Abstract
We consider an energy harvesting transmitter which may need to compress received packets before forwarding them over a flat fading channel. Data compression is required to meet the bandwidth or energy constraint at the cost of data distortion. The objective is to design optimal compression and transmission policies, namely optimal transmission and compression powers, transmission and compression rates and transmission and compression times, such that the total distortion is minimized. In this paper, we consider a time slotted system where new data and energy packets arrive at the beginning of each time slot (TS) and channel gains are assumed to remain constant during each TS. Under the assumption that the energy and data arrivals and channel gains are known non-causally which corresponds to offline optimization, we formulate the compression and transmission scheduling optimization as a convex optimization problem and characterize the properties of optimal scheduling. For the strict delay case where the transmission and compression of each packet must be executed within the corresponding TS, we provide an iterative algorithm which mimics the iterative directional water-filling (IDWF) algorithm. Numerical results are provided to illustrate our results and the properties of optimal scheduling.
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