Sparse Coding Techniques for Adjustable Lossy Compression of Baseband Signals in Centralized and Virtualized Communication Systems - IMT Atlantique Access content directly
Conference Papers Year : 2024

Sparse Coding Techniques for Adjustable Lossy Compression of Baseband Signals in Centralized and Virtualized Communication Systems

Abstract

This paper presents an efficient lossy compression method based on sparse coding for received noisy signals (RX) in satellite communication systems. The emergence of ground station as a service (GSaaS) and centralized radio access net- works (C-RAN) requires efficient data transfers between ground stations and datacenters. Our approach employs sparse coding to compress baseband signals via offline trained dictionaries. We analyze the loss introduced by compression and its impact on common modulation schemes across a Gaussian channel using the Bit Error Rate (BER) measurement. Additionally, the proposed method is compared to lossless linear prediction coding (LPC) and uniform quantization. Our study highlights the potential of lossy sparse coding to reduce bandwidth requirements while preserving signal integrity by offering a potential compression ratio of up to 8% higher than existing methods for the same degradation.
Fichier principal
Vignette du fichier
Camera ready - Sparsity.pdf (1.93 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04588541 , version 1 (27-05-2024)

Identifiers

  • HAL Id : hal-04588541 , version 1

Cite

Thibault Piana, Abdeldjalil Aissa El Bey, Matthieu Arzel, Alain Thomas. Sparse Coding Techniques for Adjustable Lossy Compression of Baseband Signals in Centralized and Virtualized Communication Systems. 32nd European Signal Processing Conference EUSIPCO, Aug 2024, Lyon, France. ⟨hal-04588541⟩
33 View
23 Download

Share

Gmail Mastodon Facebook X LinkedIn More