Exploiting Diversity by Opportunistic Scheduling in Energy Harvesting Wireless Networks

Abstract

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.