  Energy harvesting (EH) has recently emerged as an effective way to solve the
lifetime challenge of wireless sensor networks, as it can continuously harvest
energy from the environment. Unfortunately, it is challenging to guarantee a
satisfactory short-term performance in EH communication systems because the
harvested energy is sporadic. In this paper, we consider the channel training
optimization problem in EH communication systems, i.e., how to obtain accurate
channel state information to improve the communication performance. In contrast
to conventional communication systems, the optimization of the training power
and training period in EH communication systems is a coupled problem, which
makes such optimization very challenging. We shall formulate the optimal
training design problem for EH communication systems, and propose two solutions
that adaptively adjust the training period and power based on either the
instantaneous energy profile or the average energy harvesting rate. Numerical
and simulation results will show that training optimization is important in EH
communication systems. In particular, it will be shown that for short block
lengths, training optimization is critical. In contrast, for long block
lengths, the optimal training period is not too sensitive to the value of the
block length nor to the energy profile. Therefore, a properly selected fixed
training period value can be used.
