3 research outputs found
Joint Source-Channel Coding at the Application Layer for Parallel Gaussian Sources
In this paper the multicasting of independent parallel Gaussian sources over
a binary erasure broadcasted channel is considered. Multiresolution embedded
quantizer and layered joint source-channel coding schemes are used in order to
serve simultaneously several users at different channel capacities. The convex
nature of the rate-distortion function, computed by means of reverse
water-filling, allows us to solve relevant convex optimization problems
corresponding to different performance criteria. Then, layered joint
source-channel codes are constructed based on the concatenation of embedded
scalar quantizers with binary rateless encoders.Comment: 5 pages, 4 figures, submitted to ISIT-0
Scalar Quantizer Design for Two-Way Channels
The problem of lossy transmission of correlated sources over memoryless
two-way channels (TWCs) is considered. The objective is to develop a robust low
delay and low complexity source-channel coding scheme without using error
correction. A simple full-duplex channel optimized scalar quantization (COSQ)
scheme that implicitly mitigates TWC interference is designed. Numerical
results for sending Gaussian bivariate sources over binary additive-noise TWCs
with either additive or multiplicative user interference show that, in terms of
signal-to-distortion ratio performance, the proposed full-duplex COSQ scheme
compares favourably with half-duplex COSQ.Comment: the manuscript upload on arXiv is an updated version of the one
published in the CWIT'2019 Proceeding
Joint Source-Channel Coding at the Application Layer for Parallel Gaussian Sources
Abstract β In this paper the multicasting of independent parallel Gaussian sources over a binary erasure broadcasted channel is considered. Multiresolution embedded quantizer and layered joint source-channel coding schemes are used in order to serve simultaneously several users at different channel capacities. The convex nature of the rate-distortion function, computed by means of reverse water-filling, allows us to solve relevant convex optimization problems corresponding to different performance criteria. Then, layered joint source-channel codes are constructed based on the concatenation of embedded scalar quantizers with binary rateless encoders. I