A unary error correction code for the near-capacity joint source and channel coding of symbol values from an infinite set

A novel Joint Source and Channel Code (JSCC) is proposed, which we refer to as the Unary Error Correction (UEC) code. Unlike existing JSCCs, our UEC facilitates the practical encoding of symbol values that are selected from a set having an infinite cardinality. Conventionally, these symbols are conveyed using Separate Source and Channel Codes (SSCCs), but we demonstrate that the residual redundancy that is retained following source coding results in a capacity loss, which is found to have a value of 1.11 dB in a particular practical scenario. By contrast, the proposed UEC code can eliminate this capacity loss, or reduce it to an infinitesimally small value. Furthermore, the UEC code has only a moderate complexity, facilitating its employment in practical low-complexity applications

Irregular Variable Length Coding

In this thesis, we introduce Irregular Variable Length Coding (IrVLC) and investigate its applications, characteristics and performance in the context of digital multimedia broadcast telecommunications. During IrVLC encoding, the multimedia signal is represented using a sequence of concatenated binary codewords. These are selected from a codebook, comprising a number of codewords, which, in turn, comprise various numbers of bits. However, during IrVLC encoding, the multimedia signal is decomposed into particular fractions, each of which is represented using a different codebook. This is in contrast to regular Variable Length Coding (VLC), in which the entire multimedia signal is encoded using the same codebook. The application of IrVLCs to joint source and channel coding is investigated in the context of a video transmission scheme. Our novel video codec represents the video signal using tessellations of Variable-Dimension Vector Quantisation (VDVQ) tiles. These are selected from a codebook, comprising a number of tiles having various dimensions. The selected tessellation of VDVQ tiles is signalled using a corresponding sequence of concatenated codewords from a Variable Length Error Correction (VLEC) codebook. This VLEC codebook represents a specific joint source and channel coding case of VLCs, which facilitates both compression and error correction. However, during video encoding, only particular combinations of the VDVQ tiles will perfectly tessellate, owing to their various dimensions. As a result, only particular sub-sets of the VDVQ codebook and, hence, of the VLEC codebook may be employed to convey particular fractions of the video signal. Therefore, our novel video codec can be said to employ IrVLCs. The employment of IrVLCs to facilitate Unequal Error Protection (UEP) is also demonstrated. This may be applied when various fractions of the source signal have different error sensitivities, as is typical in audio, speech, image and video signals, for example. Here, different VLEC codebooks having appropriately selected error correction capabilities may be employed to encode the particular fractions of the source signal. This approach may be expected to yield a higher reconstruction quality than equal protection in cases where the various fractions of the source signal have different error sensitivities. Finally, this thesis investigates the application of IrVLCs to near-capacity operation using EXtrinsic Information Transfer (EXIT) chart analysis. Here, a number of component VLEC codebooks having different inverted EXIT functions are employed to encode particular fractions of the source symbol frame. We show that the composite inverted IrVLC EXIT function may be obtained as a weighted average of the inverted component VLC EXIT functions. Additionally, EXIT chart matching is employed to shape the inverted IrVLC EXIT function to match the EXIT function of a serially concatenated inner channel code, creating a narrow but still open EXIT chart tunnel. In this way, iterative decoding convergence to an infinitesimally low probability of error is facilitated at near-capacity channel SNRs

Nested turbo codes for the costa problem

Driven by applications in data-hiding, MIMO broadcast channel coding, precoding for interference cancellation, and transmitter cooperation in wireless networks, Costa coding has lately become a very active research area. In this paper, we first offer code design guidelines in terms of source- channel coding for algebraic binning. We then address practical code design based on nested lattice codes and propose nested turbo codes using turbo-like trellis-coded quantization (TCQ) for source coding and turbo trellis-coded modulation (TTCM) for channel coding. Compared to TCQ, turbo-like TCQ offers structural similarity between the source and channel coding components, leading to more efficient nesting with TTCM and better source coding performance. Due to the difference in effective dimensionality between turbo-like TCQ and TTCM, there is a performance tradeoff between these two components when they are nested together, meaning that the performance of turbo-like TCQ worsens as the TTCM code becomes stronger and vice versa. Optimization of this performance tradeoff leads to our code design that outperforms existing TCQ/TCM and TCQ/TTCM constructions and exhibits a gap of 0.94, 1.42 and 2.65 dB to the Costa capacity at 2.0, 1.0, and 0.5 bits/sample, respectively

Optimal soft-decoding combined trellis-coded quantization/modulation.

Chei Kwok-hung.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 66-73).Abstracts in English and Chinese.Chapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Typical Digital Communication Systems --- p.2Chapter 1.1.1 --- Source coding --- p.3Chapter 1.1.2 --- Channel coding --- p.5Chapter 1.2 --- Joint Source-Channel Coding System --- p.5Chapter 1.3 --- Thesis Organization --- p.7Chapter Chapter 2 --- Trellis Coding --- p.9Chapter 2.1 --- Convolutional Codes --- p.9Chapter 2.2 --- Trellis-Coded Modulation --- p.12Chapter 2.2.1 --- Set Partitioning --- p.13Chapter 2.3 --- Trellis-Coded Quantization --- p.14Chapter 2.4 --- Joint TCQ/TCM System --- p.17Chapter 2.4.1 --- The Combined Receiver --- p.17Chapter 2.4.2 --- Viterbi Decoding --- p.19Chapter 2.4.3 --- Sequence MAP Decoding --- p.20Chapter 2.4.4 --- Sliding Window Decoding --- p.21Chapter 2.4.5 --- Block-Based Decoding --- p.23Chapter Chapter 3 --- Soft Decoding Joint TCQ/TCM over AWGN Channel --- p.25Chapter 3.1 --- System Model --- p.26Chapter 3.2 --- TCQ with Optimal Soft-Decoder --- p.27Chapter 3.3 --- Gaussian Memoryless Source --- p.30Chapter 3.3.1 --- Theorem Limit --- p.31Chapter 3.3.2 --- Performance on PAM Constellations --- p.32Chapter 3.3.3 --- Performance on PSK Constellations --- p.36Chapter 3.4 --- Uniform Memoryless Source --- p.38Chapter 3.4.1 --- Theorem Limit --- p.38Chapter 3.4.2 --- Performance on PAM Constellations --- p.39Chapter 3.4.3 --- Performance on PSK Constellations --- p.40Chapter Chapter 4 --- Soft Decoding Joint TCQ/TCM System over Rayleigh Fading Channel --- p.42Chapter 4.1 --- Wireless Channel --- p.43Chapter 4.2 --- Rayleigh Fading Channel --- p.44Chapter 4.3 --- Idea Interleaving --- p.45Chapter 4.4 --- Receiver Structure --- p.46Chapter 4.5 --- Numerical Results --- p.47Chapter 4.5.1 --- Performance on 4-PAM Constellations --- p.48Chapter 4.5.2 --- Performance on 8-PAM Constellations --- p.50Chapter 4.5.3 --- Performance on 16-PAM Constellations --- p.52Chapter Chapter 5 --- Joint TCVQ/TCM System --- p.54Chapter 5.1 --- Trellis-Coded Vector Quantization --- p.55Chapter 5.1.1 --- Set Partitioning in TCVQ --- p.56Chapter 5.2 --- Joint TCVQ/TCM --- p.59Chapter 5.2.1 --- Set Partitioning and Index Assignments --- p.60Chapter 5.2.2 --- Gaussian-Markov Sources --- p.61Chapter 5.3 --- Simulation Results and Discussion --- p.62Chapter Chapter 6 --- Conclusion and Future Work --- p.64Chapter 6.1 --- Conclusion --- p.64Chapter 6.2 --- Future Works --- p.65Bibliography --- p.66Appendix-Publications --- p.7

Soft information based protocols in network coded relay networks

Future wireless networks aim at providing higher quality of service (QoS) to mobile users. The emergence of relay technologies has shed light on new methodologies through which the system capacity can be dramatically increased with low deployment cost. In this thesis, novel relay technologies have been proposed in two practical scenarios: wireless sensor networks (WSN) and cellular networks. In practical WSN designs, energy conservation is the single most important requirement. This thesis draws attention to a multiple access relay channels model in the WSN. The network coded symbol for the received signals from correlated sources has been derived; the network coded symbol vector is then converted into a sparse vector, after which a compressive sensing (CS) technique is applied over the sparse signals. A theoretical proof analysis is derived regarding the reliability of the network coded symbol formed in the proposed protocol. The proposed protocol results in a better bit error rate (BER) performance in comparison to the direct implementation of CS on the EF protocol. Simulation results validate our analyses. Another hot topic is the application of relay technologies to the cellular networks. In this thesis, a practical two-way transmission scheme is proposed based on the EF protocol and the network coding technique. A trellis coded quantization/modulation (TCQ/M) scheme is used in the network coding process. The soft network coded symbols are quantized into only one bit thus requiring the same transmission bandwidth as the simplest decode-and-forward protocol. The probability density function of the network coded symbol is derived to help to form the quantization codebook for the TCQ. Simulations show that the proposed soft forwarding protocol can achieve full diversity with only a transmission rate of 1, and its BER performance is equivalent to that of an unquantized EF protocol

Performance of Gray Scaled Images Using Segmented Cellular Neural Network - Cellular Neural Network Combined Trellis Coded Quantization / Modulation (SCNN - CNN CTCQ/TCM) Approach Over Rician Fading Channel

Bu çalışmada Bölütlenmiş Hücresel Yapay Sinir Ağları-Hücresel Yapay Sinir Ağları Birleşik Kafes Kodlamalı Kuantalama ve Modülasyon işleminin gerçekleştirildiği yeni bir yapı tanıtılmıştır. Burada gri tonlamalı bir görüntü bizim tarafımızdan önerilen Bölütlemeli Hücresel Yapay Sinir Ağı yaklaşımı kullanılarak 3 bit seviyesine düşürülmüş ve daha sonra CNN tabanlı bir modelden oluşmuş kafes kodlamalı kuantalama ve modülasyon yapısından geçirilmiştir. Son olarak bu önerilen yapının performans analiz işlemleri yapılarak simulasyon ve analitik hata başarım eğrileri elde edilmiştir.In this paper, Segmented Cellular Neural Network-Cellular Neural Network Combined Trellis Coded Quantization / Modulation (SCNN-CNN CTCQ/TCM) scheme is introduced. Here, a gray scaled image is lowered to 3 bit using our proposed Segmented Cellular Neural Network approach (SCNN) and then passed through a new CNN based structure which models combined trellis coded quantization / modulation. The performance of our combined scheme has been analyzed over Rician fading channel. Computer simulations studies confirm the analytical upper bound curves

Performance of Gray Scaled Images Using Segmented Cellular Neural Network - Cellular Neural Network Combined Trellis Coded Quantization / Modulation (SCNN - CNN CTCQ/TCM) Approach Over Rician Fading Channel

Bu çalışmada Bölütlenmiş Hücresel Yapay Sinir Ağları-Hücresel Yapay Sinir Ağları Birleşik Kafes Kodlamalı Kuantalama ve Modülasyon işleminin gerçekleştirildiği yeni bir yapı tanıtılmıştır. Burada gri tonlamalı bir görüntü bizim tarafımızdan önerilen Bölütlemeli Hücresel Yapay Sinir Ağı yaklaşımı kullanılarak 3 bit seviyesine düşürülmüş ve daha sonra CNN tabanlı bir modelden oluşmuş kafes kodlamalı kuantalama ve modülasyon yapısından geçirilmiştir. Son olarak bu önerilen yapının performans analiz işlemleri yapılarak simulasyon ve analitik hata başarım eğrileri elde edilmiştir.In this paper, Segmented Cellular Neural Network-Cellular Neural Network Combined Trellis Coded Quantization / Modulation (SCNN-CNN CTCQ/TCM) scheme is introduced. Here, a gray scaled image is lowered to 3 bit using our proposed Segmented Cellular Neural Network approach (SCNN) and then passed through a new CNN based structure which models combined trellis coded quantization / modulation. The performance of our combined scheme has been analyzed over Rician fading channel. Computer simulations studies confirm the analytical upper bound curves

Soft information based protocols in network coded relay networks

Future wireless networks aim at providing higher quality of service (QoS) to mobile users. The emergence of relay technologies has shed light on new methodologies through which the system capacity can be dramatically increased with low deployment cost. In this thesis, novel relay technologies have been proposed in two practical scenarios: wireless sensor networks (WSN) and cellular networks. In practical WSN designs, energy conservation is the single most important requirement. This thesis draws attention to a multiple access relay channels model in the WSN. The network coded symbol for the received signals from correlated sources has been derived; the network coded symbol vector is then converted into a sparse vector, after which a compressive sensing (CS) technique is applied over the sparse signals. A theoretical proof analysis is derived regarding the reliability of the network coded symbol formed in the proposed protocol. The proposed protocol results in a better bit error rate (BER) performance in comparison to the direct implementation of CS on the EF protocol. Simulation results validate our analyses. Another hot topic is the application of relay technologies to the cellular networks. In this thesis, a practical two-way transmission scheme is proposed based on the EF protocol and the network coding technique. A trellis coded quantization/modulation (TCQ/M) scheme is used in the network coding process. The soft network coded symbols are quantized into only one bit thus requiring the same transmission bandwidth as the simplest decode-and-forward protocol. The probability density function of the network coded symbol is derived to help to form the quantization codebook for the TCQ. Simulations show that the proposed soft forwarding protocol can achieve full diversity with only a transmission rate of 1, and its BER performance is equivalent to that of an unquantized EF protocol