Abstract
We consider an energy harvesting transmitter broadcasting individual data to two receivers. Data packets intended for each user are assumed to arrive at arbitrary but known instants. The goal is to minimize the total transmission time of the packets arriving within a certain time window, using the energy harvested during this time. Energy harvests are also modelled to occur at known discrete instants. An achievable rate region with structural properties satisfied by the two-user additive white Gaussian noise broadcast channel capacity region is assumed. Structural properties of power and rate allocations are established, as well as the uniqueness of the optimal policy. An iterative algorithm, DuOpt, is devised for efficient solution of this offline problem. DuOpt is compared with the sequential unconstrained minimization (SUMT) solution technique on randomly generated problem instances and is observed to solve the problem two orders of magnitude faster on average than SUMT.
Highlights
1 Introduction The basic offline problem of energy-efficient packet transmission scheduling [1,2,3,4,5] is to assign code rates to a set of packets whose arrival times are known beforehand, so that they are all transmitted within a given time window with minimum total energy
The solution needs to strike a trade-off between energy efficiency and delay: lowering energy expenditure per bit of information calls for lowering transmission rates, which causes delay
The practical motivation for this formulation was the case of a communication system that relies on energy harvesting from the environment to supply its battery [7]
Summary
The basic offline problem of energy-efficient packet transmission scheduling [1,2,3,4,5] is to assign code rates (transmission durations) to a set of packets whose arrival times are known beforehand, so that they are all transmitted within a given time window with minimum total energy. This paper completes the results of [1,2,11,12] with the following novel contributions: (1) establishment of structural properties of the transmission time minimizing scheduling policy in the energy harvesting BC with packet arrivals, (2) the uniqueness of the optimal policy, (3) an iterative algorithm, DuOpt, which is proved to return the optimal schedule when all the data of the user with the weaker channel is pooled, observed on numerical examples to solve the problem in the general case as well, (4) comparison of the computation time of the proposed method against solving the same problem with the well-known sequential unconstrained minimization technique (SUMT) We establish the uniqueness of the solution of Problem 1 under WUFBC
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