Adaptive Resource Allocation for Interference Management in Small Cell Networks

TLDR

The study examines femto cellular networks with multiple neighboring femtocells in enterprise settings such as shopping malls, stadiums, or corporate premises. It proposes a practical, suboptimal channel assignment and interference management algorithm for fractional frequency reuse networks, using an adaptive graph‑coloring approach to balance interference control and user fairness among femtocells. The algorithm achieves linear‑time complexity by employing adaptive graph coloring and accounts for practical factors such as channel feedback, latency, and computational overhead. In small test cases, the algorithm attains 85% of the optimal minimum user rate and, compared to alternatives, delivers up to 47% improvement over full frequency reuse in dense femtocell deployments.

Abstract

We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme.