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

Fuente: arXiv
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Hauptverfasser: Ding, Daqian, Li, Haorui, Pi, Yibo, Wang, Xudong
Format: Preprint
Veröffentlicht: 2025
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author Ding, Daqian
Li, Haorui
Pi, Yibo
Wang, Xudong
author_facet Ding, Daqian
Li, Haorui
Pi, Yibo
Wang, Xudong
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2503_08082
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Interference Graph Estimation for Resource Allocation in Multi-Cell Multi-Numerology Networks: A Power-Domain Approach
Ding, Daqian
Li, Haorui
Pi, Yibo
Wang, Xudong
Networking and Internet Architecture
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.
title Interference Graph Estimation for Resource Allocation in Multi-Cell Multi-Numerology Networks: A Power-Domain Approach
topic Networking and Internet Architecture
url https://arxiv.org/abs/2503.08082