We seek to maximize the average data throughput of a single transmitter sending data over a fading channel to a single user class. The transmitter has a fixed amount of energy and a limited amount of time to send data. Given that the channel state determines the throughput obtained per unit of energy expended, the goal is to obtain a policy for scheduling transmissions that maximizes the expected data throughput. We develop a dynamic programming formulation that leads to an optimal transmission schedule, first where the present channel state is known just before transmission, and then to the case where the current channel state is unknown before transmission, but observed after transmission and evolves according to a Markov process. We then extend our approach to the problem of minimizing the expected energy required to send a fixed amount of data over a fading channel given deadline constraints.

We seek to maximize the data throughput of an energy and time constrained transmitter sending data over a fading channel. The transmitter has a fixed amount of energy and a limited amount of time to send data. Given that the channel fade state determines the throughput obtained per unit of energy expended, the goal is to obtain a policy for scheduling transmissions that maximizes the expected data throughput. We develop a dynamic programming formulation that leads to an optimal closed-form transmission schedule. We then extend our approach to the problem of minimizing the energy required to send a fixed amount of data over a fading channel given deadline constraints.

We address the issue of optimal energy allocation and admission control for communications satellites in Earth orbit. Such satellites receive requests for transmission as they orbit the Earth, but may not be able to serve them all, due to energy limitations. The objective is to choose which requests to serve so that the expected total reward is maximized. The special case of a single energy-constrained satellite is considered. Rewards and demands from users for transmission (energy) are random and known only at request time. Using a dynamic programming approach, an optimal policy is derived and is characterized in terms of thresholds. Furthermore, in the special case where demand for energy is unlimited, an optimal policy is obtained in closed form. Although motivated by satellite communications, our approach is general and can be used to solve a variety of resource allocation problems in wireless communications.

We address the issue of optimal energy allocation and admission control for communications satellites in Earth orbit. These satellites receive requests for transmission as they orbit the Earth, but may not be able to serve them all, due to energy limitations. The objective is to choose which requests to serve so that the expected total reward is maximized. The special case of a single energy-constrained satellite is considered. Rewards and demands from users for transmission (energy) are random and known only at request time. Using a dynamic programming approach, an optimal policy is derived and is characterized in terms of thresholds. Furthermore, in the special case where demand for energy is unlimited, an optimal policy is obtained in dosed form. Although motivated by satellite communications, our approach is general and can be used to solve a variety of resource allocation problems in wireless communications.