Assessment of the Sparsity-Diversity Trade-offs in Active Users Detection for mMTC with the Orthogonal Matching Pursuit

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: de Jesus, Gabriel Martins, Lopez, Onel Luis Alcaraz, Souza, Richard Demo, Mahmood, Nurul Huda, Juntti, Markku, Latva-Aho, Matti
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866915147094687744
author de Jesus, Gabriel Martins
Lopez, Onel Luis Alcaraz
Souza, Richard Demo
Mahmood, Nurul Huda
Juntti, Markku
Latva-Aho, Matti
author_facet de Jesus, Gabriel Martins
Lopez, Onel Luis Alcaraz
Souza, Richard Demo
Mahmood, Nurul Huda
Juntti, Markku
Latva-Aho, Matti
contents Wireless communication systems must increasingly support a multitude of machine-type communications (MTC) devices, thus calling for advanced strategies for active user detection (AUD). Recent literature has delved into AUD techniques based on compressed sensing, highlighting the critical role of signal sparsity. This study investigates the relationship between frequency diversity and signal sparsity in the AUD problem. Single-antenna users transmit multiple copies of non-orthogonal pilots across multiple frequency channels and the base station independently performs AUD in each channel using the orthogonal matching pursuit algorithm. We note that, although frequency diversity may improve the likelihood of successful reception of the signals, it may also damage the channel sparsity level, leading to important trade-offs. We show that a sparser signal significantly benefits AUD, surpassing the advantages brought by frequency diversity in scenarios with limited temporal resources and/or high numbers of receive antennas. Conversely, with longer pilots and fewer receive antennas, investing in frequency diversity becomes more impactful, resulting in a tenfold AUD performance improvement.
format Preprint
id arxiv_https___arxiv_org_abs_2402_05687
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Assessment of the Sparsity-Diversity Trade-offs in Active Users Detection for mMTC with the Orthogonal Matching Pursuit
de Jesus, Gabriel Martins
Lopez, Onel Luis Alcaraz
Souza, Richard Demo
Mahmood, Nurul Huda
Juntti, Markku
Latva-Aho, Matti
Information Theory
Signal Processing
Wireless communication systems must increasingly support a multitude of machine-type communications (MTC) devices, thus calling for advanced strategies for active user detection (AUD). Recent literature has delved into AUD techniques based on compressed sensing, highlighting the critical role of signal sparsity. This study investigates the relationship between frequency diversity and signal sparsity in the AUD problem. Single-antenna users transmit multiple copies of non-orthogonal pilots across multiple frequency channels and the base station independently performs AUD in each channel using the orthogonal matching pursuit algorithm. We note that, although frequency diversity may improve the likelihood of successful reception of the signals, it may also damage the channel sparsity level, leading to important trade-offs. We show that a sparser signal significantly benefits AUD, surpassing the advantages brought by frequency diversity in scenarios with limited temporal resources and/or high numbers of receive antennas. Conversely, with longer pilots and fewer receive antennas, investing in frequency diversity becomes more impactful, resulting in a tenfold AUD performance improvement.
title Assessment of the Sparsity-Diversity Trade-offs in Active Users Detection for mMTC with the Orthogonal Matching Pursuit
topic Information Theory
Signal Processing
url https://arxiv.org/abs/2402.05687