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.

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.

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

Compressed video bitstream transmissions over wireless networks are addressed in this work. We first consider error control and power allocation for transmitting wireless video over CDMA networks in conjunction with multiuser detection. We map a layered video bitstream to several CDMA fading channels and inject multiple source/parity layers into each of these channels at the transmitter. We formulate a combined optimization problem and give the optimal joint rate and power allocation for each of linear minimum mean-square error (MMSE) multiuser detector in the uplink and two types of blind linear MMSE detectors, i.e., the direct-matrix-inversion (DMI) blind detector and the subspace blind detector, in the downlink. We then present a multiple-channel video transmission scheme in wireless CDMA networks over multipath fading channels. For a given budget on the available bandwidth and total transmit power, the transmitter determines the optimal power allocations and the optimal transmission rates among multiple CDMA channels, as well as the optimal product channel code rate allocation. We also make use of results on the large-system CDMA performance for various multiuser receivers in multipath fading channels. We employ a fast joint source-channel coding algorithm to obtain the optimal product channel code structure. Finally, we propose an end-to-end architecture for multi-layer progressive video delivery over space-time differentially coded orthogonal frequency division multiplexing (STDC-OFDM) systems. We propose to use progressive joint source-channel coding to generate operational transmission distortion-power-rate (TD-PR) surfaces. By extending the rate-distortion function in source coding to the TD-PR surface in joint source-channel coding, our work can use the ??equal slope?? argument to effectively solve the transmission rate allocation problem as well as the transmission power allocation problem for multi-layer video transmission. It is demonstrated through simulations that as the wireless channel conditions change, these proposed schemes can scale the video streams and transport the scaled video streams to receivers with a smooth change of perceptual quality.

Shannon's classical separation result holds only in the limit of infinite source code dimension and infinite channel code block length. In addition, Shannon theory does not address the design of good source codes when the probability of channel error is nonzero, which is inevitable for finite-length channel codes. Thus, for practical systems, a joint source and channel code design could improve performance for finite dimension source code and finite block length channel code, as well as complexity and delay. Consider a multicast system over a broadcast channel, where different end users typically have different capacities. To support such user or capacity diversity, it is desirable to encode the source to be broadcasted into a scalable bit stream along which multiple resolutions of the source can be reconstructed progressively from left to right. Such source coding technique is called multiresolution source coding. In wireless communications, joint source channel coding (JSCC) has attracted wide attention due to its adaptivity to time-varying channels. However, there are few works on joint source channel coding for network multicast, especially for the optimal source coding over broadcast channels. In this work, we aim at designing and analyzing the optimal multiresolution vector quantization (MRVQ) in conjunction with the subsequent broadcast channel over which the coded scalable bit stream would be transmitted. By adopting random index assignment (RIA) to link MRVQ for the source with superposition coding for the broadcast channel, we establish a closed-form formula of end-to-end distortion for a tandem system of MRVQ and a broadcast channel. From this formula we analyze the intrinsic structure of end-to-end distortion (EED) in a communication system and derive two necessary conditions for optimal multiresolution vector quantization over broadcast channels with random index assignment. According to the two necessary conditions, we propose a greedy iterative algorithm for jointly designed MRVQ with channel conditions, which depends on the channel only through several types of average channel error probabilities rather than the complete knowledge of the channel. Experiments show that MRVQ designed by the proposed algorithm significantly outperforms conventional MRVQ designed without channel information. By building an closed-form formula for the weighted EED with RIA, it also makes the computational complexity incurred during the performance analysis feasible. In comparison with MRVQ design for a fixed index assignment, the computation complexity for quantization design is significantly reduced by using random index assignment. In addition, simulations indicate that our proposed algorithm shows better robustness against channel mismatch than MRVQ design with a fixed index assignment, simply due to the nature of using only the average channel information. Therefore, we conclude that our proposed algorithm is more appropriate in both wireless communications and applications where the complete knowledge of the channel is hard to obtain. Furthermore, we propose two novel algorithms for MRVQ over broadcast channels. One aims to optimize the two corresponding quantizers at two layers alternatively and iteratively, and the other applies under the constraint that each encoding cell is convex and contains the reconstruction point. Finally, we analyze the asymptotic performance of weighted EED for the optimal joint MRVQ. The asymptotic result provides a theoretically achievable quantizer performance level and sheds light on the design of the optimal MRVQ over broadcast channel from a different aspect.

Cooperative communication has been shown that it is an effective way to combat the outage caused by channel fading; that is, it provides the spatial diversity for communication. Except for amplify-and-forward (AF) and decode-and-forward (DF), compressed-and-forward (CF) is also an efficient forwarding strategy. In this thesis, we proposed a new CF scheme. In the existing CF protocol, the relay will switch to the DF mode when the source transmitted signal can be recovered by the relay completely; no further compression is made in this scheme. In our proposed, the relay will estimate if the codeword in a block is succeeded decoded, choose the corresponding forwarding methods with LDPC coding; those are based on joint source-channel coding or compressive sensing. At the decode side, a joint decoder with side information that performs sum-product algorithm (SPA) to decode the source message. Simulation results show that the proposed CF scheme can acquire the spatial diversity and outperform AF and DF schemes.

Compressed video bitstream transmissions over wireless networks are addressed in this work. We first consider error control and power allocation for transmitting wireless video over CDMA networks in conjunction with multiuser detection. We map a layered video bitstream to several CDMA fading channels and inject multiple source/parity layers into each of these channels at the transmitter. We formulate a combined optimization problem and give the optimal joint rate and power allocation for each of linear minimum mean-square error (MMSE) multiuser detector in the uplink and two types of blind linear MMSE detectors, i.e., the direct-matrix-inversion (DMI) blind detector and the subspace blind detector, in the downlink. We then present a multiple-channel video transmission scheme in wireless CDMA networks over multipath fading channels. For a given budget on the available bandwidth and total transmit power, the transmitter determines the optimal power allocations and the optimal transmission rates among multiple CDMA channels, as well as the optimal product channel code rate allocation. We also make use of results on the large-system CDMA performance for various multiuser receivers in multipath fading channels. We employ a fast joint source-channel coding algorithm to obtain the optimal product channel code structure. Finally, we propose an end-to-end architecture for multi-layer progressive video delivery over space-time differentially coded orthogonal frequency division multiplexing (STDC-OFDM) systems. We propose to use progressive joint source-channel coding to generate operational transmission distortion-power-rate (TD-PR) surfaces. By extending the rate-distortion function in source coding to the TD-PR surface in joint source-channel coding, our work can use the ??equal slope?? argument to effectively solve the transmission rate allocation problem as well as the transmission power allocation problem for multi-layer video transmission. It is demonstrated through simulations that as the wireless channel conditions change, these proposed schemes can scale the video streams and transport the scaled video streams to receivers with a smooth change of perceptual quality.

In this thesis, bit-by-bit power allocation in order to minimize mean-squared error (MSE) distortion of a basic communication system is studied. This communication system consists of a quantizer. There may or may not be a channel encoder and a Binary Phase Shift Keying (BPSK) modulator. In the quantizer, natural binary mapping is made. First, the case where there is no channel coding is considered. In the uncoded case, hard decision decoding is done at the receiver. It is seen that errors that occur in the more significant information bits contribute more to the distortion than less significant bits. For the uncoded case, the optimum power profile for each bit is determined analytically and through computer-based optimization methods like differential evolution. For low signal-to-noise ratio (SNR), the less significant bits are allocated negligible power compared to the more significant bits. For high SNRs, it is seen that the optimum bit-by-bit power allocation gives constant MSE gain in dB over the uniform power allocation. Second, the coded case is considered. Linear block codes like (3,2), (4,3) and (5,4) single parity check codes and (7,4) Hamming codes are used and soft-decision decoding is done at the receiver. Approximate expressions for the MSE are considered in order to find a near-optimum power profile for the coded case. The optimization is done through a computer-based optimization method (differential evolution). For a simple code like (7,4) Hamming code simulations show that up to 3 dB MSE gain can be obtained by changing the power allocation on the information and parity bits. A systematic method to find the power profile for linear block codes is also introduced given the knowledge of input-output weight enumerating function of the code. The information bits have the same power, and parity bits have the same power, and the two power levels can be different.

<p>With the increasing popularity and relevance of ad-hoc wireless sensor networks, cooperative transmission is more relevant than ever. In this thesis, we consider methods for optimization of cooperative transmission schemes in wireless sensor networks. We are in particular interested in communication schemes that can be used in applications that are critical to low-delays, such as networked control, and propose suitable candidates of joint source-channel coding schemes. We show that, in many cases, there are significant gains if the parts of the system are jointly optimized for the current source and channel. We especially focus on two means of cooperative transmission, namely distributed source coding and relaying.</p><p>In the distributed source coding case, we consider transmission of correlated continuous sources and propose an algorithm for designing simple and energy-efficient sensor nodes. In particular the cases of the binary symmetric channel as well as the additive white Gaussian noise channel are studied. The system works on a sample by sample basis yielding a very low encoding complexity, at an insignificant delay. Due to the source correlation, the resulting quantizers use the same indices for several separated intervals in order to reduce the quantization distortion.</p><p>For the case of relaying, we study the transmission of a continuous Gaussian source and the transmission of an uniformly distributed discrete source. In both situations, we propose design algorithms to design low-delay source-channel and relay mappings. We show that there can be significant power savings if the optimized systems are used instead of more traditional systems. By studying the structure of the optimized source-channel and relay mappings, we provide useful insights on how the optimized systems work. Interestingly, the design algorithm generally produces relay mappings with a structure that resembles Wyner-Ziv compression.</p>