Grid Energy Consumption and QoS Tradeoff in Hybrid Energy Supply Wireless Networks

TL;DR

This paper explores the tradeoff between grid energy consumption and QoS in hybrid energy supply wireless networks, proposing algorithms to optimize this balance considering both non-causal and causal energy information.

Contribution

It introduces a total service cost metric and develops algorithms for base station assignment and power control to optimize energy use and QoS tradeoffs.

Findings

Proposed a Greedy Assignment algorithm with near-optimal performance.

Formulated the problem as a Markov decision process for causal information.

Validated algorithms through simulations demonstrating effective tradeoff management.

Abstract

Hybrid energy supply (HES) wireless networks have recently emerged as a new paradigm to enable green networks, which are powered by both the electric grid and harvested renewable energy. In this paper, we will investigate two critical but conflicting design objectives of HES networks, i.e., the grid energy consumption and quality of service (QoS). Minimizing grid energy consumption by utilizing the harvested energy will make the network environmentally friendly, but the achievable QoS may be degraded due to the intermittent nature of energy harvesting. To investigate the tradeoff between these two aspects, we introduce the total service cost as the performance metric, which is the weighted sum of the grid energy cost and the QoS degradation cost. Base station assignment and power control is adopted as the main strategy to minimize the total service cost, while both cases with non-causal and causal side information are considered. With non-causal side information, a Greedy Assignment algorithm with low complexity and near-optimal performance is proposed. With causal side information, the design problem is formulated as a discrete Markov decision problem. Interesting solution structures are derived, which shall help to develop an efficient monotone backward induction algorithm. To further reduce complexity, a Look-Ahead policy and a Threshold-based Heuristic policy are also proposed. Simulation results shall validate the effectiveness of the proposed algorithms and demonstrate the unique grid energy consumption and QoS tradeoff in HES networks.