Semi-dynamic Green Resource Management in Downlink Heterogeneous Networks by Group Sparse Power Control

TL;DR

This paper introduces a semi-dynamic resource management approach for downlink heterogeneous networks that minimizes power consumption by leveraging group sparse power control, enabling flexible and energy-efficient base station operation.

Contribution

It proposes a novel flexible power consumption model using group sparsity and a semi-dynamic management mechanism for joint resource optimization in heterogeneous networks.

Findings

The proposed model effectively reduces base station power consumption.

The SCA-based algorithm converges to a stationary solution.

Simulation results validate the efficiency of the resource management mechanism.

Abstract

This paper addresses the energy-saving problem for the downlink of heterogeneous networks, which aims at minimizing the total base stations (BSs) power consumption while each user's rate requirement is supported. The basic idea of this work is to make use of the flexibility and scalability of the system such that more benefits can be gained by efficient resource management. This motivates us to propose a flexible BS power consumption model, which can control system resources, such as antennas, frequency carriers and transmit power allocation in an energy efficient manner rather than the "on/off" binary sleep mode for BSs. To denote these power-saving modes, we employ the group sparsity of the transmit power vector instead of the {0, 1} variables. Based on this power model, a semi-dynamic green resource management mechanism is proposed, which can jointly solve a series of resource management problems, including BS association, frequency carriers (FCs) assignment, and the transmit power allocation, by group sparse power control based on the large scale fading values. In particular, the successive convex approximation (SCA)-based algorithm is applied to solve a stationary solution to the original non-convex problem. Simulation results also verify the proposed BS power model and the green resource management mechanism.