On Distributed Power Control for Uncoordinated Dual Energy Harvesting Links: Performance Bounds and Near-Optimal Policies

In this paper, we consider a point-to-point link between an energy harvesting transmitter and receiver, where neither node has the information about the battery state or energy availability at the other node. We consider a model where data is successfully delivered only in slots where both nodes are active. Energy loss occurs whenever one node turns on while the other node is in sleep mode. In each slot, based on their own energy availability, the transmitter and receiver need to independently decide whether or not to turn on, with the aim of maximizing the long-term time-average throughput. We present an upper bound on the throughput achievable by analyzing a genie-aided system that has noncausal knowledge of the energy arrivals at both the nodes. Next, we propose an online policy requiring an occasional one-bit feedback whose throughput is within one bit of the upper bound, asymptotically in the battery size. In order to further reduce the feedback required, we propose a time-dilated version of the online policy. As the time dilation gets large, this policy does not require any feedback and achieves the upper bound asymptotically in the battery size. Inspired by this, we also propose a near-optimal fully uncoordinated policy. We use Monte Carlo simulations to validate our theoretical results and illustrate the performance of the proposed policies.Comment: 8 page

On joint energy and information transfer in relay networks with an imperfect power amplifier

This paper investigates the outage probability and the throughput of relay networks with joint information and energy transfer where the relay harvests energy from transmitted radio-frequency (RF) signal of the source. Considering different power consumption models, we derive the outage probability of the systems for both adaptive and non-adaptive power allocations at the relay. With a total energy consumption constraint at the source, we provide closed-form expressions for the optimal time sharing and power allocation between the source energy and information transfer signals. The analytical and simulation results demonstrate the efficiency of joint energy and information transfer systems in different condition

Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network

Ambient radio frequency (RF) energy harvesting has emerged as a promising solution for powering small devices and sensors in massive Internet of Things (IoT) ecosystem due to its ubiquity and cost efficiency. In this paper, we study joint uplink and downlink coverage of cellular-based ambient RF energy harvesting IoT where the cellular network is assumed to be the only source of RF energy. We consider a time division-based approach for power and information transmission where each time-slot is partitioned into three sub-slots: (i) charging sub-slot during which the cellular base stations (BSs) act as RF chargers for the IoT devices, which then use the energy harvested in this sub-slot for information transmission and/or reception during the remaining two sub-slots, (ii) downlink sub-slot during which the IoT device receives information from the associated BS, and (iii) uplink sub-slot during which the IoT device transmits information to the associated BS. For this setup, we characterize the joint coverage probability, which is the joint probability of the events that the typical device harvests sufficient energy in the given time slot and is under both uplink and downlink signal-to-interference-plus-noise ratio (SINR) coverage with respect to its associated BS. This metric significantly generalizes the prior art on energy harvesting communications, which usually focused on downlink or uplink coverage separately. The key technical challenge is in handling the correlation between the amount of energy harvested in the charging sub-slot and the information signal quality (SINR) in the downlink and uplink sub-slots. Dominant BS-based approach is developed to derive tight approximation for this joint coverage probability. Several system design insights including comparison with regularly powered IoT network and throughput-optimal slot partitioning are also provided

Joint relay selection and resource allocation for energy-efficient D2D cooperative communications using matching theory

Device-to-device (D2D) cooperative relay can improve network coverage and throughput by assisting users with inferior channel conditions to implement multi-hop transmissions. Due to the limited battery capacity of handheld equipment, energy efficiency is an important issue to be optimized. Considering the two-hop D2D relay communication scenario, this paper focuses on how to maximize the energy efficiency while guaranteeing the quality of service (QoS) requirements of both cellular and D2D links by jointly optimizing relay selection, spectrum allocation and power control. Since the four-dimensional matching involved in the joint optimization problem is NP-hard, a pricing-based two-stage matching algorithm is proposed to reduce dimensionality and provide a tractable solution. In the first stage, the spectrum resources reused by relay-to-receiver links are determined by a two-dimensional matching. Then, a three-dimensional matching is conducted to match users, relays and the spectrum resources reused by transmitter-to-relay links. In the process of preference establishment of the second stage, the optimal transmit power is solved to guarantee that the D2D link has the maximized energy efficiency. Simulation results show that the proposed algorithm not only has a good performance on energy efficiency, but also enhances the average number of served users compared to the case without any relay