| The challenges associated with battery recharge, replacement and disposal in low- power wireless communicating devices deployed in harsh or commonly inaccessible environments, makes energy harvesting sources an attractive alternative. The focus of this dissertation is on the design and analysis of adaptive transmission strategies for resource constrained energy harvesting wireless networks.;We first design an optimal, deterministic scheduler for a single transmitter powered by an energy harvester, that minimizes packet loss in both additive white Gaussian noise channels and block fading channels. We then develop three low complexity schedulers that achieve near optimal performance in different system settings. We then consider a point-to-point energy harvesting system in which both the transmitter and receiver have limited buffer space and battery size. We develop strategies to minimize total packet loss by trading resources at the transmitter with that at the receiver. We analyze system performance with and without receiver feedback, in various scenarios. We next evaluate the capacity region of the Gaussian Multiple Access channel. We then develop three adaptive transmission schemes that achieve rates close to the maximum sum-rates-point for fading channels, under resource constrained settings. We adapt the proportionally fair rate allocation scheme for energy harvesting nodes. We address trade-offs between rate and fairness through two other adaptive transmission schemes for the flat fading wireless channel. Finally, we consider the impact of including processing costs in addition to transmission costs on the capacity of a fading wireless channel. We compute the achievable rate with both processing and transmission power constraints, with energy harvesters. |
