matrices to simplify the transceiver optimization problem under fixed and flexible power constraints. Numerical examples demonstrate that the proposed algorithms with robustness provide better MI performance compared to the nonrobust algorithm