Lossy Source Coding with Broadcast Side Information
🤖 AI Summary
This work investigates lossy source coding with side information delivered over a noisy broadcast channel to two receivers. Within this setting, the study leverages the rate–distortion–bandwidth (RDB) theoretical framework and employs information-theoretic analysis combined with broadcast channel modeling to establish, for the first time, an outer bound on the RDB region. Furthermore, an achievable region is constructed using a separation-based coding architecture. Under Gaussian sources and quadratic distortion, the paper fully characterizes the RDB performance limits and explicitly demonstrates the superiority of separation-based coding over uncoded schemes through comparative analysis.
Application Category
📝 Abstract
This paper considers the source coding problem with broadcast side information. The side information is sent to two receivers through a noisy broadcast channel. We provide an outer bound of the rate--distortion--bandwidth (RDB) quadruples and achievable RDB quadruples when the helper uses a separation-based scheme. Some special cases with full characterization are also provided. We then compare the separation-based scheme with the uncoded scheme in the quadratic Gaussian case.
Problem
Research questions and friction points this paper is trying to address.
Lossy Source Coding
Broadcast Side Information
Rate-Distortion-Bandwidth
Noisy Broadcast Channel
Quadratic Gaussian
Innovation
Methods, ideas, or system contributions that make the work stand out.
broadcast side information
lossy source coding
rate-distortion-bandwidth tradeoff
separation-based scheme
Gaussian quadratic distortion
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