Abstract
We formulate the radio resource allocation problem of maximizing throughput in an OFDMA (Orthogonal Frequency Division Multiple Access) downlink where the BS (Base Station) adapts the power allocation according to non-causal (offline) knowledge of the harvested energy and channel state. The offline case is important from a theoretical point of view since it provides a bound on the performance of the online problem (causal). Differently from previous works that consider a continuous mapping between SNR (Signal-to-Noise Ratio) and transmit data rate, we employ a discrete mapping that depends on the required MCSs (Modulation and Coding Schemes). Also, we propose a heuristic algorithm that provides near-optimal results and achieves a good complexity/performance trade-off. In addition, we analyze the online version of the problem, and we propose two novel solutions to solve the problem only with causal information. Furthermore, we reformulate our problem to satisfy QoS (Quality of Service) constraints for each user in a hybrid power system where the BS is powered by a fixed power source from the electric grid and by a stochastic power source from renewable energy sources. Lastly, we present an offline solution to this new problem that also achieves a considerable complexity/performance gain.
Highlights
Energy Harvesting (EH) communications are powered by renewable energy sources and can enjoy an unlimited lifetime [2]
More precise EH model based on Markov processes with states represented by continuous intervals;
In this paper we studied the problem of resource allocation for rate maximization in OFDMA systems with an EH Base Station transmitting to several users
Summary
Energy Harvesting (EH) communications are powered by renewable energy sources and can enjoy an unlimited lifetime [2]. We apply the energy consumption causality constraints that limit the used energy to the quantity available at the moment, despite the knowledge of future energy arrivals in the offline case Both restrictions are known as energy harvesting constraints, and are present in several works [2]–[5]. The main advantages of EH systems include long term operation without stable power supplies, decreased need of cabling and component replacements, and smaller cost per project Motivated by those advantages we investigate EH scenarios related to wireless communications. We extend our analysis to the online case in order to study our problem in practical scenarios In this case, all available information is causal and we have the difficulty to allocate power without exact knowledge of the energy supplies. Compares the results for offline and online cases; section VI defines the rate maximization problem with hybrid energy source and QoS constraints, describes a heuristic algorithm to solve the problem and presents results for optimal and heuristic solutions; section VII presents our conclusions
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