Scalable Network Tomography for Dynamic Spectrum Access

Fuente: arXiv
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Autori principali: Madnaik, Aadesh, Matson, N. Cameron, Sundaresan, Karthikeyan
Natura: Preprint
Pubblicazione: 2024
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author Madnaik, Aadesh
Matson, N. Cameron
Sundaresan, Karthikeyan
author_facet Madnaik, Aadesh
Matson, N. Cameron
Sundaresan, Karthikeyan
contents Mobile networks have increased spectral efficiency through advanced multiplexing strategies that are coordinated by base stations (BS) in licensed spectrum. However, external interference on clients leads to significant performance degradation during dynamic (unlicensed) spectrum access (DSA). We introduce the notion of network tomography for DSA, whereby clients are transformed into spectrum sensors, whose joint access statistics are measured and used to account for interfering sources. Albeit promising, performing such tomography naively incurs an impractical overhead that scales exponentially with the multiplexing order of the strategies deployed -- which will only continue to grow with 5G/6G technologies. To this end, we propose a novel, scalable network tomography framework called NeTo-X that 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_03376
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Scalable Network Tomography for Dynamic Spectrum Access
Madnaik, Aadesh
Matson, N. Cameron
Sundaresan, Karthikeyan
Networking and Internet Architecture
C.2.1; C.2.2; G.3
Mobile networks have increased spectral efficiency through advanced multiplexing strategies that are coordinated by base stations (BS) in licensed spectrum. However, external interference on clients leads to significant performance degradation during dynamic (unlicensed) spectrum access (DSA). We introduce the notion of network tomography for DSA, whereby clients are transformed into spectrum sensors, whose joint access statistics are measured and used to account for interfering sources. Albeit promising, performing such tomography naively incurs an impractical overhead that scales exponentially with the multiplexing order of the strategies deployed -- which will only continue to grow with 5G/6G technologies. To this end, we propose a novel, scalable network tomography framework called NeTo-X that 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.
title Scalable Network Tomography for Dynamic Spectrum Access
topic Networking and Internet Architecture
C.2.1; C.2.2; G.3
url https://arxiv.org/abs/2403.03376