Tier-Aware Resource Allocation in OFDMA Macrocell-Small Cell Networks

TL;DR

This paper proposes a joint resource allocation framework for macrocell and small cell OFDMA networks, demonstrating improved performance and convergence properties through convex relaxation and distributed solutions.

Contribution

It introduces a novel joint sub-channel and power allocation method for macrocell-small cell networks, with a focus on convex relaxation and distributed implementation.

Findings

Performance gains over traditional power minimization methods

Convex relaxation closely approximates the original MINLP problem

Distributed solution converges to centralized optimal solution

Abstract

We present a joint sub-channel and power allocation framework for downlink transmission an orthogonal frequency-division multiple access (OFDMA)-based cellular network composed of a macrocell overlaid by small cells. In this framework, the resource allocation (RA) problems for both the macrocell and small cells are formulated as optimization problems. Numerical results confirm the performance gains of our proposed RA formulation for the macrocell over the traditional resource allocation based on minimizing the transmission power. Besides, it is shown that the formulation based on convex relaxation yields a similar behavior to the MINLP formulation. Also, the distributed solution converges to the same solution obtained by solving the corresponding convex optimization problem in a centralized fashion.