Energy Efficient Scheduling for mmWave Backhauling of Small Cells in Heterogeneous Cellular Networks

TL;DR

This paper proposes an energy-efficient scheduling and power control scheme for mmWave backhauling in small cell networks, leveraging beamforming and spatial reuse to reduce energy consumption and improve efficiency in 5G heterogeneous networks.

Contribution

It introduces a novel joint scheduling and power control scheme based on maximum independent set algorithms, optimizing energy efficiency for mmWave backhaul in small cells.

Findings

Significant reduction in energy consumption demonstrated through simulations.

The proposed scheme outperforms existing methods in energy efficiency.

Optimal interference threshold depends on traffic load and network conditions.

Abstract

Heterogeneous cellular networks with small cells densely deployed underlying the conventional homogeneous macrocells are emerging as a promising candidate for the fifth generation (5G) mobile network. When a large number of base stations are deployed, the cost-effective, flexible, and green backhaul solution becomes one of the most urgent and critical challenges. With vast amounts of spectrum available, wireless backhaul in the millimeter wave (mmWave) band is able to provide several-Gbps transmission rates. To overcome high propagation loss at higher frequencies, mmWave backhaul utilize beamforming to achieve directional transmission, and concurrent transmissions (spatial reuse) under low inter-link interference can be enabled to significantly improve network capacity. To achieve an energy efficient solution for the mmWave backhauling of small cells, we first formulate the problem of minimizing the energy consumption via concurrent transmission scheduling and power control into a mixed integer nonlinear programming problem. Then we develop an energy efficient and practical mmWave backhauling scheme, where the maximum independent set based scheduling algorithm and the power control algorithm are proposed to exploit the spatial reuse for low energy consumption and high energy efficiency. We also theoretically analyze the conditions that our scheme reduces energy consumption, and the choice of the interference threshold for energy reduction. Through extensive simulations under various traffic patterns and system parameters, we demonstrate the superior performance of our scheme in terms of energy consumption and energy efficiency, and also analyze the choice of the interference threshold under different traffic loads, BS distributions, and the maximum transmission power.