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

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

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.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

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

Quantization Watermarking for Joint Compression and Data Hiding Schemes

International audienceEnrichment and protection of JPEG2000 images is an important issue. Data hiding techniques are a good solution to solve these problems. In this context, we can consider the joint approach to introduce data hiding technique into JPEG2000 coding pipeline. Data hiding consists of imperceptibly altering multimedia content, to convey some information. This process is done in such a way that the hidden data is not perceptible to an observer. Digital watermarking is one type of data hiding. In addition to the imperceptibility and payload constraints, the watermark should be robust against a variety of manipulations or attacks. We focus on trellis coded quantization (TCQ) data hiding techniques and propose two JPEG2000 compression and data hiding schemes. The properties of TCQ quantization, defined in JPEG2000 part 2, are used to perform quantization and information embedding during the same time. The first scheme is designed for content description and management applications with the objective of achieving high payloads. The compression rate/imperceptibility/payload trade off is our main concern. The second joint scheme has been developed for robust watermarking and can have consequently many applications. We achieve the better imperceptibility/robustness trade off in the context of JPEG2000 compression. We provide some experimental results on the implementation of these two schemes

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

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

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

Near-capacity dirty-paper code design : a source-channel coding approach

This paper examines near-capacity dirty-paper code designs based on source-channel coding. We first point out that the performance loss in signal-to-noise ratio (SNR) in our code designs can be broken into the sum of the packing loss from channel coding and a modulo loss, which is a function of the granular loss from source coding and the target dirty-paper coding rate (or SNR). We then examine practical designs by combining trellis-coded quantization (TCQ) with both systematic and nonsystematic irregular repeat-accumulate (IRA) codes. Like previous approaches, we exploit the extrinsic information transfer (EXIT) chart technique for capacity-approaching IRA code design; but unlike previous approaches, we emphasize the role of strong source coding to achieve as much granular gain as possible using TCQ. Instead of systematic doping, we employ two relatively shifted TCQ codebooks, where the shift is optimized (via tuning the EXIT charts) to facilitate the IRA code design. Our designs synergistically combine TCQ with IRA codes so that they work together as well as they do individually. By bringing together TCQ (the best quantizer from the source coding community) and EXIT chart-based IRA code designs (the best from the channel coding community), we are able to approach the theoretical limit of dirty-paper coding. For example, at 0.25 bit per symbol (b/s), our best code design (with 2048-state TCQ) performs only 0.630 dB away from the Shannon capacity