Joint Long-Term Admission Control and Beamforming in Green Downlink Networks: Offline and Online Approaches

TL;DR

This paper addresses joint long-term admission control and beamforming in green downlink networks, proposing offline and online algorithms to optimize power consumption while maintaining QoS, with the online method supporting real-time data transmission.

Contribution

It introduces a novel joint optimization framework for admission control and beamforming, including the first online algorithm for real-time network management in this context.

Findings

The online algorithm performs close to the offline solution in simulations.

Both algorithms effectively reduce power consumption while maintaining QoS.

The online approach is practical for real-time network control.

Abstract

Admission control is an effective solution to managing a wireless network with a large user set. It dynamically rejects users in bad conditions, and thereby guarantees high quality-of-service (QoS) for the others. Unfortunately, a frequently-varying admissible user set requests remarkable power to continually re-establish the transmission link. Hence, we explore the stability of admissible user set, and formulate a joint long-term admission control and beamforming problem for a network with one multi-antenna base station (BS) and multiple single-antenna users. We consider the downlink transmission in a time period containing multiple time slices. By jointly optimizing the admissible users and the BS transmit beamformers in different time slices, we aim to minimize the total power cost, including not only the power for QoS guarantee, but also the power for user status switching. Due to the NP-hardness of the problem, we develop two (offline and online) algorithms to find some efficient suboptimal solutions. The offline algorithm requires all channel state information (CSI), and solves the admissible users and beamformers in different time slices in one shot, based on successive upper-bound minimization (SUM). To support real-time data transmission, we further design an alternating direction method of multipliers (ADMM)-based online algorithm, which outputs the admissible users and beamformers in different time slices successively, utilizing the previous admissible user set, the actual value of current CSI, and the distribution of future CSI. Simulations validate the performance of the two algorithms, and show that the online algorithm is an efficient practical alternative to the offline algorithm.