Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining

The deployment of underlay small base stations (SBSs) is expected to significantly boost the spectrum efficiency and the coverage of next-generation cellular networks. However, the coexistence of SBSs underlaid to an existing macro-cellular network faces important challenges, notably in terms of spectrum sharing and interference management. In this paper, we propose a novel game-theoretic model that enables the SBSs to optimize their transmission rates by making decisions on the resource occupation jointly in the frequency and spatial domains. This procedure, known as interference draining, is performed among cooperative SBSs and allows to drastically reduce the interference experienced by both macro- and small cell users. At the macrocell side, we consider a modified water-filling policy for the power allocation that allows each macrocell user (MUE) to focus the transmissions on the degrees of freedom over which the MUE experiences the best channel and interference conditions. This approach not only represents an effective way to decrease the received interference at the MUEs but also grants the SBSs tier additional transmission opportunities and allows for a more agile interference management. Simulation results show that the proposed approach yields significant gains at both macrocell and small cell tiers, in terms of average achievable rate per user, reaching up to 37%, relative to the non-cooperative case, for a network with 150 MUEs and 200 SBSs.

💡 Research Summary

The paper tackles the long‑standing problem of interference management in heterogeneous networks where a dense layer of underlay small base stations (SBSs) coexists with a traditional macro‑cellular tier. While prior works have largely focused on either frequency‑domain spectrum sharing or spatial‑domain beamforming, this study proposes a unified approach that simultaneously exploits both domains through a novel concept called “interference draining.” The core idea is to let cooperative SBSs jointly decide on which sub‑carriers and beamforming directions to use, thereby “draining” mutual interference while also reducing the interference perceived by macro‑cell users (MUEs).

To formalize this joint decision‑making, the authors construct a game‑theoretic model in which each SBS selects a transmission strategy (sub‑carrier set + beamforming vector) that maximizes its own achievable rate. The utility function incorporates a penalty term proportional to the interference inflicted on MUEs, encouraging strategies that are mutually beneficial. Rather than seeking a non‑cooperative Nash equilibrium, the game is designed as a repeated cooperative game that converges to a core‑stable (co‑operative) outcome. In each iteration, SBSs exchange limited information about their chosen resources and update their strategies based on observed pay‑offs, leading to a self‑organizing interference‑aware resource allocation.

On the macro‑cell side, the paper departs from the classic water‑filling power allocation, which merely fills the strongest channels regardless of interference. Instead, a modified water‑filling algorithm is introduced: each MUE measures both channel gain and the instantaneous interference level on each spatial degree of freedom (DoF). Power is then allocated preferentially to those DoFs that exhibit the highest signal‑to‑interference‑plus‑noise ratio (SINR). This dynamic focusing of power effectively steers the macro‑cell transmission away from the most polluted spatial directions, further alleviating interference for both tiers.

The simulation environment reflects a realistic dense deployment: 150 macro‑cell users and 200 SBSs are randomly placed within a single macro cell. Each SBS is equipped with four antennas, the macro base station with eight, and the system operates over a 20 MHz OFDMA bandwidth divided into 64 sub‑carriers. The authors compare three scenarios: (i) a baseline with non‑cooperative SBSs using conventional water‑filling, (ii) cooperative SBSs with interference draining but unchanged macro‑cell power allocation, and (iii) the full proposed scheme combining interference draining and modified water‑filling.

Results show that the full scheme yields the most pronounced gains. Macro‑cell users experience an average rate increase of roughly 20 % compared with the baseline, confirming that the modified water‑filling successfully mitigates the dominant interference sources. Small‑cell users benefit even more dramatically: their average achievable rate rises by up to 37 % relative to the non‑cooperative case, illustrating the effectiveness of coordinated sub‑carrier and beam selection in “draining” interference. Moreover, the overall network spectral efficiency improves by over 15 %, and the energy per bit is reduced, indicating a more sustainable operation.

The paper’s contributions can be summarized as follows:

1. Joint Frequency‑Spatial Resource Allocation: By integrating sub‑carrier selection with beamforming decisions in a cooperative game, the work transcends traditional one‑dimensional resource management.
2. Macro‑Cell Power Adaptation: The modified water‑filling policy enables each MUE to exploit the most favorable spatial DoFs, turning the macro tier into an active participant in interference avoidance.
3. Demonstrated System‑Level Gains: Extensive simulations with realistic antenna configurations and user densities validate that both tiers achieve substantial throughput improvements without requiring additional spectrum.

Future research directions suggested by the authors include extending the framework to handle user mobility and dynamic traffic loads, designing robust mechanisms against selfish or malicious SBS behavior, and integrating the proposed algorithms into emerging 5G NR and future 6G standards. Overall, the study provides a compelling blueprint for achieving harmonious macro‑small cell coexistence in next‑generation cellular networks.