Energy-aware Adaptive Spectrum Access and Power Allocation in LAA Networks via Lyapunov Optimization

TL;DR

This paper proposes an online Lyapunov optimization-based algorithm for adaptive spectrum access and power allocation in LAA networks, significantly reducing energy consumption while maintaining QoS amid dynamic wireless conditions.

Contribution

It introduces a novel Lyapunov optimization framework for joint spectrum and power management in LAA and Wi-Fi networks considering real-time variability.

Findings

Reduces power consumption by up to 72.1% compared to existing schemes.

Provides theoretical performance bounds with a power-delay tradeoff.

Demonstrates effectiveness under dynamic traffic and Wi-Fi node variations.

Abstract

To relieve the traffic burden and improve the system capacity, licensed-assisted access (LAA) has been becoming a promising technology to the supplementary utilization of the unlicensed spectrum. However, due to the densification of small base stations (SBSs) and the dynamic variety of the number of Wi-Fi nodes in the overlapping areas, the licensed channel interference and the unlicensed channel collision could seriously influence the Quality of Service (QoS) and the energy consumption. In this paper, jointly considering time-variant wireless channel conditions, dynamic traffic loads, and random numbers of Wi-Fi nodes, we address an adaptive spectrum access and power allocation problem that enables minimizing the system power consumption under a certain queue stability constraint in the LAA-enabled SBSs and Wi-Fi networks. The complex stochastic optimization problem is rewritten as the difference of two convex (D.C.) program in the framework of Lyapunov optimization, thus developing an online energy-aware optimal algorithm. We also characterize the performance bounds of the proposed algorithm with a tradeoff of [O(1=V ); O(V )] between power consumption and delay theoretically. The numerical results verify the tradeoff and show that our scheme can reduce the power consumption over the existing scheme by up to 72.1% under the same traffic delay.