Energy Harvesting Wireless Communications: A Review of Recent Advances

This article summarizes recent contributions in the broad area of energy harvesting wireless communications. In particular, we provide the current state of the art for wireless networks composed of energy harvesting nodes, starting from the information-theoretic performance limits to transmission scheduling policies and resource allocation, medium access and networking issues. The emerging related area of energy transfer for self-sustaining energy harvesting wireless networks is considered in detail covering both energy cooperation aspects and simultaneous energy and information transfer. Various potential models with energy harvesting nodes at different network scales are reviewed as well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications (Special Issue: Wireless Communications Powered by Energy Harvesting and Wireless Energy Transfer

Cost minimization for fading channels with energy harvesting and conventional energy

In this paper, we investigate resource allocation strategies for a point-to-point wireless communications system with hybrid energy sources consisting of an energy harvester and a conventional energy source. In particular, as an incentive to promote the use of renewable energy, we assume that the renewable energy has a lower cost than the conventional energy. Then, by assuming that the non-causal information of the energy arrivals and the channel power gains are available, we minimize the total energy cost of such a system over $N$ fading slots under a proposed outage constraint together with the energy harvesting constraints. The outage constraint requires a minimum fixed number of slots to be reliably decoded, and thus leads to a mixed-integer programming formulation for the optimization problem. This constraint is useful, for example, if an outer code is used to recover all the data bits. Optimal linear time algorithms are obtained for two extreme cases, i.e., the number of outage slot is $1$ or $N-1$. For the general case, a lower bound based on the linear programming relaxation, and two suboptimal algorithms are proposed. It is shown that the proposed suboptimal algorithms exhibit only a small gap from the lower bound. We then extend the proposed algorithms to the multi-cycle scenario in which the outage constraint is imposed for each cycle separately. Finally, we investigate the resource allocation strategies when only causal information on the energy arrivals and only channel statistics is available. It is shown that the greedy energy allocation is optimal for this scenario.Comment: to appear in IEEE Transactions on Wireless Communication

Exploiting Diversity by Opportunistic Scheduling in Energy Harvesting Wireless Networks

It is in recent years that harvesting energy from ambient energy sources (e.g., solar, wind, or vibration) has been commercialized, which is a promising technique to fulfil sustainable operations for many kinds of electrical systems. To advocate reducing the emission of greenhouse gases, people in communication society are seeking to accommodate and take advantage of this new technology for wireless systems, such as sensor networks, Internet of Things, and heterogeneous networks. In this dissertation, we focus on energy harvesting (EH) based wireless networks, where multiple users are powered by energy harvesters and share limited spectrum resources. In this system, the design of efficient access schemes plays a crucial role in optimizing the system performance. Moreover, different from the conventional wireless systems, there are two random processes that must be jointly counted in the transmission design: the channel fading and the dynamics of the EH powered battery. Specifically, we narrow down the design onto two typical network setups. First, in a single channel access scenario, an ad hoc network with multiple transmitter-receiver pairs is considered, where all EH-based transmitters share one channel by random access. Two EH rate models are applied: Constant and i.i.d. (i.e., independent and identically distributed) EH rate models. To quantify the roles of both the energy and channel state information, a distributed opportunistic scheduling framework is proposed such that the average throughput of the network is maximized. Second, in a multi-channel access scenario, we study an uplink transmission under a heterogeneous network hierarchy, where each EH-based mobile user (MU) is capable of both deterministically accessing to a large network via one private channel, and dynamically accessing a small network with a certain probability via one common channel shared by multiple MUs. Considering a time-correlated EH model, we study an opportunistic transmission scheme to maximize the average throughput for each MU by jointly exploiting the statistics of the system states. Finally, back to the single channel access setup, we investigate the multiuser energy diversity by analyzing the fundamental scaling law of the throughput over the number of EH-based users under both centralized and distributed access schemes. We reveal the throughput gain coming from both the increase of total available energy harvested over time/space and the combined dynamics of batteries