Scalable Network Tomography for Dynamic Spectrum Access
Published in IEEE Infocom, 2024
Recommended citation: A. Madnaik, N. C. Matson and K. Sundaresan, "Scalable Network Tomography for Dynamic Spectrum Access," IEEE INFOCOM 2024 - IEEE Conference on Computer Communications, Vancouver, Canada, 2024 https://arxiv.org/abs/2403.03376
This paper is about NeTo-X, a scalable network tomography framework which estimates joint client access statistics with just linear overhead, and forms a blue-print of the interference, thus enabling efficient DSA for future networks. NeTo-X’s design incorporates intelligent algorithms that leverage multi-channel diversity and the spatial locality of interference impact on clients to accurately estimate the desired interference statistics from just pair-wise measurements of its clients. The merits of its framework are showcased in the context of resource management and jammer localization applications, where its performance significantly outperforms baseline approaches and closely approximates optimal performance at a scalable overhead.
