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

Optimized Scalable Image and Video Transmission for MIMO Wireless Channels

In this chapter, we focus on proposing new strategies to efficiently transfer a compressed image/video content through wireless links using a multiple antenna technology. The proposed solutions can be considered as application layer physical layer (APP-PHY) cross layer design methods as they involve optimizing both application and physical layers. After a wide state-of-the-art study, we present two main solutions. The first focuses on using a new precoding algorithm that takes into account the image/video content structure when assigning transmission powers. We showed that its results are better than the existing conventional precoders. Second, a link adaptation process is integrated to efficiently assign coding parameters as a function of the channel state. Simulations over a realistic channel environment show that the link adaptation activates a dynamic process that results in a good image/video reconstruction quality even if the channel is varying. Finally, we incorporated soft decoding algorithms at the receiver side, and we showed that they could induce further improvements. In fact, almost 5 dB peak signal-to-noise ratio (PSNR) improvements are demonstrated in the case of transmission over a Rayleigh channel

QUALITY-DRIVEN CROSS LAYER DESIGN FOR MULTIMEDIA SECURITY OVER RESOURCE CONSTRAINED WIRELESS SENSOR NETWORKS

The strong need for security guarantee, e.g., integrity and authenticity, as well as privacy and confidentiality in wireless multimedia services has driven the development of an emerging research area in low cost Wireless Multimedia Sensor Networks (WMSNs). Unfortunately, those conventional encryption and authentication techniques cannot be applied directly to WMSNs due to inborn challenges such as extremely limited energy, computing and bandwidth resources. This dissertation provides a quality-driven security design and resource allocation framework for WMSNs. The contribution of this dissertation bridges the inter-disciplinary research gap between high layer multimedia signal processing and low layer computer networking. It formulates the generic problem of quality-driven multimedia resource allocation in WMSNs and proposes a cross layer solution. The fundamental methodologies of multimedia selective encryption and stream authentication, and their application to digital image or video compression standards are presented. New multimedia selective encryption and stream authentication schemes are proposed at application layer, which significantly reduces encryption/authentication complexity. In addition, network resource allocation methodologies at low layers are extensively studied. An unequal error protection-based network resource allocation scheme is proposed to achieve the best effort media quality with integrity and energy efficiency guarantee. Performance evaluation results show that this cross layer framework achieves considerable energy-quality-security gain by jointly designing multimedia selective encryption/multimedia stream authentication and communication resource allocation

CDDM: Channel Denoising Diffusion Models for Wireless Semantic Communications

Diffusion models (DM) can gradually learn to remove noise, which have been widely used in artificial intelligence generated content (AIGC) in recent years. The property of DM for eliminating noise leads us to wonder whether DM can be applied to wireless communications to help the receiver mitigate the channel noise. To address this, we propose channel denoising diffusion models (CDDM) for semantic communications over wireless channels in this paper. CDDM can be applied as a new physical layer module after the channel equalization to learn the distribution of the channel input signal, and then utilizes this learned knowledge to remove the channel noise. We derive corresponding training and sampling algorithms of CDDM according to the forward diffusion process specially designed to adapt the channel models and theoretically prove that the well-trained CDDM can effectively reduce the conditional entropy of the received signal under small sampling steps. Moreover, we apply CDDM to a semantic communications system based on joint source-channel coding (JSCC) for image transmission. Extensive experimental results demonstrate that CDDM can further reduce the mean square error (MSE) after minimum mean square error (MMSE) equalizer, and the joint CDDM and JSCC system achieves better performance than the JSCC system and the traditional JPEG2000 with low-density parity-check (LDPC) code approach.Comment: submitted to IEEE Transactions on Wireless Communications. arXiv admin note: substantial text overlap with arXiv:2305.0916

Semantic Communications for Image Recovery and Classification via Deep Joint Source and Channel Coding

With the recent advancements in edge artificial intelligence (AI), future sixth-generation (6G) networks need to support new AI tasks such as classification and clustering apart from data recovery. Motivated by the success of deep learning, the semantic-aware and task-oriented communications with deep joint source and channel coding (JSCC) have emerged as new paradigm shifts in 6G from the conventional data-oriented communications with separate source and channel coding (SSCC). However, most existing works focused on the deep JSCC designs for one task of data recovery or AI task execution independently, which cannot be transferred to other unintended tasks. Differently, this paper investigates the JSCC semantic communications to support multi-task services, by performing the image data recovery and classification task execution simultaneously. First, we propose a new end-to-end deep JSCC framework by unifying the coding rate reduction maximization and the mean square error (MSE) minimization in the loss function. Here, the coding rate reduction maximization facilitates the learning of discriminative features for enabling to perform classification tasks directly in the feature space, and the MSE minimization helps the learning of informative features for high-quality image data recovery. Next, to further improve the robustness against variational wireless channels, we propose a new gated deep JSCC design, in which a gated net is incorporated for adaptively pruning the output features to adjust their dimensions based on channel conditions. Finally, we present extensive numerical experiments to validate the performance of our proposed deep JSCC designs as compared to various benchmark schemes

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks

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

Adaptive resource optimization for edge inference with goal-oriented communications

AbstractGoal-oriented communications represent an emerging paradigm for efficient and reliable learning at the wireless edge, where only the information relevant for the specific learning task is transmitted to perform inference and/or training. The aim of this paper is to introduce a novel system design and algorithmic framework to enable goal-oriented communications. Specifically, inspired by the information bottleneck principle and targeting an image classification task, we dynamically change the size of the data to be transmitted by exploiting banks of convolutional encoders at the device in order to extract meaningful and parsimonious data features in a totally adaptive and goal-oriented fashion. Exploiting knowledge of the system conditions, such as the channel state and the computation load, such features are dynamically transmitted to an edge server that takes the final decision, based on a proper convolutional classifier. Hinging on Lyapunov stochastic optimization, we devise a novel algorithmic framework that dynamically and jointly optimizes communication, computation, and the convolutional encoder classifier, in order to strike a desired trade-off between energy, latency, and accuracy of the edge learning task. Several simulation results illustrate the effectiveness of the proposed strategy for edge learning with goal-oriented communications

Design of a secure architecture for the exchange of biomedical information in m-Health scenarios

El paradigma de m-Salud (salud móvil) aboga por la integración masiva de las más avanzadas tecnologías de comunicación, red móvil y sensores en aplicaciones y sistemas de salud, para fomentar el despliegue de un nuevo modelo de atención clínica centrada en el usuario/paciente. Este modelo tiene por objetivos el empoderamiento de los usuarios en la gestión de su propia salud (p.ej. aumentando sus conocimientos, promocionando estilos de vida saludable y previniendo enfermedades), la prestación de una mejor tele-asistencia sanitaria en el hogar para ancianos y pacientes crónicos y una notable disminución del gasto de los Sistemas de Salud gracias a la reducción del número y la duración de las hospitalizaciones. No obstante, estas ventajas, atribuidas a las aplicaciones de m-Salud, suelen venir acompañadas del requisito de un alto grado de disponibilidad de la información biomédica de sus usuarios para garantizar una alta calidad de servicio, p.ej. fusionar varias señales de un usuario para obtener un diagnóstico más preciso. La consecuencia negativa de cumplir esta demanda es el aumento directo de las superficies potencialmente vulnerables a ataques, lo que sitúa a la seguridad (y a la privacidad) del modelo de m-Salud como factor crítico para su éxito. Como requisito no funcional de las aplicaciones de m-Salud, la seguridad ha recibido menos atención que otros requisitos técnicos que eran más urgentes en etapas de desarrollo previas, tales como la robustez, la eficiencia, la interoperabilidad o la usabilidad. Otro factor importante que ha contribuido a retrasar la implementación de políticas de seguridad sólidas es que garantizar un determinado nivel de seguridad implica unos costes que pueden ser muy relevantes en varias dimensiones, en especial en la económica (p.ej. sobrecostes por la inclusión de hardware extra para la autenticación de usuarios), en el rendimiento (p.ej. reducción de la eficiencia y de la interoperabilidad debido a la integración de elementos de seguridad) y en la usabilidad (p.ej. configuración más complicada de dispositivos y aplicaciones de salud debido a las nuevas opciones de seguridad). Por tanto, las soluciones de seguridad que persigan satisfacer a todos los actores del contexto de m-Salud (usuarios, pacientes, personal médico, personal técnico, legisladores, fabricantes de dispositivos y equipos, etc.) deben ser robustas y al mismo tiempo minimizar sus costes asociados. Esta Tesis detalla una propuesta de seguridad, compuesta por cuatro grandes bloques interconectados, para dotar de seguridad a las arquitecturas de m-Salud con unos costes reducidos. El primer bloque define un esquema global que proporciona unos niveles de seguridad e interoperabilidad acordes con las características de las distintas aplicaciones de m-Salud. Este esquema está compuesto por tres capas diferenciadas, diseñadas a la medidas de los dominios de m-Salud y de sus restricciones, incluyendo medidas de seguridad adecuadas para la defensa contra las amenazas asociadas a sus aplicaciones de m-Salud. El segundo bloque establece la extensión de seguridad de aquellos protocolos estándar que permiten la adquisición, el intercambio y/o la administración de información biomédica -- por tanto, usados por muchas aplicaciones de m-Salud -- pero no reúnen los niveles de seguridad detallados en el esquema previo. Estas extensiones se concretan para los estándares biomédicos ISO/IEEE 11073 PHD y SCP-ECG. El tercer bloque propone nuevas formas de fortalecer la seguridad de los tests biomédicos, que constituyen el elemento esencial de muchas aplicaciones de m-Salud de carácter clínico, mediante codificaciones novedosas. Finalmente el cuarto bloque, que se sitúa en paralelo a los anteriores, selecciona herramientas genéricas de seguridad (elementos de autenticación y criptográficos) cuya integración en los otros bloques resulta idónea, y desarrolla nuevas herramientas de seguridad, basadas en señal -- embedding y keytagging --, para reforzar la protección de los test biomédicos.The paradigm of m-Health (mobile health) advocates for the massive integration of advanced mobile communications, network and sensor technologies in healthcare applications and systems to foster the deployment of a new, user/patient-centered healthcare model enabling the empowerment of users in the management of their health (e.g. by increasing their health literacy, promoting healthy lifestyles and the prevention of diseases), a better home-based healthcare delivery for elderly and chronic patients and important savings for healthcare systems due to the reduction of hospitalizations in number and duration. It is a fact that many m-Health applications demand high availability of biomedical information from their users (for further accurate analysis, e.g. by fusion of various signals) to guarantee high quality of service, which on the other hand entails increasing the potential surfaces for attacks. Therefore, it is not surprising that security (and privacy) is commonly included among the most important barriers for the success of m-Health. As a non-functional requirement for m-Health applications, security has received less attention than other technical issues that were more pressing at earlier development stages, such as reliability, eficiency, interoperability or usability. Another fact that has contributed to delaying the enforcement of robust security policies is that guaranteeing a certain security level implies costs that can be very relevant and that span along diferent dimensions. These include budgeting (e.g. the demand of extra hardware for user authentication), performance (e.g. lower eficiency and interoperability due to the addition of security elements) and usability (e.g. cumbersome configuration of devices and applications due to security options). Therefore, security solutions that aim to satisfy all the stakeholders in the m-Health context (users/patients, medical staff, technical staff, systems and devices manufacturers, regulators, etc.) shall be robust and, at the same time, minimize their associated costs. This Thesis details a proposal, composed of four interrelated blocks, to integrate appropriate levels of security in m-Health architectures in a cost-efcient manner. The first block designes a global scheme that provides different security and interoperability levels accordingto how critical are the m-Health applications to be implemented. This consists ofthree layers tailored to the m-Health domains and their constraints, whose security countermeasures defend against the threats of their associated m-Health applications. Next, the second block addresses the security extension of those standard protocols that enable the acquisition, exchange and/or management of biomedical information | thus, used by many m-Health applications | but do not meet the security levels described in the former scheme. These extensions are materialized for the biomedical standards ISO/IEEE 11073 PHD and SCP-ECG. Then, the third block proposes new ways of enhancing the security of biomedical standards, which are the centerpiece of many clinical m-Health applications, by means of novel codings. Finally the fourth block, with is parallel to the others, selects generic security methods (for user authentication and cryptographic protection) whose integration in the other blocks results optimal, and also develops novel signal-based methods (embedding and keytagging) for strengthening the security of biomedical tests. The layer-based extensions of the standards ISO/IEEE 11073 PHD and SCP-ECG can be considered as robust, cost-eficient and respectful with their original features and contents. The former adds no attributes to its data information model, four new frames to the service model |and extends four with new sub-frames|, and only one new sub-state to the communication model. Furthermore, a lightweight architecture consisting of a personal health device mounting a 9 MHz processor and an aggregator mounting a 1 GHz processor is enough to transmit a 3-lead electrocardiogram in real-time implementing the top security layer. The extra requirements associated to this extension are an initial configuration of the health device and the aggregator, tokens for identification/authentication of users if these devices are to be shared and the implementation of certain IHE profiles in the aggregator to enable the integration of measurements in healthcare systems. As regards to the extension of SCP-ECG, it only adds a new section with selected security elements and syntax in order to protect the rest of file contents and provide proper role-based access control. The overhead introduced in the protected SCP-ECG is typically 2{13 % of the regular file size, and the extra delays to protect a newly generated SCP-ECG file and to access it for interpretation are respectively a 2{10 % and a 5 % of the regular delays. As regards to the signal-based security techniques developed, the embedding method is the basis for the proposal of a generic coding for tests composed of biomedical signals, periodic measurements and contextual information. This has been adjusted and evaluated with electrocardiogram and electroencephalogram-based tests, proving the objective clinical quality of the coded tests, the capacity of the coding-access system to operate in real-time (overall delays of 2 s for electrocardiograms and 3.3 s for electroencephalograms) and its high usability. Despite of the embedding of security and metadata to enable m-Health services, the compression ratios obtained by this coding range from ' 3 in real-time transmission to ' 5 in offline operation. Complementarily, keytagging permits associating information to images (and other signals) by means of keys in a secure and non-distorting fashion, which has been availed to implement security measures such as image authentication, integrity control and location of tampered areas, private captioning with role-based access control, traceability and copyright protection. The tests conducted indicate a remarkable robustness-capacity tradeoff that permits implementing all this measures simultaneously, and the compatibility of keytagging with JPEG2000 compression, maintaining this tradeoff while setting the overall keytagging delay in only ' 120 ms for any image size | evidencing the scalability of this technique. As a general conclusion, it has been demonstrated and illustrated with examples that there are various, complementary and structured manners to contribute in the implementation of suitable security levels for m-Health architectures with a moderate cost in budget, performance, interoperability and usability. The m-Health landscape is evolving permanently along all their dimensions, and this Thesis aims to do so with its security. Furthermore, the lessons learned herein may offer further guidance for the elaboration of more comprehensive and updated security schemes, for the extension of other biomedical standards featuring low emphasis on security or privacy, and for the improvement of the state of the art regarding signal-based protection methods and applications