ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / This paper considers the joint selection of the source code rate and channel code rate in an image telemetry system. Specifically considered is the JPEG2000 image coder and an LDPC code family. The goal is to determine the optimum apportioning of bits between the source and channel codes for a given channel signal-to-noise ratio and total bit rate, R(total). Optimality is in the sense of maximum peak image SNR and the tradeoff is between the JPEG2000 bit rate R(source) and the LDPC code rate R(channel). For comparison, results are included for the industry standard rate-1/2, memory-6 convolutional code.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / A practical joint source/channel coding algorithm is proposed for the transmission of multiple images and videos to reduce the overall reconstructed source distortion at the receiver within a given total bit rate. It is demonstrated that by joint coding of multiple sources with such an objective, both improved distortion performance as well as reduced quality variation can be achieved at the same time. Experimental results based on multiple images and video sequences justify our conclusion.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / This paper presents a joint source-channel decoding scheme based on a JPEG2000 source coder and an LDPC channel coder. At the encoder, JPEG2000 is used to perform source coding with certain error resilience (ER) modes, and LDPC codes are used to perform channel coding. At the decoder, after one iteration of LDPC decoding, the output codestream is then decoded by JPEG2000. With the error resilience mode switches on, the source decoder detects the position of the first error within each codeblock of the JPEG2000 codestream. This information is fed back to the channel decoder, and incorporated into the calculation of likelihood values of variable nodes for the next iteration of LDPC decoding. Our results indicate that the proposed method has significant gains over conventional separate channel and source decoding.

This dissertation is divided into two main topics. In the first topic, we study the joint source-channel coding problem of transmitting an analog source over a Gaussian channel in two cases - (i) the presence of interference known only to the transmitter and (ii) in the presence of side information about the source known only to the receiver. We introduce hybrid digital analog forms of the Costa and Wyner-Ziv coding schemes. We present random coding based schemes in contrast to lattice based schemes proposed by Kochman and Zamir. We also discuss superimposed digital and analog schemes for the above problems which show that there are infinitely many schemes for achieving the optimal distortion for these problems. This provides an extension of the schemes proposed by Bross and others to the interference/source side information case. The result of this study shows that the proposed hybrid digital analog schemes are more robust to a mismatch in channel signal-to-noise ratio (SNR), than pure separate source coding followed by channel coding solutions. We then discuss applications of the hybrid digital analog schemes for transmitting under a channel SNR mismatch and for broadcasting a Gaussian source with bandwidth compression. We also study applications of joint source-channel coding schemes for a cognitive setup and also for the setup of transmitting an analog Gaussian source over a Gaussian channel, in the presence of an eavesdropper. In the next topic, we consider joint physical layer coding and network coding solutions for bi-directional relaying. We consider a communication system where two transmitters wish to exchange information through a central relay. The transmitter and relay nodes exchange data over synchronized, average power constrained additive white Gaussian noise channels. We propose structured coding schemes using lattices for this problem. We study two decoding approaches, namely lattice decoding and minimum angle decoding. Both the decoding schemes can be shown to achieve the upper bound at high SNRs. The proposed scheme can be thought of as a joint physical layer, network layer code which outperforms other recently proposed analog network coding schemes. We also study extensions of the bi-directional relay for the case with asymmetric channel links and also for the multi-hop case. The result of this study shows that structured coding schemes using lattices perform close to the upper bound for the above communication system models.

This thesis proposes a framework for combined source-channel coding under power and bandwidth constrained noisy channel. The framework is then applied to progressive image coding transmission using constant envelope M-ary Phase Shift Key (MPSK) signaling over an Additive White Gaussian Channel (AWGN) channel. First the framework for uncoded MPSK signaling is developed. Then, it’s extended to include coded modulation using Trellis Coded Modulation (TCM) for MPSK signaling. Simulation results show that coded MPSK signaling performs 3.1 to 5.2 dB better than uncoded MPSK signaling depending on the constellation size. Finally, an adaptive TCM system is presented for practical implementation of the proposed scheme, which outperforms uncoded MPSK system over all signal to noise ratio (Es/No) ranges for various MPSK modulation formats. In the second part of this thesis, the performance of the scheme is investigated from the channel capacity point of view. Using powerful channel codes like Turbo and Low Density Parity Check (LDPC) codes, the combined source-channel coding scheme is shown to be within 1 dB of the performance limit with MPSK channel signaling.

We study the problem of communicating a discrete time analog source over a channel such that the resulting distortion is minimized. For ergodic channels, Shannon showed that separate source and channel coding is optimal. In this work we study this problem for non-ergodic channels. Although not much can be said about the general problem of transmitting any analog sources over any non-ergodic channels with any distortion metric, for many practical problems like video broadcast and voice transmission, we can gain insights by studying the transmission of a Gaussian source over a wireless channel with mean square error as the distortion measure. Motivated by different applications, we consider three different non-ergodic channel models - (1) Additive white Gaussian noise (AWGN) channel whose signal-to-noise ratio (SNR) is unknown at the transmitter; (2) Rayleigh fading multiple-input multiple-output MIMO channel whose SNR is known at the transmitter; and (3) Rayleigh fading MIMO channel whose SNR is unknown at the transmitter. The traditional approach to study these problems has been to fix certain SNRs of interest and study the corresponding achievable distortion regions. However, the problems formulated this way have not been solved even for simple setups like 2 SNRs for the AWGN channel. We are interested in performance over a wide range of SNR and hence we use the distortion SNR exponent metric to study this problem. Distortion SNR exponent is defined as the rate of decay of distortion with SNR in the high SNR limit. We study several layered transmissions schemes where the source is first compressed in layers and then the layers are transmitted using channel codes that provide variable error protection. Results show that in several cases such layered transmission schemes are optimal in terms of the distortion SNR exponent. Specifically, if the band- width expansion (number of channel uses per source sample) is b, we show that the optimal distortion SNR exponent for the AWGN channel is b and it is achievable using a superposition based layered scheme. For the L-block Rayleigh fading M x N MIMO channel the optimal exponent is characterized for b < (|N - M|+1)= min(M;N) and b > MNL2. This corresponds to the entire range of b when min(M;N) = 1 and L = 1. The results also show that the exponents obtained using layered schemes which are a small subclass of joint source channel coding (JSCC) schemes are, surprisingly, as good as and better in some cases than achievable exponent of all other JSCC schemes reported so far.

Joint source-channel coding (JSCC) has been acknowledged to have superior performance over separate source-channel coding in terms of coding efficiency, delay and complexity. In the first part of this thesis, we study a hybrid digital-analog (HDA) JSCC system to transmit a memoryless Gaussian source over a memoryless Gaussian channel under bandwidth compression. Information-theoretic upper bounds on the asymptotically optimal mean squared error distortion of the system are obtained. An allocation scheme for distributing the channel input power between the analog and the digital signals is derived for the HDA system with mismatched channel conditions. A low-complexity and low-delay version of the system is next designed and implemented. We then propose an image communication application demonstrating the effectiveness of HDA coding. In the second part of this thesis, we consider problems in information hiding. We begin by considering a single-user joint compression and private watermarking (JCPW) problem. For memoryless Gaussian sources and memoryless Gaussian attacks, an exponential upper bound on the probability of error in decoding the watermark is derived. Numerical examples show that the error exponent is positive over a (large) subset of the entire achievable region derived by Karakos and Papamarcou (2003). We then extend the JCPW problem to a multi-user setting. Two encoders independently embed two secret information messages into two correlated host sources subject to a pair of tolerable distortion levels. The (compressed) outputs are subject to multiple access attacks. The tradeoff between the achievable watermarking rates and the compression rates is studied for discrete memoryless host sources and discrete memoryless multiple access channels. We derive an inner bound and an outer bound with single-letter characterization for the achievable compression and watermarking rate region. We next consider a problem where two correlated sources are separately embedded into a common host source. A single-letter sufficient condition is established under which the sources can be successfully embedded into the host source under multiple access attacks. Finally, we investigate a public two-user information hiding problem under multiple access attacks. Inner and outer bounds for the embedding capacity region are obtained with single-letter characterization. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2007-09-28 23:11:21.398

Joint source-channel coding (JSCC) has emerged to be a major field of research recently. Channel optimized vector quantization (COVQ) is a simple feasible JSCC scheme introduced for communication over practical channels. In this work, we propose an iterative design algorithm, referred to as the iterative maximum a posteriori (MAP) decoded (IMD) algorithm, to improve COVQ systems. Based on this algorithm, we design a COVQ based on symbol MAP hard-decision demodulation that exploits the non-uniformity of the quantization indices probability distribution. The IMD design algorithm consists of a loop which starts by designing a COVQ, obtaining the index source distribution, updating the discrete memoryless channel (DMC) according to the achieved index distribution, and redesigning the COVQ. This loop stops when the point-to-point distortion is minimized. We consider memoryless Gaussian and Gauss-Markov sources transmitted over binary phase-shift keying modulated additive white Gaussian noise (AWGN) and Rayleigh fading channels. Our scheme, which is shown to have less encoding complexity than conventional COVQ and less encoding complexity and storage requirements than soft-decision demodulated (SDD) COVQ systems, is also shown to provide a notable signal-to-distortion ratio (SDR) gain over the conventional COVQ designed for hard-decision demodulated channels while sometimes matching or exceeding the SDD COVQ performance, especially for higher quantization dimensions and/or rates. In addition to our main result, we also propose another iterative algorithm to design SDD COVQ based on the notion of the JSCC error exponent. This system is shown to have some gain over classical SDD COVQ both in terms of the SDR and the exponent itself. / Thesis (Master, Mathematics & Statistics) -- Queen's University, 2008-08-29 17:58:52.329

International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / A joint source-channel coding scheme (JSCCS) used in applications, like sending images, voice, music etc. over internet/ wireless networks, involves source coding to compress the information and channel coding to detect/ correct errors, introduced by the channel. In this paper, we investigate the unequal error protection (UEP) capability of a class of low-density parity-check (LDPC) codes in a JSCCS. This class of irregular LDPC codes is constructed from cyclic difference families (CDFs).

<p>In this thesis an approach to joint source-channel coding using direct source to channel mappings is studied. The system studied communicates i.i.d. Gaussian sources on a point-to-point Gaussian memoryless channel with limited feedback (supporting channel state information at most). The mappings, named Shannon-Kotel'nikov (SK) mappings, are memoryless mappings between the source space of dimension M and the channel space of dimension N. Such mappings can be used for error control when M<N, called dimension expansion, and for lossy compression when M>N, called dimension reduction. The SK-mappings operate on amplitude continuous and time discrete signals (meaning that there is no bits involved) through (piecewise) continuous curves or hyper surfaces in general.</p><p>The reason for studying SK-mappings is that they are delay free, robust against varying channel conditions, and have quite good performance at low complexity.</p><p>First a theory for determining and categorizing the distortion using SK-mappings for communication is introduced and developed. This theory is further used to show that SK-mappings can reach the information theoretical bound optimal performance theoretically attainable (OPTA) when their dimension approach infinity.</p><p>One problem is to determine the overall optimal geometry of the SK-mappings. Indications on the overall geometry can be found by studying the codebooks and channel constellations of power constrained channel optimized vector quantizers (PCCOVQ). The PCCOVQ algorithm will find the optimal placing of quantizer representation vectors in the source space and channel symbols in the channel space. A PCCOVQ algorithm giving well performing mappings for the dimension reduction case has been found in the past. In this thesis the PCCOVQ algorithm is modified to give well performing dimension expanding mappings for scalar sources, and 1:2 and 1:3 PCCOVQ examples are given.</p><p>Some example SK-mappings are proposed and analyzed. 2:1 and 1:2 PCCOVQ mappings are used as inspiration for making 2:1 and 1:2 SK-mappings based on the Archimedean spiral. Further 3:1, 4:1, 3:2 and 2:3 SK-mappings are found and analyzed. All example SK-mappings are modeled mathematically using the proposed theory on SK-mappings. These mathematical models are further used to find the optimal coefficients for all the proposed SK-mappings as a function of the channel signal-to-noise ratio (CSNR), making adaptations to varying channel conditions simple.</p>