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A dataset has been created from an experiment regarding the subjective Quality of Experience (QoE) in relation to stalling video feeds in interactive 6-Degrees-of-freedom Virtual Reality (6-DOF VR). The main purpose of collecting this data is to provide insight into the QoE of stalls that may occur in interactive remote-rendered 6-DOF VR. The data contains information regarding user ratings coupled with various stall lengths and for both frozen or reprojected images. Additionally, user motion and pixel changes (in the form of Mean Square Errors) in successive images in the vicinity of the stall are also stored. In summary, 29 users participated in testing, each rating 16 scenes, amounting to a total of 464 rated scenes. © 2022 IEEE.

Subjective 360° video quality experiments provide the ground truth for developing related systems such that acceptable quality of experience is offered to the users. To obtain statistically meaningful insights from the data recorded in quality experiments, engaging a sufficiently large number of subjects is essential. In contrast to conventional videos, little has been reported on statistical measures that may guide the choice of the number of subjects required for 360° video quality experiments. In this paper, the standard deviation of opinion score (SOS) hypothesis, measuring the diversity among the opinion scores given by a panel of subjects, is used to reveal the number of subjects needed. It is shown that the number of subjects needed varies depending on a threshold on SOS characteristics in terms of diversity among opinion scores. © 2022 IEEE.

Data hiding or information hiding is a prominent class of information security that aims at reliably conveying secret data embedded in a cover object over a covert channel. Digital media such as audio, image, video, and three-dimensional (3D) media can act as cover objects to carry such secret data. Digital media security has acquired tremendous significance in recent years and will be even more important with the development and delivery of new digital media over digital communication networks. In particular, least significant bit (LSB) data hiding is easy to implement and to combine with other hiding techniques, offers high embedding capacity for data, can resist steganalysis and several types of attacks, and is well suited for real-time applications. This article provides a comprehensive survey on LSB data hiding in digital media. The fundamental concepts and terminologies used in data hiding are reviewed along with a general data hiding model. The five attributes of data hiding, i.e., capacity, imperceptibility, robustness, detectability, and security, and the related performance metrics used in this survey to compare the characteristics of the different LSB data hiding methods are discussed. Given the classification of data hiding methods with respect to audio, image, video, and 3D media, a comprehensive survey of LSB data hiding for each of these four digital media is provided. In particular, landmark studies, state-of-the-art approaches, and applications of LSB data hiding are described for each of the four digital media. Their performance is compared with respect to the data hiding attributes which illustrates benefits and drawbacks of the reviewed LSB data hiding methods. The article concludes with summarizing main findings and suggesting directions for future research. This survey will be helpful for researchers and practitioners to keep abreast about the potential of LSB data hiding in digital media and to develop novel applications based on suitable performance trade-offs between data hiding attributes.

In this paper, we propose a viewing direction weighted bit plane least significant bit (LSB) data hiding method for 360° videos. Normalized Gaussian mixture models (GMMs) of the distributions of the relative viewing direction frequency for latitude, longitude, and both latitude and longitude are used to describe the human viewing behavior of 360° videos on head-mounted displays (HMDs). Apart from formulating data hiding weight functions to control the amount of secret data to be hidden at given latitudes and longitudes, the GMMs are used in this work also to define viewing direction weighted bit plane functions. These viewing direction weighted bit plane functions specify the number of bit planes to be used for data hiding depending on the latitude and longitude. As humans pay more attention to the central front view of 360° videos when watched on HMDs, the number of engaged bit planes is decreased accordingly from the poles to the equator, and from the west and the east to the front view. A performance assessment of the proposed viewing direction weighted bit plane LSB data hiding method is conducted, showing the trade-offs between capacity and objective perceptual video quality. The results indicate that it is preferable to first utilize a given bit plane for data hiding in an entire 360° video frame before engaging the next higher bit plane subject to the viewing direction weighted bit plane functions. © 2021 IEEE.

In this paper, we propose a viewing direction based least significant bit (LSB) data hiding method for 360◦ videos. The distributions of viewing direction frequency for latitude and longitude are used to control the amount of secret data to be hidden at the latitude, longitude, or both latitude and longitude of 360◦ videos. Normalized Gaussian mixture models mimicking the viewing behavior of humans are formulated to define data hiding weight functions for latitude, longitude, and both latitude and longitude. On this basis, analytical expressions for the capacity offered by the proposed method to hide secret data in 360◦ cover videos are derived. Numerical results for the capacity using different numbers of bit planes and popular 360◦ video resolutions for data hiding are provided. The fidelity of the proposed method is assessed in terms of the peak signal-to-noise ratio (PSNR), weighted-to-spherically uniform PSNR (WS-PSNR), and non-content-based perceptual PSNR (NCP-PSNR). The experimental results illustrate that NCP-PSNR returns the highest fidelity because it gives lower weights to the impact of LSB data hiding on fidelity outside the front regions near the equator. The visual quality of the proposed method as perceived by humans is assessed using the structural similarity (SSIM) index and the non-content-based perceptual SSIM (NCP-SSIM) index. The experimental results show that both SSIM-based metrics are able to account for the spatial perceptual information of different scenes while the PSNR-based fidelity metrics cannot exploit this information. Furthermore, NCP-SSIM reflects much better the impact of the proposed method on visual quality with respect to viewing directions compared to SSIM. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. open access

The development of immersive media systems and services relies on subjective tests that provide ground truth on the quality of experience as perceived by humans. In this paper, we investigate the opinion score consistency through a repeated subjective 360° video quality assessment experiment. The test stimuli are presented on a head-mounted display with participants given the task to rate the video quality in three repeated sessions for both standing and seated viewing. The statistical analysis of the data from the subjective tests aims at revealing if participants change their rating behavior over time or keep their opinion scores given to the test stimuli in standing and seated viewing consistent in a statistical sense. The experimental results are reported in terms of histograms of opinion scores, skewness and kurtosis of opinion scores, mean opinion scores, standard deviation of opinion scores (SOS), SOS fitting functions, and analysis of variance tests. The statistical analysis supports the conjecture that each participant has its own but consistent rating behavior throughout the respective sessions for standing and seated viewing. The finding that the quality rating behavior of the individual participant does not fundamentally change over time may, e.g., assist in scheduling subjective tests under pandemic conditions where experimental campaigns may need to be stalled for an unknown period of time. © 2021 IEEE. open access

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented.

In this paper, we study the performance of multiple-input multiple-output cognitive amplify-and-forward relay networks using orthogonal space–time block coding over independent Nakagami-m fading. It is assumed that both the direct transmission and the relaying transmission from the secondary transmitter to the secondary receiver are applicable. In order to process the received signals from these links, selection combining is adopted at the secondary receiver. To evaluate the system performance, an expression for the outage probability valid for an arbitrary number of transceiver antennas is presented. We also derive a tight approximation for the symbol error rate to quantify the error probability. In addition, the asymptotic performance in the high signal-to-noise ratio regime is investigated to render insights into the diversity behavior of the considered networks. To reveal the effect of network parameters on the system performance in terms of outage probability and symbol error rate, selected numerical results are presented. In particular, these results show that the performance of the system is enhanced when increasing the number of antennas at the transceivers of the secondary network. However, increasing the number of antennas at the primary receiver leads to a degradation in the secondary system performance.

Due to the rapid development of wireless communications together with the inflexibility of the current spectrum allocation policy, radio spectrum becomes more and more exhausted. One of the critical challenges of wireless communication systems is to efficiently utilize the limited frequency resources to be able to support the growing demand of high data rate wireless services. As a promising solution, cognitive radios have been suggested to deal with the scarcity and under-utilization of radio spectrum. The basic idea behind cognitive radios is to allow unlicensed users, also called secondary users (SUs), to access the licensed spectrum of primary users (PUs) which improves spectrum utilization. In order to not degrade the performance of the primary networks, SUs have to deploy interference control, interference mitigating, or interference avoidance techniques to minimize the interference incurred at the PUs. Cognitive radio networks (CRNs) have stimulated a variety of studies on improving spectrum utilization. In this context, this thesis has two main objectives. Firstly, it investigates the performance of single hop CRNs with spectrum sharing and opportunistic spectrum access. Secondly, the thesis analyzes the performance improvements of two hop cognitive radio networks when incorporating advanced radio transmission techniques. The thesis is divided into three parts consisting of an introduction part and two research parts based on peer-reviewed publications. Fundamental background on radio propagation channels, cognitive radios, and advanced radio transmission techniques are discussed in the introduction. In the first research part, the performance of single hop CRNs is analyzed. Specifically, underlay spectrum access using M/G/1/K queueing approaches is presented in Part I-A while dynamic spectrum access with prioritized traffics is studied in Part I-B. In the second research part, the performance benefits of integrating advanced radio transmission techniques into cognitive cooperative radio networks (CCRNs) are investigated. In particular, opportunistic spectrum access for amplify-and-forward CCRNs is presented in Part II-A where collaborative spectrum sensing is deployed among the SUs to enhance the accuracy of spectrum sensing. In Part II-B, the effect of channel estimation error and feedback delay on the outage probability and symbol error rate (SER) of multiple-input multiple-output CCRNs is investigated. In Part II-C, adaptive modulation and coding is employed for decode-and-forward CCRNs to improve the spectrum efficiency and to avoid buffer overflow at the relay. Finally, a hybrid interweave-underlay spectrum access scheme for a CCRN is proposed in Part II-D. In this work, the dynamic spectrum access of the PUs and SUs is modeled as a Markov chain which then is utilized to evaluate the outage probability, SER, and outage capacity of the CCRN.

In this paper, we analyze the performance of cognitive amplify-and-forward (AF) relay networks with beamforming under the peak interference power constraint of the primary user (PU). We focus on the scenario that beamforming is applied at the multi-antenna secondary transmitter and receiver. Also, the secondary relay network operates in channel state information assisted AF mode, and the signals undergo independent Nakagami-m fading. In particular, closed-form expressions for the outage probability and symbol error rate (SER) of the considered network over Nakagami-m fading are presented. More importantly, asymptotic closed-form expressions for the outage probability and SER are derived. These tractable closed-form expressions for the network performance readily enable us to evaluate and examine the impact of network parameters on the system performance. Specifically, the impact of the number of antennas, the fading severity parameters, the channel mean powers, and the peak interference power is addressed. The asymptotic analysis manifests that the peak interference power constraint imposed on the secondary relay network has no effect on the diversity gain. However, the coding gain is affected by the fading parameters of the links from the primary receiver to the secondary relay network.