Dual-Timescale Spectrum Management in Small-Cell Wireless Networks

TL;DR

This paper introduces a dual-timescale spectrum management framework for small-cell wireless networks, combining centralized and distributed optimization to improve resource allocation amid traffic and interference variability.

Contribution

It proposes a novel dual-timescale spectrum management framework with efficient algorithms, addressing both slow and fast timescale resource allocation in heterogeneous networks.

Findings

Framework improves spectrum utilization efficiency.

Algorithms guarantee convergence and are computationally efficient.

Simulation results show performance gains over existing methods.

Abstract

To attain the targeted data rates of next generation cellular networks requires dense deployment of small cells in addition to macro cells which provide wide coverage. Dynamic radio resource management is crucial to the success of such heterogeneous networks due to much more pronounced traffic and interference variations in small cells. This work proposes a framework for spectrum management organized according to two timescales, which include 1) centralized optimization on a moderate timescale corresponding to typical duration of user sessions (several seconds to minutes in today's networks), and 2) distributed spectrum allocation on a fast timescale corresponding to typical latency requirements (a few milliseconds). An optimization problem is formulated to allocate resources on the slower timescale with consideration of (distributed) opportunistic scheduling on the faster timescale. Both fixed and fully flexible user association schemes are considered. Iterative algorithms are developed to solve these optimization problems efficiently for a cluster of cells with guaranteed convergence. Simulation results demonstrate advantages of the proposed framework and algorithms.