Multimedia Communication Systems Research Articles

Retracted: Vehicle Routing Optimization Based on Multimedia Communication and Intelligent Transportation System

Retracted: Vehicle Routing Optimization Based on Multimedia Communication and Intelligent Transportation System

Emergence of energy optimization in MIMO-OFDM communication system with hybrid teamwork-grasshopper optimization

Abstract In the application of mobile multimedia and wireless communication system needs an enormous amount of data. Due to the usage of a huge data rate, a superior amount of energy is offered to BER, which effectively enhances the entire energy consumption rate in the system, and also, the generation of CO2 emission leads to global warming. Hence, professionals searched for energy-efficient approaches for attaining enhanced data rates in wireless communication systems. Then, professionals observed the energy efficacy as well as QoS as an essential factor in developing and validating the mobile multimedia communication system that has created superior interest in recent days. In this paper, energy-efficient models are suggested for MIMO-OFDM mobile multimedia communication systems with statistical QoS constraints. Hence, this research suggests a new MTGSO for energy optimization in the MIMO-OFDM mobile multimedia communication system to improve spectral efficiency and system capacity. Thus, the empirical result of the designed method attains better performance regarding average power constraints, achieving 29.8 %, 21.3 %, 123.8 %, and 4.2 % enhanced than SSO, FOA, GSO, and TOA. This energy-efficient hybrid algorithm for MIMO-OFDM proves its efficiency in terms of various performance measures and statistical measures.

PoCH: automatic HDL code generator tool for Polar channel coding decoders in multimedia communication systems

PoCH: automatic HDL code generator tool for Polar channel coding decoders in multimedia communication systems

RE-MAC: A Hybrid MAC Protocol for Underwater Multimedia Communication System

In this article, we propose a reliable and efficient medium access control (MAC) protocol, RE-MAC, for resource-constraint underwater acoustic multimedia communication systems. RE-MAC achieves scalability by utilizing a hybrid MAC protocol smartly, which takes advantage of contention, reservation, and null data packet (NDP) based channel access mechanisms. The proposed scheme achieves multihop communication and synchronization for video streaming using a transmission opportunity (TXOP) based efficient channel access mechanism at the access point (AP) and relay nodes. TXOP time has been utilized by relay and AP for sending stream of frames with low overhead. To improve the efficiency in multihop communication, RE-MAC finds an optimal frame duration for relays and AP. RE-MAC efficiently places the NDP mechanism replacing traditional ACK-based control packet exchange. We incorporate the TXOP in AP and relay nodes for multimedia streaming and sleep mode for stations. Further, the video compression technique gives the efficiency of our system to improve the transmission of multimedia data. Our proposed schemes help communicate multimedia data without compromising the quality of service. We have demonstrated our proposed scheme experimentally in a prototype. After that, a simulation-based detailed performance analysis is provided to see the scalability of the proposed scheme. Compared to the existing state-of-the-art solutions, RE-MAC significantly delivers the throughput, energy consumption, delay, and packet loss.

Deep Learning-Based Acoustic Echo Cancellation for Surround Sound Systems

Surround sound systems that play back multi-channel audio signals through multiple loudspeakers can improve augmented reality, which has been widely used in many multimedia communication systems. It is common that a hand-free speech communication system suffers from the acoustic echo problem, and the echo needs to be canceled or suppressed completely. This paper proposes a deep learning-based acoustic echo cancellation (AEC) method to recover the desired near-end speech from the microphone signals in surround sound systems. The ambisonics technique was adopted to record the surround sound for reproduction. To achieve a better generalization capability against different loudspeaker layouts, the compressed complex spectra of the first-order ambisonic signals (B-format) were sent to the neural network as the input features directly instead of using the ambisonic decoded signals (D-format). Experimental results on both simulated and real acoustic environments showed the effectiveness of the proposed algorithm in surround AEC, and outperformed other competing methods in terms of the speech quality and the amount of echo reduction.

G.M. MCLUHAN: COMMUNICATION AS A MEANS SOCIALIZATION

Background. The problems of specifics and transformations of social communication are updated in the modern conditions of the contradictory development of the multimedia communication system, which actively affects the processes of socialization. In modern reality, Internet tools often play a more significant role in socialization processes than traditional social agents. The Internet expands the possibilities for revealing the personality, but at the same time gives rise to the risks of socialization of young people. The authors of the article turn to a critical understanding of the concept of GM. McLuhan (1911-1980), Canadian communication technology theorist. The main works of G.M. McLuhan came out in the 60s. XX century, however, the ideas expressed in them are still in demand in world science.
 Purpose. The authors critically analyze the theory of communications by M. McLuhan, which gives grounds for conclusions about its modern research capabilities and, at the same time, about the gaps left by it, in understanding the processes of socialization of a person in continuous and diverse flows of communication.
 Methods. In the study, the authors rely on a philosophical and cultural approach, including techniques and methods of sociological analysis of communication, as well as an interdisciplinary approach.
 Results. As G.M. McLuhan rightly believed, communication processes are the necessary basis for the formation, maintenance and transformation of cultural phenomena and the person himself. The communication theory of G.M. McLuhan demonstrates the influence of technology on changing a person’s thinking, his consciousness, ability to perceive, mentality, lifestyle. Technical means of communication creating new languages of communication fulfill a revolutionary role in sociocultural dynamics in general and in the processes of socialization in particular, creating a universal environment for the formation of personality. At the same time, based on the analysis of the works of G.M. McLuhan, the limitations of a media-oriented approach are shown. The authors of the article demonstrate the advantage of philosophical, cultural and interdisciplinary approaches in domestic communicativism, based not on a technocratic, but on a humanistic dominant.
 Scope of results. The results obtained can be applied in the study of socio-cultural transformations and communication in the context of global challenges of our time, in the formation of research approaches to understanding the specifics and functions of modern socialization and communication processes.

Vehicle Routing Optimization Based on Multimedia Communica-tion and Intelligent Transportation System

With the maturity and popularity of network technology and multimedia technology, more and more communication tools and means have entered people’s lives. The usual communication tools are often limited to the ability to transmit sound signals. This method does not well express the information between the two parties in some special occasions, such as a noisy environment, where both parties have language or hearing impairments. The multimedia communication system is a technology that combines network communication and multimedia. It utilizes the efficiency of data transmission over the network and the diversity of information in multimedia, making communication between people faster, clearer, and more intuitive. The multimedia communication system is an important part of the application to the intelligent transportation system. Intelligent transportation system is a systematic, real-time, accurate, interactive, and extensive traffic management system established by the comprehensive use of modern high and new technology in the transportation system. With these characteristics, intelligent transportation system has increasingly become an important means to solve modern traffic problems. Based on multimedia communication and intelligent transportation system, this article optimizes the vehicle path and realizes the application of intelligent transportation.

Introduction to the Special Issue on 6G Enabled Interactive Multimedia Communication Systems

No abstract available.

An energy efficiency perceptive on MIMO‐OFDM systems using hybrid fruit fly‐based salp swarm optimization technique

AbstractThis paper is to plan for the development of energy‐efficient MIMO‐OFDM mobile multimedia communication systems using the intelligent meta‐heuristic approach. This model is concentrated on solving the multi‐channel optimization problem. Recent research work is focused on single‐channel optimization problems, and hence the conversion of multi‐channel optimization problems into single‐channel optimization problems is considered the challenging point in this research. In the proposed MIMO‐OFDM method for mobile multimedia communication systems, the channel‐matrix Singular Value Decomposition (SVD) method is used for implementing the sub‐channel grouping scheme, which has simplified the multichannel problem to a multi‐target single‐channel optimization problem. In this optimization problem, the transmission power‐allocation threshold is optimized for attaining the objective function of maximization of energy efficiency. A hybridized optimization algorithm named Hybrid Fruit Fly‐based Salp Swarm Optimization (HFF‐SSO) is utilized for energy optimization in the MIMO‐OFDM mobile multimedia communication system. This hybrid algorithm has reached an energy‐efficient system with a high convergence rate, which is proved by the comparison over the conventional systems.

Video compression based on zig-zag 3D DCT and run-length encoding for multimedia communication systems

Purpose With the advent of technology, a huge amount of data is being transmitted and received through the internet. Large bandwidth and storage are required for the exchange of data and storage, respectively. Hence, compression of the data which is to be transmitted over the channel is unavoidable. The main purpose of the proposed system is to use the bandwidth effectively. The videos are compressed at the transmitter’s end and reconstructed at the receiver’s end. Compression techniques even help for smaller storage requirements. Design/methodology/approach The paper proposes a novel compression technique for three-dimensional (3D) videos using a zig-zag 3D discrete cosine transform. The method operates a 3D discrete cosine transform on the videos, followed by a zig-zag scanning process. Finally, to convert the data into a single bit stream for transmission, a run-length encoding technique is used. The videos are reconstructed by using the inverse 3D discrete cosine transform, inverse zig-zag scanning (quantization) and inverse run length coding techniques. The proposed method is simple and reduces the complexity of the convolutional techniques. Findings Coding reduction, code word reduction, peak signal to noise ratio (PSNR), mean square error, compression percent and compression ratio values are calculated, and the dominance of the proposed method over the convolutional methods is seen. Originality/value With zig-zag quantization and run length encoding using 3D discrete cosine transform for 3D video compression, gives compression up to 90% with a PSNR of 41.98 dB. The proposed method can be used in multimedia applications where bandwidth, storage and data expenses are the major issues.

FPGA implementation of high performance digital FIR filter design using a hybrid adder and multiplier

ABSTRACT The energetic growth in portable multimedia and mobile communication system has increased the requirement of high-speed signal processing system with compact area and power consumption. Finite impulse response(FIR) filters are broadly used in image, signal, speech and video signal processing, medical electronics, noise filtering, mobile communication and many other fields. The performance of the whole signal processing system with FIR filter depends on the basic building block of multiplier and adders. Hence, the hybrid FIR filter is proposed to improve the speed of the signal processing system using hybrid adder and hybrid multiplier. In this technique, the basic hybrid adder is designed with the help of 2-bit adders, BEC and 4:1 Multiplexer. Also, the hybrid multiplier is designed based on partial products of two consecutive multiplicand bits which are added at same time using Han-Carlson, Weinberger and Ling adder. The proposed FIR filter is functionally verified and synthesised using Xilinx ISE simulator and is implemented in Spartan 6 FPGA boards. The result shows that the delay of FIR filter using the proposed multiplier is improved by 26.51%, 15.59%, 15.83% and 2.79% as compared with CLA, conventional CSA, CSA-BK-BEC and the proposed adder with array multiplier, respectively.

Communication Protocols and Technologies for Multimedia Transmission: A Comprehensive Study

The exponential growth in end-user demand for multimedia content has necessitated significant advancements in communication technologies and multimedia processing. This paper presents a comprehensive review of various multimedia communication systems, focusing on the techniques employed for processing multimedia content and ensuring seamless transmission. It examines various technologies and communication protocols used to transport multimedia material while also addressing the difficulties these technologies present. The goal is to satisfy the growing demands for multimedia communication that include high data rates, wide bandwidth, low latency, and increased Quality of Service (QoS).

Vehicle Routing Optimization Based on Multimedia Communication and Intelligent Transportation System

With the maturity and popularity of network technology and multimedia technology, more and more communication tools and means have entered people’s lives. The usual communication tools are often limited to the ability to transmit sound signals. This method does not well express the information between the two parties in some special occasions, such as a noisy environment, where both parties have language or hearing impairments. The multimedia communication system is a technology that combines network communication and multimedia. It utilizes the efficiency of data transmission over the network and the diversity of information in multimedia, making communication between people faster, clearer, and more intuitive. The multimedia communication system is an important part of the application to the intelligent transportation system. Intelligent transportation system is a systematic, real-time, accurate, interactive, and extensive traffic management system established by the comprehensive use of modern high and new technology in the transportation system. With these characteristics, intelligent transportation system has increasingly become an important means to solve modern traffic problems. Based on multimedia communication and intelligent transportation system, this article optimizes the vehicle path and realizes the application of intelligent transportation. The proposed intelligent transportation system realizes functions, such as vehicle speed detection, vehicle behavior semantic analysis, license plate recognition by processing video data, and image data acquired based on multimedia communication, and can capture illegal vehicles and then identify illegal vehicles. The license plate is conducive to promoting the management and control of intelligent transportation and reducing the occurrence of traffic accidents.

Design of Robust Video Transmission System by Using Efficient Forward Error Correction Scheme

The advent of modern digital technologies has made multimedia communication systems one of the most demanding technologies of the time. The use of available bandwidth for efficient and errorless multimedia communication is the key challenge for the wireless communication research community. However, a wireless network has the disadvantage of being prone to random channel noise and data contamination. This paper proposes a robust video transmission framework by using an efficient forward error correction technique. In this work, the experimental performance of widely used forward error correction codes i.e., Convolution codes, LDPC codes, Turbo codes, and Concatenated codes, are compared based on their capability to compensate the channel noise and distortion. An efficient encoding scheme is devised for the transmission of YUV encoded frames by using the selected FEC codes in a noisy channel environment. The retrieved video is analysed by using the Peak Signal-to-Noise ratio and bit error rate as performance metrics. The results and cross comparison shows that concatenated codes have a handsome improvement in avoiding channel contamination and distortion.

Unified quality assessment of natural and screen content images via adaptive weighting on double scales

In multimedia communication systems, digital images may contain various visual contents, among which the natural scene images (NSIs) and screen content images (SCIs) are two important and common types. The existing full-reference image quality assessment (IQA) metrics are designed for only one type of images, but cannot precisely perceive the visual quality of another type. It is still unclear what the different characteristics are between NSIs and SCIs resulting in this failure. Inspired by some psychological studies, we figure out that it is due to the different structural scale levels between NSIs and SCIs. Given this observation, this paper introduces the gradient degradation of Gaussians (GDoG) to analyze the images’ structural scale level, proposes a fast unified IQA index for both NSIs and SCIs by incorporating an adaptive weighting strategy on double scales. Experimental results conducted on several databases verify the effectiveness and efficiency of the proposed unified IQA index for both types of images, also demonstrate that the adaptive weighting strategy based on GDoG can improve the existing models for cross-content-type images.

Assessment of Machine Learning-Based Audiovisual Quality Predictors

Quality assessment of audiovisual (AV) signals is important from the perspective of system design, optimization, and management of a modern multimedia communication system. However, automatic prediction of AV quality via the use of computational models remains challenging. In this context, machine learning (ML) appears to be an attractive alternative to the traditional approaches. This is especially when such assessment needs to be made in no-reference (i.e., the original signal is unavailable) fashion. While development of ML-based quality predictors is desirable, we argue that proper assessment and validation of such predictors is also crucial before they can be deployed in practice. To this end, we raise some fundamental questions about the current approach of ML-based model development for AV quality assessment and signal processing for multimedia communication in general. We also identify specific limitations associated with the current validation strategy which have implications on analysis and comparison of ML-based quality predictors. These include a lack of consideration of: (a) data uncertainty, (b) domain knowledge, (c) explicit learning ability of the trained model, and (d) interpretability of the resultant model. Therefore, the primary goal of this article is to shed some light into mentioned factors. Our analysis and proposed recommendations are of particular importance in the light of significant interests in ML methods for multimedia signal processing (specifically in cases where human-labeled data is used), and a lack of discussion of mentioned issues in existing literature.

Long-term rate control for concurrent multipath real-time video transmission in heterogeneous wireless networks

Concurrent multipath transmission provides an effective solution for streaming high-quality mobile videos in heterogeneous wireless networks. Rate control is commonly adopted in multimedia communication systems to fully utilize the available network bandwidth. This paper proposes a novel rate control for concurrent multipath video transmission. The existing rate control algorithms mainly adapt bit rate in the short-term pattern, i.e., without considering the long-term video transmission quality. We propose a long-term rate control scheme that takes into account the status of both the transmission buffer and video frames. First, a mathematical model is developed to formulate the non-convex problem of long-term quality maximization. Second, we develop a dynamic programming solution for online encoding bit rate control based on buffer status. The performance evaluation is conducted in a real test bed over LTE and Wi-Fi networks. Experimental results demonstrate that the proposed long-term rate control scheme achieves appreciable improvements over the short-term rate control schemes in terms of video quality and delay performance.

A Real‐Time and Long‐Term Face Tracking Method Using Convolutional Neural Network and Optical Flow in IoT‐Based Multimedia Communication Systems

The development of the Internet of Things (IoT) stimulates many research works related to Multimedia Communication Systems (MCS), such as human face detection and tracking. This trend drives numerous progressive methods. Among these methods, the deep learning‐based methods can spot face patch in an image effectively and accurately. Many people consider face tracking as face detection, but they are two different techniques. Face detection focuses on a single image, whose shortcoming is obvious, such as unstable and unsmooth face position when adopted on a sequence of continuous images; computing is expensive due to its heavy reliance on Convolutional Neural Networks (CNNs) and limited detection performance on the edge device. To overcome these defects, this paper proposes a novel face tracking strategy by combining CNN and optical flow, namely, C‐OF, which achieves an extremely fast, stable, and long‐term face tracking system. Two key things for commercial applications are the stability and smoothness of face positions in a sequence of image frames, which can provide more probability for face biological signal extraction, silent face antispoofing, and facial expression analysis in the fields of IoT‐based MCS. Our method captures face patterns in every two consequent frames via optical flow to get rid of the unstable and unsmooth problems. Moreover, an innovative metric for measuring the stability and smoothness of face motion is designed and adopted in our experiments. The experimental results illustrate that our proposed C‐OF outperforms both face detection and object tracking methods.

Comparing Delay-Constrained ALOHA and CSMA: A Learning-Based Low-Complexity Approximate Approach

Supporting delay-constrained traffic becomes more and more critical in multimedia communication systems, tactile Internet, networked control systems, and cyber-physical systems, etc. In delay-constrained traffic, each packet has a hard deadline. When it is not delivered before the hard deadline, it becomes useless and will be removed from the system. This feature is completely different from that of traditional delay-unconstrained traffic and brings new challenge to network protocol design. In this work, we study the widely-used (slotted) ALOHA and CSMA wireless access protocols but under the new delay-constrained setting. Our goal is to compare delay-constrained ALOHA and CSMA for different system settings and thus give network operators guidelines on protocol selection. We use two Markov chains to analyze delay-constrained ALOHA and CSMA, respectively. However, the number of states of Markov chains increases exponentially with respect to the number of users in the network. Therefore, we can only compare the exact performance of delay-constrained ALOHA and CSMA for small-scale networks. To address the curse of dimensionality, we design a single-user parameterized ALOHA (resp. CSMA) system, where the parameters are to be learned to approximate the original multi-user ALOHA (resp. CSMA) system. In addition, our low-complexity approach preserves the Markov-chain structure of the systems and thus enables us to compute some other interested performance metrics such as average delivery time. We use our low-complexity approach to reveal the conditions under which ALOHA (resp. CSMA) outperforms CSMA (resp. ALOHA) in the delay-constrained setting via extensive simulations.

A Novel, Efficient, and Secure Anomaly Detection Technique Using DWU‐ODBN for IoT‐Enabled Multimedia Communication Systems

The Internet of Things (IoT) is enhancing our lives in a variety of structures, which consists of smarter cities, agribusiness, and e‐healthcare, among others. Even though the Internet of Things has many features with the consumer Internet of Things, the open nature of smart devices and their worldwide connection make IoT networks vulnerable to a variety of assaults. Several approaches focused on attack detection in Internet of Things devices, which has the longest calculation times and the lowest accuracy issues. It is proposed in this paper that an attack detection framework for Internet of Things devices, based on the DWU‐ODBN method, be developed to alleviate the existing problems. At the end of the process, the proposed method is used to identify the source of the assault. It comprises steps such as preprocessing, feature extraction, feature selection, and classification to identify the source of the attack. A random oversampler is used to preprocess the input data by dealing with NaN values, categorical features, missing values, and unbalanced datasets before being used to deal with the imbalanced dataset. When the data has been preprocessed, it is then sent to the MAD Median‐KS test method, which is used to extract features from the dataset. To categorize the data into attack and nonattack categories, the features are classified using the dual weight updation‐based optimal deep belief network (DWU‐ODBN) classification technique, which is explained in more detail below. According to the results of the experimental assessment, the proposed approach outperforms existing methods in terms of detecting intrusions and assaults. The proposed work achieves 77 seconds to achieve the attack detection with an accuracy rate of 98.1%.