Blind Source Separation for ALOHA Massive Machine Type Communications

This paper studies the use of Blind Source Separation (BSS) as a replacement for Coded Random Access in diversity ALOHA massive machine-type communications. We propose a scheme for efficiently implementing BSS within the ALOHA framework, while also determining the number of active users in each slot. We experimentally evaluate the achievable performance and highlight the factors that influence the number of detectable users.

Authors

Institutions

Publication Details

Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174549
Citations
1
Primary Topic
Wireless Communication Networks Research
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Blind Source Separation for ALOHA Massive Machine Type Communications

Alberto Carini, F. Babich, Michele Godeas
1 citations
Wireless Communication Networks Research
1.49
article

Blind Source Separation for ALOHA Massive Machine Type Communications

Alberto Carini, F. Babich, Michele Godeas
article en
1 citations

Abstract

This paper studies the use of Blind Source Separation (BSS) as a replacement for Coded Random Access in diversity ALOHA massive machine-type communications. We propose a scheme for efficiently implementing BSS within the ALOHA framework, while also determining the number of active users in each slot. We experimentally evaluate the achievable performance and highlight the factors that influence the number of detectable users.

University of Trieste (IT)
Openalex Percentile: Top 13%
Wireless Communication Networks Research
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Blind Source Separation for ALOHA Massive Machine Type Communications — Alberto Carini, F. Babich, et al. · (2025) | TGRS Research Map | TGRS