REFIM: A Practical Interference Management in Heterogeneous Wireless Access Networks

TLDR

Small‑cell deployments such as pico and femto cells are increasingly used to exploit spatial reuse, but the resulting heterogeneous network requires more sophisticated interference management to protect growing numbers of cell‑edge users. The authors introduce REFIM, a low‑complexity, fully distributed reference‑based interference‑management scheme for the downlink of heterogeneous multi‑cell networks. REFIM formulates an intractable global optimization, then decomposes it into per‑base‑station problems using a reference‑user concept to reduce computational and backhaul signaling overhead, and is evaluated through extensive simulations including real‑deployment scenarios. Simulations show REFIM boosts cell‑edge throughput by over 40 % and overall performance by 10–107 %, achieving about 95 % of the near‑optimal centralized MC‑IIWF algorithm, and demonstrates that a well‑managed spectrum‑sharing policy can outperform the best spectrum‑splitting strategy.

Abstract

Due to the increasing demand of capacity in wireless cellular networks, the small cells such as pico and femto cells are becoming more popular to enjoy a spatial reuse gain, and thus cells with different sizes are expected to coexist in a complex manner. In such a heterogeneous environment, the role of interference management (IM) becomes of more importance, but technical challenges also increase, since the number of cell-edge users, suffering from severe interference from the neighboring cells, will naturally grow. In order to overcome low performance and/or high complexity of existing static and other dynamic IM algorithms, we propose a novel low-complex and fully distributed IM scheme, called REFIM (REFerence based Interference Management), in the downlink of heterogeneous multi-cell networks. We first formulate a general optimization problem that turns out to require intractable computation complexity for global optimality. To have a practical solution with low computational and signaling overhead, which is crucial for low-cost small-cell solutions, e.g., femto cells, in REFIM, we decompose it into per-BS (base station) problems based on the notion of reference user and reduce feedback overhead over backhauls both temporally and spatially. We evaluate REFIM through extensive simulations under various configurations, including the scenarios from a real deployment of BSs. We show that, compared to the schemes without IM, REFIM can yield more than 40% throughput improvement of cell-edge users while increasing the overall performance by 10~107%. This is equal to about 95% performance of the existing centralized IM algorithm (MC-IIWF) that is known to be near-optimal but hard to implement in practice due to prohibitive complexity. We also present that as long as interference is managed well, the spectrum sharing policy can outperform the best spectrum splitting policy where the number of subchannels is optimally divided between macro and femto cells.