Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Jie Wang 0144

dblp:29/5259-144 · DBLP profile ↗
← Back
2ranked-venue papers
2as first author
2since 2021 · last 2025
0000-0002-8185-001XORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 2 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Software-defined and programmable networks · 33% Wireless sensing and localization · 33% Physical-layer communications · 33%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › signal processing for communications
signal separation
0.512021
A Compliance Monitoring System for Open SDR Platforms · SenSys 2021
Wireless sensing and localization › RF sensing
spectrum monitoring
0.512021
A Compliance Monitoring System for Open SDR Platforms · SenSys 2021

Methods — techniques the papers use, named apart from their topics

signal separation · 0.5linear system model estimation · 0.5
YearPublicationVenuePosition
2025 Augmenting channel estimation via loss field: Site-trained Bayesian modeling and comparative analysis
Jie Wang 0144, Meles G. Weldegebriel, Neal Patwari
Comput. Networks1
2021 A Compliance Monitoring System for Open SDR Platforms
abstract
Next-generation wireless experimentation benefits from new large-scale open-access software defined radio (SDR) platforms. Each SDR's transmissions must be measured and monitored to guarantee spectrum compliance. The measured spectrum is, however, corrupted by external co-channel signals. This demo presents the Bidirectional Incident/Transmit Signal Separator (BITSS), a system which estimates the linear system model, the SDR's transmit signal, and the signals from other sources incident to the antenna, all on the fly and without a signal prior or system information. We implement and run BITSS on POWDER and evaluate its performance. The demo shows that BITSS enables separation over a range of signal parameters with high accuracy and alerts users and the operator whenever a spectrum violation occurs.
Jie Wang 0144, Jacobus E. van der Merwe, Neal Patwari
SenSys1