Real & Simulated QPSK Up-Converted Signals by a Sampling Method Using a Cascaded MZMs Link

This study focuses on a novel concept of transmitting of a quadrature phase shift keying (QPSK) modulation by an electro-optical frequency up-conversion using a cascaded Mach–Zehnder modulators (MZMs) link. Furthermore, we conduct and compare the results obtained by simulations using the Virtual Photonics Inc. (VPI) (Berlin, Germany) simulator and real-world experiments. The design and operating regime peculiarities of the MZM used as a sampling up-converter mixer in a radio over fiber (RoF) system are also analyzed. Besides, the simulation and experimental results of static and dynamic characteristics of the MZM have approximately the same behavior. The conversion gain of the cascaded MZMs link is simulated over many mixing frequencies and it can decrease from 17.5 dB at 8.3 GHz to −4.5 dB at 39.5 GHz. However, in real world settings, it may decrease from 15.5 dB at 8.3 GHz to −6 dB at 39.5 GHz. The maximum frequency range is attained at 78.5 GHz for up-conversion through simulations. Error vector magnitude (EVM) values have been done to evaluate the performance of our system. An EVM of 16% at a mixing frequency of 39.5 GHz with a bit rate of 12.5 Gbit/s was observed with the considering sampling technique, while it reached 19% in real-world settings with a sampling frequency of 39.5 GHz and a bit rate of 12.5 Gbit/s.

Research on Fast Compensation Algorithm for Interframe Motion of Multimedia Video Based on Manhattan Distance

To improve the video quality, aiming at the problems of low peak signal-to-noise ratio, poor visual effect, and low bit rate of traditional methods, this paper proposes a fast compensation algorithm for the interframe motion of multimedia video based on Manhattan distance. The absolute median difference based on wavelet transform is used to estimate the multimedia video noise. According to the Gaussian noise variance estimation result, the active noise mixing forensics algorithm is used to preprocess the original video for noise mixing, and the fuzzy C-means clustering method is used to smoothly process the noisy multimedia video and obtain significant information from the multimedia video. The block-based motion idea is to divide each frame of the video sequence into nonoverlapping macroblocks, find the best position of the block corresponding to the current frame in the reference frame according to the specific search range and specific rules, and obtain the relative Manhattan distance between the current frame and the background of multimedia video using the Manhattan distance calculation formula. Then, the motion between the multimedia video frames is compensated. The experimental results show that the algorithm in this paper has a high peak signal-to-noise ratio and a high bit rate, which effectively improves the visual effect of the video.

Coverage enhancements of vehicles users using mobile stations at 5G cellular networks

High mobility requirements are one of the challenges face fifth-generation wireless (5G) cellular networks by providing acceptable wireless services to users traveling at speed up to 350 km/h. This paper presents a new scenario to increase the bit rate and coverage for passengers that use the vehicles for traveling through the installation a mobile station (MS) on these vehicles to provide a high-quality service to users. Based on signal to noise ratio (SNR’s) mathematical derivation and the outage probability of the user link, the proposed system is evaluated. Numerical results indicate an enhancement for users who received signal strength (RSS) from (-72 to -55) dBm and (15 to 38) Mbps in bit rate. Moreover, their number of users increased by proposed system adoption.

Efficiency of spatially recursive algorithms for transmitting images of marine vessels

На современном этапе развития интеллектуальных морских технологий необходимо включить в состав видеосистемы обработки изображений две подсистемы передачи видеоинформации морских сюжетов. Во первых на основе спектрального преобразования сигналов из пространственной области в частотную для оперативной доставки видеоинформации, полученной с различных камер подводного и надводного наблюдения. Во вторых, на основе пространственных методов обработки, без перехода в спектральную область сигнала для передачи выделенных ключевых точек объектов на изображениях. При этом важнейшая особенность этих подсистем заключается в улучшении информационных показателей качества морских видеосистем автоматизированной обработкой видеоинформации: точность визуальных данных, битовая скорость передачи по каналам связи и вычислительная сложность алгоритмов анализа и передачи видеоинформации. В предлагаемом исследовании приводятся алгоритмы спектральной и пространственной обработки видеоинформации, проведена оценка эффективности алгоритмов обработки изображений. А также отражены результаты моделирования алгоритмов и сравнительная оценка информационных показателей интеллектуальных морских видеосистем: точность, битовая скорость и вычислительная сложность видеосистем обработки морских изображений. At the present stage of the development of intelligent marine technologies, it is necessary to include two subsystems for the transmission of video information of marine scenes in the video image processing system: 1) based on the spectral conversion of signals from the spatial domain to the frequency domain for the rapid delivery of video information obtained from various underwater and surface surveillance cameras; 2) based on spatial processing methods without switching to the spectral domain of the signal to transmit selected key points of objects in the images. At the same time, the most important feature of these subsystems is to improve the information quality indicators of marine video systems by automated processing of video information: the accuracy of visual data, the bit rate of transmission over communication channels and the computational complexity of algorithms for analyzing and transmitting video information. The proposed study provides algorithms for spectral and spatial processing of video information. The results of algorithm modeling and comparative evaluation of information indicators of intelligent marine video systems are also presented: accuracy, bit rate and computational complexity of marine image processing video systems.

Метод непрямого приховування інформації в процесі стиснення відеозображень

It is substantiated that steganographic systems should be used to ensure the protection of special information resources in conditions of its prompt delivery. Here, steganographic technologies are an integral part of complex information protection systems. Simultaneously, for steganographic systems, there is a contradiction between the density of embedded data and level of information compaction of video container (level of reduction of volume bit volume of compact presented video image concerning bit volume of an initial video image). It leads to the fact that under the conditions of the required quality (reliability) of digital video information, the bit rate level of the covert channel is insufficient. Consequently, the scientific-applied problem concerns the necessity to increase the integrity (the level of correspondence of the hidden information before its embedding in a video container and after its extraction) and bit rate of the hidden channel of special information transmission. It is relevant. The solution of the described problem in the field of application of steganographic transformations can be realized based on the application of two different approaches. The first approach is based on methods of direct message embedding. But this approach is characterized by introducing distortions in the video images used as a container. Therefore, changes in structural and statistical patterns in the syntactic description of the video container happen. It reduces the potential for video container compaction. The second approach to creating steganographic transformation methods is based on information hiding using indirect embedding technique. Here, the embedding process exploits the functional dependency between the elements of the video container and the elements of the embedded message. Setting a specific dependency between the elements in the video container corresponds to the embedded element with a value of "0" or "1". However, the existing indirect steganographic transformation methods have a disadvantage. It consists of an insufficient value of embedded data density. To eliminate these disadvantages, it is proposed to develop an approach that allows using not only psychovisual but also structural redundancy of video container for concealment. Therefore, the research objective of this paper is to develop a method for indirect information withholding in the video container compression process to increase the bit rate of the hidden message channel. In the process of research, a steganographic multiagent system is constructed, which allows embedding hidden message elements without loss of information based on the indirect approach by modifying the active bases of the multiagent basis considering their uncertainty. To select transformants (data sets) as containers for information embedding, the requirement of the existence of a base system with all active bases is taken into account. The number of embedded bits of the hidden message is equal to the number of active bases in the base system of the multiadic space. Because of the made experiments, the following results have been received: in the process of embedding messages based on the created method distortions in a video container is not brought; for the created method the additional increase in the hidden channel bit rate in average 5 … 7 times are reached.

Video Compression for Screen Recorded Sequences Following Eye Movements

With the advent of smartphones and tablets, video traffic on the Internet has increased enormously. With this in mind, in 2013 the High Efficiency Video Coding (HEVC) standard was released with the aim of reducing the bit rate (at the same quality) by 50% with respect to its predecessor. However, new contents with greater resolutions and requirements appear every day, making it necessary to further reduce the bit rate. Perceptual video coding has recently been recognized as a promising approach to achieving high-performance video compression and eye tracking data can be used to create and verify these models. In this paper, we present a new algorithm for the bit rate reduction of screen recorded sequences based on the visual perception of videos. An eye tracking system is used during the recording to locate the fixation point of the viewer. Then, the area around that point is encoded with the base quantization parameter (QP) value, which increases when moving away from it. The results show that up to 31.3% of the bit rate may be saved when compared with the original HEVC-encoded sequence, without a significant impact on the perceived quality.

Fast but Not Furious. When Sped Up Bit Rate of Information Drives Rule Induction

The language abilities of young and adult learners range from memorizing specific items to finding statistical regularities between them (item-bound generalization) and generalizing rules to novel instances (category-based generalization). Both external factors, such as input variability, and internal factors, such as cognitive limitations, have been shown to drive these abilities. However, the exact dynamics between these factors and circumstances under which rule induction emerges remain largely underspecified. Here, we extend our information-theoretic model (Radulescu et al., 2019), based on Shannon’s noisy-channel coding theory, which adds into the “formula” for rule induction the crucial dimension of time: the rate of encoding information by a time-sensitive mechanism. The goal of this study is to test the channel capacity-based hypothesis of our model: if the input entropy per second is higher than the maximum rate of information transmission (bits/second), which is determined by the channel capacity, the encoding method moves gradually from item-bound generalization to a more efficient category-based generalization, so as to avoid exceeding the channel capacity. We ran two artificial grammar experiments with adults, in which we sped up the bit rate of information transmission, crucially not by an arbitrary amount but by a factor calculated using the channel capacity formula on previous data. We found that increased bit rate of information transmission in a repetition-based XXY grammar drove the tendency of learners toward category-based generalization, as predicted by our model. Conversely, we found that increased bit rate of information transmission in complex non-adjacent dependency aXb grammar impeded the item-bound generalization of the specific a_b frames, and led to poorer learning, at least judging by our accuracy assessment method. This finding could show that, since increasing the bit rate of information precipitates a change from item-bound to category-based generalization, it impedes the item-bound generalization of the specific a_b frames, and that it facilitates category-based generalization both for the intervening Xs and possibly for a/b categories. Thus, sped up bit rate does not mean that an unrestrainedly increasing bit rate drives rule induction in any context, or grammar. Rather, it is the specific dynamics between the input entropy and the maximum rate of information transmission.