arXiv subjects

Eleni Gkiouzepi

Publications and source records attributed to Eleni Gkiouzepi.

4 recordsLinked to original sources

arXiv2026

Joint Random Access and Localization in Cell-Free User-Centric Networks with Frequency-Selective Fading Channels

We study random access (RACH) schemes for cell-free (CF) user-centric networks to handle many geographically distributed users with sporadic traffic and intermittent activity. The RACH must allow the system to: 1) detect preambles sent by the (yet unknown) random access users in the RACH slot; 2) localize them for fast allocation of user-centric radio-unit (RU) clusters. Most prior work uses simplified models, neglecting frame-synchronous but chip-asynchronous transmission, possible line-of-sight (LoS) propagation for certain user-RU pairs, and multipath non-line-of-sight (NLoS) propagation yielding frequency-selective channels. Building on our previous work, we consider location-dependent partitioned random access codebooks where users in a geographic area (location) use the corresponding subset of random access preambles. We present a unified framework for joint detection and localization over a spatially consistent network-wide channel model, incorporating these neglected aspects. We evaluate two schemes: 1) a ``legacy'' scheme using Zadoff-Chu (ZC) sequences, extending the 3GPP 2-step RACH to the CF case; 2) our multisource approximate message passing (AMP) approach extended to multipath frequency-selective fading. For both schemes, we develop novel approximated GLRT preamble detection and Maximum-Likelihood position estimators with super-resolution refinement, implicitly exploiting received signal strength, angle of arrival, and time-difference of arrival information embedded into LoS components. Numerical results show that the AMP-based scheme achieves superior preamble detection, while both schemes have similar and excellent localization capability.

cs.IT↗

arXiv2026

Random Access and Localization in Cell-Free User-Centric Networks with Multipath Channels

In a wireless network, the initial/random access mechanism (RACH) allows idle/new users to join the network and (possibly) request allocated transmission resources for subsequent traffic. Building on our own previous work, for cell-free user-centric networks, we consider location-dependent random access codebooks such that users in a certain geographic area (location) make use of the corresponding set of random access preambles (codewords). We expand our previous work in two ways: (1) we consider multipath channels with line-of-sight (LoS) propagation within a given radius; (2) we consider two different approaches. The first makes use of Zadoff-Chu (ZC) sequences and GLRT detection to cope with the unknown delay, and it is conceptually similar to the 3GPP 2-step RACH specification (here extended to the cell-free case). The second builds on our previous work on multisource approximate message passing (AMP). For both schemes, we also consider a novel near Maximum-Likelihood approach for localization of the random access users directly from the detected RACH preambles, implicitly using angle of arrival and time difference of arrival information embedded into the LoS components. Simulation results show that the AMP approach achieves generally better performance for random access user detection, while both approaches have similar localization capability with a slight superiority for the frequency-domain scheme.

cs.IT↗

arXiv2025

Joint Message Detection and Channel Estimation for Unsourced Random Access in Cell-Free User-Centric Wireless Networks

We consider unsourced random access (uRA) in a cell-free (CF) user-centric wireless network, where a large number of potential users compete for a random access slot, while only a finite subset is active. The random access users transmit codewords of length $L$ symbols from a shared codebook, which are received by $B$ geographically distributed radio units (RUs) equipped with $M$ antennas each. Our goal is to devise and analyze a \emph{centralized} decoder to detect the transmitted messages (without prior knowledge of the active users) and estimate the corresponding channel state information. A specific challenge lies in the fact that, due to the geographically distributed nature of the CF network, there is no fixed correspondence between codewords and large-scale fading coefficients (LSFCs). This makes current activity detection approaches which make use of this fixed LSFC-codeword association not directly applicable. To overcome this problem, we propose a scheme where the access codebook is partitioned in location-based subcodes, such that users in a particular location make use of the corresponding subcode. The joint message detection and channel estimation is obtained via a novel {\em Approximated Message Passing} (AMP) algorithm for a linear superposition of matrix-valued sources corrupted by noise. The statistical asymmetry in the fading profile and message activity leads to \emph{different statistics} for the matrix sources, which distinguishes the AMP formulation from previous cases. In the regime where the codebook size scales linearly with $L$, while $B$ and $M$ are fixed, we present a rigorous high-dimensional (but finite-sample) analysis of the proposed AMP algorithm. Exploiting this, we then present a precise (and rigorous) large-system analysis of the message missed-detection and false-alarm rates, as well as the channel estimation mean-square error.

cs.IT↗

arXiv2024

Joint Message Detection, Channel, and User Position Estimation for Unsourced Random Access in Cell-Free Networks

We consider unsourced random access (uRA) in user-centric cell-free (CF) wireless networks, where random access users send codewords from a common codebook during specifically dedicated random access channel (RACH) slots. The system is conceptually similar to the so-called 2-step RACH currently discussed in 3GPP standardization. In order to cope with the distributed and CF nature of the network, we propose to partition the network coverage area into zones (referred to as ''locations'') and assign an uRA codebook to each location, such that users in a certain location make use of the associated codebook. The centralized uRA decoder makes use of the multisource AMP algorithm recently proposed by the authors. This yields at once the list of active uRA codewords, an estimate of the corresponding channel vectors, and an estimate of the active users' position. We show excellent performance of this approach and perfect agreement with the rigorous theoretical ''state evolution'' analysis. We also show that the proposed ''location-based'' partitioned codebook approach significantly outperforms a baseline system with a single non-partitioned uRA codebook.

cs.IT↗