Simultaneous Interference Graph Estimation and Resource Allocation in Multi-Cell Multi-Numerology Networks

Resource allocation in multi-cell networks typically requires knowing the inter-cell interference channel gains. When multiple numerologies are employed, resource allocation further needs to estimate the inter-numerology interference within each cell. However, there lacks viable methods of interference graph estimation (IGE), depicting the intra- and inter-cell interference channel gains, for multi-cell multi-numerology networks. To fill this gap, we propose an efficient power-domain approach to IGE for the resource allocation in multi-cell multi-numerology networks. Unlike traditional reference signal-based approaches that consume frequency-time resources, our approach uses power as a new dimension for the estimation of channel gains. By carefully controlling the transmit powers of base stations, our approach is capable of estimating both the intra- and inter-cell interference channel gains, useful to resource allocation. Further, as a power-domain approach, it can be seamlessly integrated with the resource allocation in multi-numerology networks, such that IGE and resource allocation can be conducted simultaneously. We derive the necessary conditions for power-domain IGE and formulate the joint optimization problem of IGE and resource allocation. Our simulation results show that power-domain IGE can accurately estimate the interference channel gains and incurs low power overhead.