Wireless Network Topology Inference: A Markov Chains Approach
We address the problem of inferring the topology of a wireless network using limited observational data. Specifically, we assume that we can detect when a node is transmitting, but no further information regarding the transmission is available. We propose a novel network estimation procedure grounde...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Communications Society |
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| Online Access: | https://ieeexplore.ieee.org/document/11062658/ |
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| author | James Martin Tristan Pryer Luca Zanetti |
| author_facet | James Martin Tristan Pryer Luca Zanetti |
| author_sort | James Martin |
| collection | DOAJ |
| description | We address the problem of inferring the topology of a wireless network using limited observational data. Specifically, we assume that we can detect when a node is transmitting, but no further information regarding the transmission is available. We propose a novel network estimation procedure grounded in the following abstract problem: estimating the parameters of a finite discrete-time Markov chain by observing, at each time step, which states are visited by multiple “anonymous” copies of the chain. We develop a consistent estimator that approximates the transition matrix of the chain in the operator norm, with the number of required samples scaling roughly linearly with the size of the state space. Applying this estimation procedure to wireless networks, our numerical experiments demonstrate that the proposed method accurately infers network topology across a wide range of parameters, consistently outperforming transfer entropy, particularly under conditions of high network congestion. |
| format | Article |
| id | doaj-art-7abbc3e534b447ce8bb75f36972ec35a |
| institution | Kabale University |
| issn | 2644-125X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Communications Society |
| spelling | doaj-art-7abbc3e534b447ce8bb75f36972ec35a2025-08-20T03:50:45ZengIEEEIEEE Open Journal of the Communications Society2644-125X2025-01-0165584559810.1109/OJCOMS.2025.358456311062658Wireless Network Topology Inference: A Markov Chains ApproachJames Martin0https://orcid.org/0009-0009-8935-6188Tristan Pryer1Luca Zanetti2https://orcid.org/0000-0002-4667-2764Institute for Mathematical Innovation, University of Bath, Bath, U.K.Institute for Mathematical Innovation, University of Bath, Bath, U.K.Institute for Mathematical Innovation, University of Bath, Bath, U.K.We address the problem of inferring the topology of a wireless network using limited observational data. Specifically, we assume that we can detect when a node is transmitting, but no further information regarding the transmission is available. We propose a novel network estimation procedure grounded in the following abstract problem: estimating the parameters of a finite discrete-time Markov chain by observing, at each time step, which states are visited by multiple “anonymous” copies of the chain. We develop a consistent estimator that approximates the transition matrix of the chain in the operator norm, with the number of required samples scaling roughly linearly with the size of the state space. Applying this estimation procedure to wireless networks, our numerical experiments demonstrate that the proposed method accurately infers network topology across a wide range of parameters, consistently outperforming transfer entropy, particularly under conditions of high network congestion.https://ieeexplore.ieee.org/document/11062658/Markov chainstopology inferencewireless networks |
| spellingShingle | James Martin Tristan Pryer Luca Zanetti Wireless Network Topology Inference: A Markov Chains Approach IEEE Open Journal of the Communications Society Markov chains topology inference wireless networks |
| title | Wireless Network Topology Inference: A Markov Chains Approach |
| title_full | Wireless Network Topology Inference: A Markov Chains Approach |
| title_fullStr | Wireless Network Topology Inference: A Markov Chains Approach |
| title_full_unstemmed | Wireless Network Topology Inference: A Markov Chains Approach |
| title_short | Wireless Network Topology Inference: A Markov Chains Approach |
| title_sort | wireless network topology inference a markov chains approach |
| topic | Markov chains topology inference wireless networks |
| url | https://ieeexplore.ieee.org/document/11062658/ |
| work_keys_str_mv | AT jamesmartin wirelessnetworktopologyinferenceamarkovchainsapproach AT tristanpryer wirelessnetworktopologyinferenceamarkovchainsapproach AT lucazanetti wirelessnetworktopologyinferenceamarkovchainsapproach |