The kindest cut: Enhancing the user experience of mobile tv through adequate zooming

The growing market of Mobile TV requires automated adaptation of standard TV footage to small size displays. Especially extreme long shots (XLS) depicting distant objects can spoil the user experience, e.g. in soccer content. Automated zooming schemes can improve the visual experience if the resulting footage meets user expectations in terms of the visual detail and quality but does not omit valuable context information. Current zooming schemes are ignorant of beneficial zoom ranges for a given target size when applied to standard definition TV footage. In two experiments 84 participants were able to switch between original and zoom enhanced soccer footage at three sizes - from 320x240 (QVGA) down to 176x144 (QCIF). Eye tracking and subjective ratings showed that zoom factors between 1.14 and 1.33 were preferred for all sizes. Interviews revealed that a zoom factor of 1.6 was too high for QVGA content due to low perceived video quality, but beneficial for QCIF size. The optimal zoom depended on the target display size. We include a function to compute the optimal zoom for XLS depending on the target device size. It can be applied in automatic content adaptation schemes and should stimulate further research on the requirements of different shot types in video coding

Satellite Communications [Editorial]

YesWe are delighted to bring to you this special issue on satellite communications, which we have prepared as part of the spreading of excellence remit of the satellite communications network of excellence (SatNEx). The SatNEx project, which began in 2004, is funded for five years under the European Union¿s Sixth Framework Programme (FP6) Information Society Technologies (IST) Thematic Area. Led by the German Aerospace Center, SatNEx brings together a network of 24 partners, distributed throughout Europe, with membership drawn from ten countries. The philosophy underlying the SatNEx approach revolves around the selection of focused actions under Joint Programmes of Activities, which are carried out collectively by the partners and include research, integration, and dissemination activities. Training represents an important part of the SatNEx remit and is supported through a number of initiatives including the hosting of internship projects and an annual summer school. The call for papers resulted in a high number of submissions, from which we have been able to select 12 excellent papers dealing with the different aspects of satellite communications and navigation.European Unio

Adaptive Network Coding Schemes for Satellite Communications

In this paper, we propose two novel physical layer aware adaptive network coding and coded modulation schemes for time variant channels. The proposed schemes have been applied to different satellite communications scenarios with different Round Trip Times (RTT). Compared to adaptive network coding, and classical non-adaptive network coding schemes for time variant channels, as benchmarks, the proposed schemes demonstrate that adaptation of packet transmission based on the channel variation and corresponding erasures allows for significant gains in terms of throughput, delay and energy efficiency. We shed light on the trade-off between energy efficiency and delay-throughput gains, demonstrating that conservative adaptive approaches that favors less transmission under high erasures, might cause higher delay and less throughput gains in comparison to non-conservative approaches that favor more transmission to account for high erasures.Comment: IEEE Advanced Satellite Multimedia Systems Conference and the 14th Signal Processing for Space Communications Workshop (ASMS/SPSC), 201

Network Coding Channel Virtualization Schemes for Satellite Multicast Communications

In this paper, we propose two novel schemes to solve the problem of finding a quasi-optimal number of coded packets to multicast to a set of independent wireless receivers suffering different channel conditions. In particular, we propose two network channel virtualization schemes that allow for representing the set of intended receivers in a multicast group to be virtualized as one receiver. Such approach allows for a transmission scheme not only adapted to per-receiver channel variation over time, but to the network-virtualized channel representing all receivers in the multicast group. The first scheme capitalizes on a maximum erasure criterion introduced via the creation of a virtual worst per receiver per slot reference channel of the network. The second scheme capitalizes on a maximum completion time criterion by the use of the worst performing receiver channel as a virtual reference to the network. We apply such schemes to a GEO satellite scenario. We demonstrate the benefits of the proposed schemes comparing them to a per-receiver point-to-point adaptive strategy

Energy Efficient Adaptive Network Coding Schemes for Satellite Communications

In this paper, we propose novel energy efficient adaptive network coding and modulation schemes for time variant channels. We evaluate such schemes under a realistic channel model for open area environments and Geostationary Earth Orbit (GEO) satellites. Compared to non-adaptive network coding and adaptive rate efficient network-coded schemes for time variant channels, we show that our proposed schemes, through physical layer awareness can be designed to transmit only if a target quality of service (QoS) is achieved. As a result, such schemes can provide remarkable energy savings.Comment: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 24 March 201

Graph-Based User Scheduling Algorithms for LEO-MIMO Non-Terrestrial Networks

In this paper, we study the user scheduling prob-lem in a Low Earth Orbit (LEO) Multi-User Multiple-Input-Multiple-Output (MIMO) system. We propose an iterative graph-based maximum clique scheduling approach, in which users are grouped together based on a dissimilarity measure and served by the satellite via space-division multiple access (SDMA) by means of Minimum Mean Square Error (MMSE) digital beamforming on a cluster basis. User groups are then served in different time slots via time-division multiple access (TDMA). As dissimilarity measure, we consider both the channel coefficient of correlation and the users' great circle distance. A heuristic optimization of the optimal cluster size is performed in order to maximize the system capacity. To further validate our analysis, we compare our proposed graph-based schedulers with the well-established algorithm known as Multiple Antenna Downlink Orthogonal clustering (MADOC). Results are presented in terms of achievable per-user capacity and show the superiority in performance of the proposed schedulers w.r.t. MADOC

Improved Graph-Based User Scheduling For Sum-Rate Maximization in LEO-NTN Systems

In this paper, we study the problem of user scheduling for Low Earth Orbit (LEO) Multi-User (MU) Multiple-Input-Multiple-Output (MIMO) Non-Terrestrial Network (NTN) systems with the objective of maximizing the sum-rate capacity while minimizing the total number of clusters. We propose an iterative graph-based maximum clique scheduling approach with constant graph density. Users are grouped together based on the channel coefficient of correlation (CoC) as dissimilarity metric and served by the satellite via Space Division Multiple Access (SDMA) by means of Minimum Mean Square Error (MMSE) digital beamforming on a cluster basis. Clusters are then served in different time slots via Time Division Multiple Access (TDMA). The results, presented in terms of per-cluster sum-rate capacity and per-user throughput, show that the presented approach can significantly improve the system performance

Joint Graph-based User Scheduling and Beamforming in LEO-MIMO Satellite Communication Systems

In this paper, a Low earth orbit (LEO) High-Throughput Satellite (HTS) Multi-User multiple-input multiple-output (MIMO) system is considered. With the objective of minimizing inter-beam interference among users, we propose a joint graph-based user scheduling and feed space beamforming framework for the downlink. First, we construct a graph where the vertices are the users and edges are based on a dissimilarity measure of their channels. Secondly, we design a low complexity greedy user clustering strategy, in which we iteratively search for the maximum clique in the graph. Finally, a Minimum Mean Square Error (MMSE) beamforming matrix is applied on a cluster basis with different power normalization schemes. A heuristic optimization of the graph density, i.e., optimal cluster size, is performed in order to maximize the system capacity. The proposed scheduling algorithm is compared with a position-based scheduler, in which a beam lattice is generated on ground and one user per beam is randomly selected to form a cluster. Results are presented in terms of achievable per-user capacity and show the superiority in performance of the proposed scheduler w.r.t. to the position-based approach

Evaluation of MU-MIMO Digital Beamforming Algorithms in B5G/6G LEO Satellite Systems

Satellite Communication (SatCom) systems will be a key component of 5G and 6G networks to achieve the goal of providing unlimited and ubiquitous communications and deploying smart and sustainable networks. To meet the ever-increasing demand for higher throughput in 5G and beyond, aggressive frequency reuse schemes (i.e., full frequency reuse), combined with digital beamforming techniques to cope with the massive co-channel interference, are recognized as a key solution. Aimed at (i) eliminating the joint optimization problem among the beamforming vectors of all users, (ii) splitting it into distinct ones, and (iii) finding a closed-form solution, we propose a beamforming algorithm based on maximizing the users' Signal-to-Leakage-and-Noise Ratio (SLNR) served by a Low Earth Orbit (LEO) satellite. We investigate and assess the performance of several beamforming algorithms, including both those based on Channel State Information (CSI) at the transmitter, i.e., Minimum Mean Square Error (MMSE) and Zero-Forcing (ZF), and those only requiring the users' locations, i.e., Switchable Multi-Beam (MB). Through a detailed numerical analysis, we provide a thorough comparison of the performance in terms of per-user achievable spectral efficiency of the aforementioned beamforming schemes, and we show that the proposed SLNR beamforming technique is able to outperform both MMSE and ZF schemes in the presented SatCom scenario

Evaluation of multi-user multiple-input multiple-output digital beamforming algorithms in B5G/6G low Earth orbit satellite systems

Satellite communication systems will be a key component of 5G and 6G networks to achieve the goal of providing unlimited and ubiquitous communications and deploying smart and sustainable networks. To meet the ever-increasing demand for higher throughput in 5G and beyond, aggressive frequency reuse schemes (i.e., full frequency reuse), combined with digital beamforming techniques to cope with the massive co-channel interference, are recognized as a key solution. Aimed at (i) eliminating the joint optimization problem among the beamforming vectors of all users, (ii) splitting it into distinct ones, and (iii) finding a closed-form solution, we propose a beamforming algorithm based on maximizing the users' signal-to-leakage-and-noise ratio served by a low Earth orbit satellite. We investigate and assess the performance of several beamforming algorithms, including both those based on channel state information at the transmitter, that is, minimum mean square error and zero forcing, and those only requiring the users' locations, that is, switchable multi-beam. Through a detailed numerical analysis, we provide a thorough comparison of the performance in terms of per-user achievable spectral efficiency of the aforementioned beamforming schemes, and we show that the proposed signal to-leakage-plus-noise ratio beamforming technique is able to outperform both minimum mean square error and multi-beam schemes in the presented satellite communication scenario