Optimal Packet Scheduling in an Energy Harvesting Communication System

• Published in: IEEE transactions on communications Vol. 60; no. 1; pp. 220 - 230
• Main Authors: Jing Yang, Ulukus, Sennur
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2012; Institute of Electrical and Electronics Engineers
• Subjects: Applied sciences; Delay; Energy consumption; Energy harvesting; Exact sciences and technology; Minimization; Radiocommunications; rechargeable wireless networks; Resource management; Scheduling algorithm; Switching and signalling; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Teletraffic; transmission completion time minimization; Transmitters; Transmitters. Receivers; Packet switching; transmission completion time minimization; Wireless telecommunication; Transmitter; Teletraffic; Scheduling; Traffic load; Energy harvesting; Transmission time; Arrival time; rechargeable wireless networks; Off line; Wireless network; Transmission rate
• ISSN: 0090-6778
• DOI: 10.1109/TCOMM.2011.112811.100349

We consider the optimal packet scheduling problem in a single-user energy harvesting wireless communication system. In this system, both the data packets and the harvested energy are modeled to arrive at the source node randomly. Our goal is to adaptively change the transmission rate according to the traffic load and available energy, such that the time by which all packets are delivered is minimized. Under a deterministic system setting, we assume that the energy harvesting times and harvested energy amounts are known before the transmission starts. For the data traffic arrivals, we consider two different scenarios. In the first scenario, we assume that all bits have arrived and are ready at the transmitter before the transmission starts. In the second scenario, we consider the case where packets arrive during the transmissions, with known arrival times and sizes. We develop optimal off-line scheduling policies which minimize the time by which all packets are delivered to the destination, under causality constraints on both data and energy arrivals.