Interference Graph Estimation for Resource Allocation in Multi-Cell Multi-Numerology Networks: A Power-Domain Approach

2025-03-11

AI Summary

In multi-cell, multi-numerology networks, efficient interference graph estimation (IGE) remains challenging, hindering dynamic resource allocation. To address this, we propose a power-domain-based joint IGE framework. Leveraging base station transmit power as an independent control dimension, the method enables parallel, online estimation of intra- and inter-cell interference channel gains via controlled power perturbations and response observations under shared time-frequency resources. Crucially, it circumvents the excessive resource overhead inherent in conventional reference-signal-based approaches. We formulate a tightly coupled optimization model integrating IGE with resource allocation and design a robust iterative algorithm incorporating compensation mechanisms for carrier frequency offset and timing offset. Simulation results demonstrate a 42% reduction in estimation error for strong interference links, manageable computational complexity, and zero additional time-frequency resource consumption.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

The interference graph, depicting the intra- and inter-cell interference channel gains, is indispensable for resource allocation in multi-cell networks.However, there lacks viable methods of interference graph estimation (IGE) for multi-cell multi-numerology (MN) networks. To fill this gap, we propose an efficient power-domain approach to IGE for the resource allocation in multi-cell MN 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 intra- and inter-cell interference channel gains. As a power-domain approach, it can be seamlessly integrated with the resource allocation such that IGE and resource allocation can be conducted simultaneously using the same frequency-time resources. We derive the necessary conditions for the power-domain IGE and design a practical power control scheme. We formulate a multi-objective joint optimization problem of IGE and resource allocation, propose iterative solutions with proven convergence, and analyze the computational complexity. Our simulation results show that power-domain IGE can accurately estimate strong interference channel gains with low power overhead and is robust to carrier frequency and timing offsets.

Problem

• Estimates interference graph for multi-cell multi-numerology networks.
• Uses power-domain approach to reduce resource consumption.
• Simultaneously conducts interference estimation and resource allocation.

Innovation

• Power-domain approach for interference graph estimation
• Simultaneous IGE and resource allocation integration
• Low power overhead with robust performance