3 research outputs found
Source-Channel Diversity for Parallel Channels
We consider transmitting a source across a pair of independent, non-ergodic
channels with random states (e.g., slow fading channels) so as to minimize the
average distortion. The general problem is unsolved. Hence, we focus on
comparing two commonly used source and channel encoding systems which
correspond to exploiting diversity either at the physical layer through
parallel channel coding or at the application layer through multiple
description source coding.
For on-off channel models, source coding diversity offers better performance.
For channels with a continuous range of reception quality, we show the reverse
is true. Specifically, we introduce a new figure of merit called the distortion
exponent which measures how fast the average distortion decays with SNR. For
continuous-state models such as additive white Gaussian noise channels with
multiplicative Rayleigh fading, optimal channel coding diversity at the
physical layer is more efficient than source coding diversity at the
application layer in that the former achieves a better distortion exponent.
Finally, we consider a third decoding architecture: multiple description
encoding with a joint source-channel decoding. We show that this architecture
achieves the same distortion exponent as systems with optimal channel coding
diversity for continuous-state channels, and maintains the the advantages of
multiple description systems for on-off channels. Thus, the multiple
description system with joint decoding achieves the best performance, from
among the three architectures considered, on both continuous-state and on-off
channels.Comment: 48 pages, 14 figure
Source-channel coding for robust image transmission and for dirty-paper coding
In this dissertation, we studied two seemingly uncorrelated, but conceptually
related problems in terms of source-channel coding: 1) wireless image transmission
and 2) Costa ("dirty-paper") code design.
In the first part of the dissertation, we consider progressive image transmission
over a wireless system employing space-time coded OFDM. The space-time coded
OFDM system based on a newly built broadband MIMO fading model is theoretically
evaluated by assuming perfect channel state information (CSI) at the receiver for
coherent detection. Then an adaptive modulation scheme is proposed to pick the
constellation size that offers the best reconstructed image quality for each average
signal-to-noise ratio (SNR).
A more practical scenario is also considered without the assumption of perfect
CSI. We employ low-complexity decision-feedback decoding for differentially space-
time coded OFDM systems to exploit transmitter diversity. For JSCC, we adopt a
product channel code structure that is proven to provide powerful error protection and
bursty error correction. To further improve the system performance, we also apply
the powerful iterative (turbo) coding techniques and propose the iterative decoding
of differentially space-time coded multiple descriptions of images.
The second part of the dissertation deals with practical dirty-paper code designs. We first invoke an information-theoretical interpretation of algebraic binning and
motivate the code design guidelines in terms of source-channel coding. Then two
dirty-paper code designs are proposed. The first is a nested turbo construction based
on soft-output trellis-coded quantization (SOTCQ) for source coding and turbo trellis-
coded modulation (TTCM) for channel coding. A novel procedure is devised to
balance the dimensionalities of the equivalent lattice codes corresponding to SOTCQ
and TTCM. The second dirty-paper code design employs TCQ and IRA codes for
near-capacity performance. This is done by synergistically combining TCQ with IRA
codes so that they work together as well as they do individually. Our TCQ/IRA
design approaches the dirty-paper capacity limit at the low rate regime (e.g., < 1:0
bit/sample), while our nested SOTCQ/TTCM scheme provides the best performs so
far at medium-to-high rates (e.g., >= 1:0 bit/sample). Thus the two proposed practical
code designs are complementary to each other
Dynamic information and constraints in source and channel coding
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 237-251).This thesis explore dynamics in source coding and channel coding. We begin by introducing the idea of distortion side information, which does not directly depend on the source but instead affects the distortion measure. Such distortion side information is not only useful at the encoder but under certain conditions knowing it at the encoder is optimal and knowing it at the decoder is useless. Thus distortion side information is a natural complement to Wyner-Ziv side information and may be useful in exploiting properties of the human perceptual system as well as in sensor or control applications. In addition to developing the theoretical limits of source coding with distortion side information, we also construct practical quantizers based on lattices and codes on graphs. Our use of codes on graphs is also of independent interest since it highlights some issues in translating the success of turbo and LDPC codes into the realm of source coding. Finally, to explore the dynamics of side information correlated with the source, we consider fixed lag side information at the decoder. We focus on the special case of perfect side information with unit lag corresponding to source coding with feedforward (the dual of channel coding with feedback).(cont.) Using duality, we develop a linear complexity algorithm which exploits the feedforward information to achieve the rate-distortion bound. The second part of the thesis focuses on channel dynamics in communication by introducing a new system model to study delay in streaming applications. We first consider an adversarial channel model where at any time the channel may suffer a burst of degraded performance (e.g., due to signal fading, interference, or congestion) and prove a coding theorem for the minimum decoding delay required to recover from such a burst. Our coding theorem illustrates the relationship between the structure of a code, the dynamics of the channel, and the resulting decoding delay. We also consider more general channel dynamics. Specifically, we prove a coding theorem establishing that, for certain collections of channel ensembles, delay-universal codes exist that simultaneously achieve the best delay for any channel in the collection. Practical constructions with low encoding and decoding complexity are described for both cases.(cont.) Finally, we also consider architectures consisting of both source and channel coding which deal with channel dynamics by spreading information over space, frequency, multiple antennas, or alternate transmission paths in a network to avoid coding delays. Specifically, we explore whether the inherent diversity in such parallel channels should be exploited at the application layer via multiple description source coding, at the physical layer via parallel channel coding, or through some combination of joint source-channel coding. For on-off channel models application layer diversity architectures achieve better performance while for channels with a continuous range of reception quality (e.g., additive Gaussian noise channels with Rayleigh fading), the reverse is true. Joint source-channel coding achieves the best of both by performing as well as application layer diversity for on-off channels and as well as physical layer diversity for continuous channels.by Emin Martinian.Ph.D