9 research outputs found
Universally Near Optimal Online Power Control for Energy Harvesting Nodes
We consider online power control for an energy harvesting system with random
i.i.d. energy arrivals and a finite size battery. We propose a simple online
power control policy for this channel that requires minimal information
regarding the distribution of the energy arrivals and prove that it is
universally near-optimal for all parameter values. In particular, the policy
depends on the distribution of the energy arrival process only through its mean
and it achieves the optimal long-term average throughput of the channel within
both constant additive and multiplicative gaps. Existing heuristics for online
power control fail to achieve such universal performance. This result also
allows us to approximate the long-term average throughput of the system with a
simple formula, which sheds some light on the qualitative behavior of the
throughput, namely how it depends on the distribution of the energy arrivals
and the size of the battery.Comment: the proposed scheme is shown to be optimal both within constant
additive and multiplicative gaps; submitted to Journal on Selected Areas in
Communications - Series on Green Communications and Networking (Issue 3);
revised following reviewers' comment
Can Feedback Increase the Capacity of the Energy Harvesting Channel?
We investigate if feedback can increase the capacity of an energy harvesting
communication channel where a transmitter powered by an exogenous energy
arrival process and equipped with a finite battery communicates to a receiver
over a memoryless channel. For a simple special case where the energy arrival
process is deterministic and the channel is a BEC, we explicitly compute the
feed-forward and feedback capacities and show that feedback can strictly
increase the capacity of this channel. Building on this example, we also show
that feedback can increase the capacity when the energy arrivals are i.i.d.
known noncausally at the transmitter and the receiver