Rate-Distortion Performance of Sequential Massive Random Access to Gaussian Sources with Memory

01/17/2018
by   Elsa Dupraz, et al.
0

In Sequential Massive Random Access (SMRA), a set of correlated sources is jointly encoded and stored on a server, and clients want to access to only a subset of the sources. Since the number of simultaneous clients can be huge, the server is only authorized to extract a bitstream from the stored data: no re-encoding can be performed before the transmission of a request. In this paper, we investigate the SMRA performance of lossy source coding of Gaussian sources with memory. In practical applications such as Free Viewpoint Television, this model permits to take into account not only inter but also intra correlation between sources. For this model, we provide the storage and transmission rates that are achievable for SMRA under some distortion constraint, and we consider two particular examples of Gaussian sources with memory.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/05/2018

Lossy Transmission of Correlated Sources over Two-Way Channels

Achievability and converse results for the lossy transmission of correla...
research
06/14/2022

Two-terminal source coding with common sum reconstruction

We present the problem of two-terminal source coding with Common Sum Rec...
research
04/10/2018

The Sum-Rate-Distortion Region of Correlated Gauss-Markov Sources

We derive the sum-rate-distortion region for a generic number of success...
research
03/07/2022

D-semifaithful codes that are universal over both memoryless sources and distortion measures

We prove the existence of codebooks for d-semifaithful lossy compression...
research
08/01/2021

Experimental Findings on the Sources of Detected Unrecoverable Errors in GPUs

We investigate the sources of Detected Unrecoverable Errors (DUEs) in GP...
research
11/05/2020

Incremental Refinements and Multiple Descriptions with Feedback

It is well known that independent (separate) encoding of K correlated so...
research
10/26/2018

Information Bottleneck Methods for Distributed Learning

We study a distributed learning problem in which Alice sends a compresse...

Please sign up or login with your details

Forgot password? Click here to reset