1 research outputs found
Energy Management for Energy Harvesting Wireless Sensors with Adaptive Retransmission
This paper analyzes the communication between two energy harvesting wireless
sensor nodes. The nodes use automatic repeat request and forward error
correction mechanism for the error control. The random nature of available
energy and arrivals of harvested energy may induce interruption to the signal
sampling and decoding operations. We propose a selective sampling scheme where
the length of the transmitted packet to be sampled depends on the available
energy at the receiver. The receiver performs the decoding when complete
samples of the packet are available. The selective sampling information bits
are piggybacked on the automatic repeat request messages for the transmitter
use. This way, the receiver node manages more efficiently its energy use.
Besides, we present the partially observable Markov decision process
formulation, which minimizes the long-term average pairwise error probability
and optimizes the transmit power. Optimal and suboptimal power assignment
strategies are introduced for retransmissions, which are adapted to the
selective sampling and channel state information. With finite battery size and
fixed power assignment policy, an analytical expression for the average packet
drop probability is derived. Numerical simulations show the performance gain of
the proposed scheme with power assignment strategy over the conventional
scheme.Comment: accepted in IEEE Transactions on Communications, June 2017, Keywords:
Wireless sensors networks, energy harvesting, packet drop probability,
partially observable Markov decision processe