Optimal Offline Packet Scheduling in Energy Harvesting 2-user Multiple Access Channel with Common Data

TL;DR

This paper develops an optimal offline packet scheduling method for energy harvesting 2-user Gaussian MACs with common data, considering data correlation, and demonstrates improved performance over non-optimized approaches.

Contribution

It introduces a novel optimal scheduling solution for energy harvesting MACs with common data, extending existing models to include data correlation.

Findings

The proposed algorithm achieves a larger departure region.

Numerical results show significant improvement over non-scheduling methods.

The solution generalizes previous MAC scheduling approaches to include common data.

Abstract

The lifetime and the sustainability of the wireless sensor networks (WSNs) can be increased with energy harvesting transmitters utilizing optimum packet scheduling. On the other hand, WSNs are observed to collect spatially or temporally correlated data which should be taken into account for the optimum packet scheduling in an energy harvesting system. However, the solutions available for 2-user multiple-access channel (MAC) systems with energy harvesting transmitters do not consider the common data or the correlation among the data. In this paper, optimal packet scheduling for energy harvesting 2-user Gaussian MAC with common data is achieved by assuming deterministic knowledge of the data and energy packets, i.e., offline solution. The optimum departure region is found by using Karush- Kuhn-Tucker (KKT) conditions generalizing the solutions obtained for the MAC without common data. An efficient iterative backward water-filling algorithm is defined. The optimum solution is numerically compared with the case of no scheduling, uniform power scheduling and the previous solutions defined for the MAC without common data by showing the improvement obtained with the optimization.