Dynamic Sleep Control in Green Relay-Assisted Networks for Energy Saving and QoS Improving

TL;DR

This paper proposes a dynamic sleep control mechanism for relay stations in green cellular networks, optimizing energy savings and QoS by scheduling renewable energy use and employing dynamic programming.

Contribution

It introduces a novel RS sleep control policy based on renewable energy scheduling and dynamic programming, reducing complexity with greedy and reduced DP algorithms.

Findings

Reduced energy consumption with optimized RS sleep scheduling.

Enhanced QoS performance through dynamic energy management.

Reduced computational complexity with proposed algorithms.

Abstract

We study the relay station (RS) sleep control mechanism targeting on reducing energy consumption while improving users' quality of service (QoS) in green relay-assisted cellular networks, where the base station (BS) is powered by grid power and the RSs are powered by renewable energy. By adopting green RSs, the grid power consumption of the BS is greatly reduced. But due to the uncertainty and stochastic characteristics of the renewable energy, power supply for RSs is not always sufficient. Thus the harvested energy needs to be scheduled appropriately to cater to the dynamic traffic so as to minimize the energy saving in the long term. An optimization problem is formulated to find the optimal sleep ratio of RSs to match the time variation of energy harvesting and traffic arrival. To fully use the renewable energy, green-RS-first principle is adopted in the user association process. The optimal RS sleeping policy is obtained through dynamic programming (DP) approach, which divides the original optimization problem into per-stage subproblems. A reduced DP algorithm and a greedy algorithm are further proposed to greatly reduce the computation complexity. By simulations, the reduced DP algorithm outperforms the greedy algorithm in achieving satisfactory energy saving and QoS performance.