An Adaptive Source-Channel Coding with Feedback for Progressive Transmission of Medical Images

A novel adaptive source-channel coding with feedback for progressive transmission of medical images is proposed here. In the source coding part, the transmission starts from the region of interest (RoI). The parity length in the channel code varies with respect to both the proximity of the image subblock to the RoI and the channel noise, which is iteratively estimated in the receiver. The overall transmitted data can be controlled by the user (clinician). In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends. A MATLAB-based TCP/IP connection has been established to demonstrate the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel. The experimental results verify the effectiveness of the design

Joint Source-Channel Coding of JPEG 2000 Image Transmission Over Two-Way Multi-Relay Networks

In this paper, we develop a two-way multi-relay scheme for JPEG 2000 image transmission. We adopt a modified time-division broadcast (TDBC) cooperative protocol, and derive its power allocation and relay selection under a fairness constraint. The symbol error probability of the optimal system configuration is then derived. After that, a joint source-channel coding (JSCC) problem is formulated to find the optimal number of JPEG 2000 quality layers for the image and the number of channel coding packets for each JPEG 2000 codeblock that can minimize the reconstructed image distortion for the two users, subject to a rate constraint. Two fast algorithms based on dynamic programming (DP) and branch and bound (BB) are then developed. Simulation demonstrates that the proposed JSCC scheme achieves better performance and lower complexity than other similar transmission systems

Optimal Progressive Image Transmission Over Rayleigh Fading Channels

A fixed-packet optimal joint source channel coding scheme for transmission of progressive images over Rayleigh channels is proposed. A first order Markov model is used in rate allocation problem to concern channel temporal variations during image transmission. Also, introducing a modification on the used progressive coding scheme, the requirement for the immediate decoding termination upon the observation of an erroneous packet is relatively relaxed. A rate allocation mechanism for this modified version of progressive codes is also proposed

Product Code Optimization for Determinate State LDPC Decoding in Robust Image Transmission

We propose a novel scheme for error resilient image transmission. The proposed scheme employs a product coder consisting of LDPC codes and RS codes in order to deal effectively with bit errors. The efficiency of the proposed scheme is based on the exploitation of determinate symbols in Tanner graph decoding of LDPC codes and a novel product code optimization technique based on error estimation. Experimental evaluation demonstrates the superiority of the proposed system in comparison to recent state-of-the art techniques for image transmission

Semantic and effective communications

Shannon and Weaver categorized communications into three levels of problems: the technical problem, which tries to answer the question "how accurately can the symbols of communication be transmitted?"; the semantic problem, which asks the question "how precisely do the transmitted symbols convey the desired meaning?"; the effectiveness problem, which strives to answer the question "how effectively does the received meaning affect conduct in the desired way?". Traditionally, communication technologies mainly addressed the technical problem, ignoring the semantics or the effectiveness problems. Recently, there has been increasing interest to address the higher level semantic and effectiveness problems, with proposals ranging from semantic to goal oriented communications. In this thesis, we propose to formulate the semantic problem as a joint source-channel coding (JSCC) problem and the effectiveness problem as a multi-agent partially observable Markov decision process (MA-POMDP). As such, for the semantic problem, we propose DeepWiVe, the first-ever end-to-end JSCC video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. We also further show that it is possible to use predefined constellation designs as well as secure the physical layer communication against eavesdroppers for deep learning (DL) driven JSCC schemes, making such schemes much more viable for deployment in the real world. For the effectiveness problem, we propose a novel formulation by considering multiple agents communicating over a noisy channel in order to achieve better coordination and cooperation in a multi-agent reinforcement learning (MARL) framework. Specifically, we consider a MA-POMDP, in which the agents, in addition to interacting with the environment, can also communicate with each other over a noisy communication channel. The noisy communication channel is considered explicitly as part of the dynamics of the environment, and the message each agent sends is part of the action that the agent can take. As a result, the agents learn not only to collaborate with each other but also to communicate "effectively'' over a noisy channel. Moreover, we show that this framework generalizes both the semantic and technical problems. In both instances, we show that the resultant communication scheme is superior to one where the communication is considered separately from the underlying semantic or goal of the problem.Open Acces

Factor Graph Based Detection Schemes for Mobile Terrestrial DVB Systems with Long OFDM Blocks

This PhD dissertation analyzes the performance of second generation digital video broadcasting (DVB) systems in mobile terrestrial environments and proposes an iterative detection algorithm based on factor graphs (FG) to reduce the distortion caused by the time variation of the channel, providing error-free communication in very severe mobile conditions. The research work focuses on mobile scenarios where the intercarrier interference (ICI) is very high: high vehicular speeds when long orthogonal frequency-division multiplexing (OFDM) blocks are used. As a starting point, we provide the theoretical background on the main topics behind the transmission and reception of terrestrial digital television signals in mobile environments, along with a general overview of the main signal processing techniques included in last generation terrestrial DVB systems. The proposed FG-based detector design is then assessed over a simpli ed bit-interleaved coded modulation (BICM)-OFDM communication scheme for a wide variety of mobile environments. Extensive simulation results show the e ectiveness of the proposed belief propagation (BP) algorithm over the channels of interest in this research work. Moreover, assuming that low density parity-check (LDPC) codes are decoded by means of FG-based algorithms, a high-order FG is de ned in order to accomplish joint signal detection and decoding into the same FG framework, o ering a fully parallel structure very suitable when long OFDM blocks are employed. Finally, the proposed algorithms are analyzed over the physical layer of DVB-T2 speci cation. Two reception schemes are proposed which exploit the frequency and time-diversity inherent in time-varying channels with the aim of achieving a reasonable trade-o among performance, complexity and latency.Doktoretza tesi honek bigarren belaunaldiko telebista digitalaren eraginkortasuna aztertzen du eskenatoki mugikorrean, eta faktoreen grafoetan oinarritzen den hartzaile iteratibo bat proposatzen du denboran aldakorra den kanalak sortzen duen distortsioa leundu eta seinalea errorerik gabe hartzea ahalbidetzen duena. Proposatutako detektorea BICM-OFDM komunikazio eskema orokor baten gainean ebaluatu da lurreko broadcasting kanalaren baldintzak kontutan hartuz. Simulazio emaitzek algoritmo honen eraginkortasuna frogatzen dute Doppler frekuentzia handietan. Ikerketa lanaren bigarren zatian, faktoreen grafoetan oinarritutako detektorea eskema turbo zabalago baten baitan txertatu da LDPC dekodi katzaile batekin batera. Hartzaile diseinu honen abantaila nagusia da OFDM simbolo luzeetara ondo egokitzen dela. Azkenik, proposatutako algoritmoa DVB-T2 katearen baitan inplementatu da, bi hartzaile eskema proposatu direlarik seinaleak duen dibertsitate tenporal eta frekuentziala probesteko, beti ere eraginkortasunaren, konplexutasunaren eta latentziaren arteko konpromisoa mantenduz.Este trabajo de tesis analiza el rendimiento de la segunda generación de la televisión digital terreste en escenarios móviles y propone un algoritmo iterativo basado en grafos de factores para la detección de la señal y la reducción de la distorsión causada por la variación temporal del canal, permitiendo así recibir la señal libre de errores. El detector basado en grafos de factores propuesto es evaluado sobre un esquema de comunicaciones general BICM-OFDM en condiciones de transmisión propios de canales de difusión terrestres. Los resultados de simulación presentados muestran la e ciencia del algoritmo de detección propuesto en presencia de frecuencias Doppler muy altas. En una segunda parte del trabajo de investigación, el detector propuesto es incorporado a un esquema turbo junto con un decodi cador LDPC, dando lugar a un receptor iterativo que presenta características especialmente apropiadas para su implementación en sistemas OFDM con longitudes de símbolo elevadas. Por último, se analiza la implementación del algoritmo propuesto sobre la cadena de recepción de DVB-T2. Se presentan dos esquemas de recepción que explotan la diversidad temporal y frecuencial presentes en la señal afectada por canales variantes en el tiempo, consiguiendo un compromiso razonable entre rendimiento, complejidad y latencia

Progressive transmission of medical images

A novel adaptive source-channel coding scheme for progressive transmission of medical images with a feedback system is therefore proposed in this dissertation. The overall design includes Discrete Wavelet Transform (DWT), Embedded Zerotree Wavelet (EZW) coding, Joint Source-Channel Coding (JSCC), prioritization of region of interest (RoI), variability of parity length based on feedback, and the corresponding hardware design utilising Simulink. The JSCC can achieve an efficient transmission by incorporating unequal error projection (UEP) and rate allocation. An algorithm is also developed to estimate the number of erroneous data in the receiver. The algorithm detects the address in which the number of symbols for each subblock is indicated, and reassigns an estimated correct data according to a decision making criterion, if error data is detected. The proposed system has been designed based on Simulink which can be used to generate netlist for portable devices. A new compression method called Compressive Sensing (CS) is also revisited in this work. CS exhibits many advantages in comparison with EZW based on our experimental results. DICOM JPEG2000 is an efficient coding standard for lossy or lossless multi-component image coding. However, it does not provide any mechanism for automatic RoI definition, and is more complex compared to our proposed scheme. The proposed system significantly reduces the transmission time, lowers computation cost, and maintains an error-free state in the RoI with regards to the above provided features. A MATLAB-based TCP/IP connection is established to demonstrate the efficacy of the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary and symmetric channel (BSC) and Rayleigh channel. The experimental results confirm the effectiveness of the design.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Signal optimization for Galileo evolution

Global Navigation Satellite System (GNSS) are present in our daily lives. Moreover, new users areemerging with further operation needs involving a constant evolution of the current navigationsystems. In the current framework of Galileo (GNSS European system) and especially within theGalileo E1 Open Service (OS), adding a new acquisition aiding signal could contribute to providehigher resilience at the acquisition phase, as well as to reduce the time to first fix (TTFF).Designing a new GNSS signal is always a trade-off between several performance figures of merit.The most relevant are the position accuracy, the sensitivity and the TTFF. However, if oneconsiders that the signal acquisition phase is the goal to design, the sensitivity and the TTFF havea higher relevance. Considering that, in this thesis it is presented the joint design of a GNSS signaland the message structure to propose a new Galileo 2nd generation signal, which provides ahigher sensitivity in the receiver and reduce the TTFF. Several aspects have been addressed inorder to design a new signal component. Firstly, the spreading modulation definition must considerthe radio frequency compatibility in order to cause acceptable level of interference inside the band.Moreover, the spreading modulation should provide good correlation properties and goodresistance against the multipath in order to enhance the receiver sensitivity and to reduce theTTFF. Secondly, the choice of the new PRN code is also crucial in order to ease the acquisitionphase. A simple model criterion based on a weighted cost function is used to evaluate the PRNcodes performance. This weighted cost function takes into account different figures of merit suchas the autocorrelation, the cross-correlation and the power spectral density. Thirdly, the design ofthe channel coding scheme is always connected with the structure of the message. A joint designbetween the message structure and the channel coding scheme can provide both, reducing theTTFF and an enhancement of the resilience of the decoded data. In this this, a new method to codesign the message structure and the channel coding scheme for the new G2G signal isproposed. This method provides the guideline to design a message structure whose the channelcoding scheme is characterized by the full diversity, the Maximum Distance Separable (MDS) andthe rate compatible properties. The channel coding is essential in order to enhance the datademodulation performance, especially in harsh environments. However, this process can be verysensitive to the correct computation of the decoder input. Significant improvements were obtainedby considering soft inputs channel decoders, through the Log Likelihood Ratio LLRs computation.However, the complete knowledge of the channel state information (CSI) was usually considered,which it is infrequently in real scenarios. In this thesis, we provide new methods to compute LLRlinear approximations, under the jamming and the block fading channels, considering somestatistical CSI. Finally, to transmit a new signal in the same carrier frequency and using the sameHigh Power Amplifier (HPA) generates constraints in the multiplexing design, since a constant orquasi constant envelope is needed in order to decrease the non-linear distortions. Moreover, themultiplexing design should provide high power efficiency to not waste the transmitted satellitepower. Considering the precedent, in this thesis, we evaluate different multiplexing methods,which search to integrate a new binary signal in the Galileo E1 band while enhancing thetransmitted power efficiency. Besides that, even if the work is focused on the Galileo E1, many ofthe concepts and methodologies can be easily extended to any GNSS signa

Layered Wyner-Ziv video coding for noisy channels

The growing popularity of video sensor networks and video celluar phones has generated the need for low-complexity and power-efficient multimedia systems that can handle multiple video input and output streams. While standard video coding techniques fail to satisfy these requirements, distributed source coding is a promising technique for ??uplink?? applications. Wyner-Ziv coding refers to lossy source coding with side information at the decoder. Based on recent theoretical result on successive Wyner-Ziv coding, we propose in this thesis a practical layered Wyner-Ziv video codec using the DCT, nested scalar quantizer, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information) for noiseless channel. The DCT is applied as an approximation to the conditional KLT, which makes the components of the transformed block conditionally independent given the side information. NSQ is a binning scheme that facilitates layered bit-plane coding of the bin indices while reducing the bit rate. LDPC code based Slepian-Wolf coding exploits the correlation between the quantized version of the source and the side information to achieve further compression. Different from previous works, an attractive feature of our proposed system is that video encoding is done only once but decoding allowed at many lower bit rates without quality loss. For Wyner-Ziv coding over discrete noisy channels, we present a Wyner-Ziv video codec using IRA codes for Slepian-Wolf coding based on the idea of two equivalent channels. For video streaming applications where the channel is packet based, we apply unequal error protection scheme to the embedded Wyner-Ziv coded video stream to find the optimal source-channel coding trade-off for a target transmission rate over packet erasure channel