A Multi-server Scheduling Framework for Resource Allocation in Wireless Multi-carrier Networks

TL;DR

This paper introduces a multi-server scheduling framework for wireless multi-carrier networks, improving resource allocation efficiency and power consumption through novel service disciplines and integrated MAC-PHY schemes.

Contribution

It proposes and analyzes a multi-server packetized general processor sharing (MPGPS) framework, including adaptive and opportunistic variants, for enhanced multiuser resource allocation in OFDM networks.

Findings

MPGPS effectively serves multiple users simultaneously.

The integrated MAC-PHY scheme improves resource utilization.

Adaptive MPGPS balances power efficiency and queueing performance.

Abstract

Multiuser resource allocation has recently been recognized as an effective methodology for enhancing the power and spectrum efficiency in OFDM (orthogonal frequency division multiplexing) systems. It is, however, not directly applicable to current packet-switched networks, because (i) most existing packet-scheduling schemes are based on a single-server model and do not serve multiple users at the same time; and (ii) the conventional separate design of MAC (medium access control) packet scheduling and PHY (physical) resource allocation yields inefficient resource utilization. In this paper, we propose a cross-layer resource allocation algorithm based on a novel multi-server scheduling framework to achieve overall high system power efficiency in packet-switched OFDM networks. Our contribution is four fold: (i) we propose and analyze a MPGPS (multi-server packetized general processor sharing) service discipline that serves multiple users at the same time and facilitates multiuser resource allocation; (ii) we present a MPGPS-based joint MAC-PHY resource allocation scheme that incorporates packet scheduling, subcarrier allocation, and power allocation in an integrated framework; (iii) by investigating the fundamental tradeoff between multiuser-diversity and queueing performance, we present an A-MPGPS (adaptive MPGPS) service discipline that strikes balance between power efficiency and queueing performance; and (iv) we extend MPGPS to an O-MPGPS (opportunistic MPGPS) service discipline to further enhance the resource utilization efficiency.