References of "Ottersten, Björn 50002797"
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See detailDemand and Interference Aware Adaptive Resource Management for High Throughput GEO Satellite Systems
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

in IEEE Open Journal of the Communications Society (2022)

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS ... [more ▼]

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS) systems. Accordingly, future satellites are expected to employ advanced resource/interference management techniques to achieve high system spectrum efficiency and low power consumption while ensuring user demand satisfaction. This paper proposes a novel demand and interference aware adaptive resource management for geostationary (GEO) VHTS systems. For this, we formulate a multi-objective optimization problem to minimize the total transmit power consumption and system bandwidth usage while matching the offered capacity with the demand per beam. In this context, we consider resource management for a system with full-precoding, i.e. all beams are precoded; without precoding, i.e. no precoding is applied to any beam; and with partial precoding, i.e. only some beams are precoded. The nature of the problem is non-convex and we solve it by jointly using the Dinkelbach and Successive Convex Approximation (SCA) methods. The simulation results show that the proposed method outperforms the benchmark schemes. Specifically, we show that the proposed method requires low resource consumption, low computational time, and simultaneously achieves a high demand satisfaction. [less ▲]

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See detail5G-SpaceLab
Querol, Jorge UL; Abdalla, Abdelrahman UL; Bokal, Zhanna UL et al

Poster (2021, April 19)

The new phase of space exploration involves a growing number of human and robotic missions with varying communication and service requirements. Continuous, maximum coverage of areas where activities are ... [more ▼]

The new phase of space exploration involves a growing number of human and robotic missions with varying communication and service requirements. Continuous, maximum coverage of areas where activities are concentrated and orbiting missions (single spacecraft or constellations) around the Earth, Moon or Mars will be particularly challenging. The standardization of the 5G Non-Terrestrial Networks (NTN) has already begun [1], and nothing prevents 5G from becoming a common communications standard supporting space resource missions [2]. The 5G Space Communications Lab (5G-SpaceLab) is an interdisciplinary experimental platform, funded by the Luxembourg Space Agency and is part of the Space Research Program of SnT. The lab allows users to design and emulate realistic space communications and control scenarios for the next-generation of space applications. The capabilities of the 5G-SpaceLab testbed combine the experience of different disciplines including space communications, space and satellite mission design, and space robotics. The most relevant include the demonstration of SDR 5G NTN terminals including NB-IoT, emulation of space communications channel scenarios (e.g. link budget, delay, Doppler…), small satellite platform and payload design and testing, satellite swarm flight formation, lunar rover and robotic arm control and AI-powered telerobotics. Earth-Moon communications is one of the scenarios demonstrated in the 5G-SpaceLab. Bidirectional communication for the teleoperation of lunar rovers for near real-time operations including data collection and sensors feedback will be tested. AI-based approaches for perception and control will be developed to overcome communication delays and to provide safer, trustworthy, and efficient remote control of the rovers. [1] 3GPP Release 17 Timeline. [Online]. Available: https://www.3gpp.org/release-17 [2] Nokia, Nokia selected by NASA to build first ever cellular network on the Moon. [Online]. Available: https://www.nokia.com/about-us/news/releases/2020/10/19/nokia-selected-by-nasa-to-build-first-ever-cellular-network-on-the-moon/ [less ▲]

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See detailActive Popularity Learning with Cache Hit Ratio Guarantees using a Matrix Completion Committee
Bommaraveni, Srikanth UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

Scientific Conference (2020, October 08)

Edge caching is a promising technology to facethe stringent latency requirements and back-haul trafficoverloading in 5G wireless networks. However, acquiringthe contents and modeling the optimal cache ... [more ▼]

Edge caching is a promising technology to facethe stringent latency requirements and back-haul trafficoverloading in 5G wireless networks. However, acquiringthe contents and modeling the optimal cache strategy is achallenging task. In this work, we use an active learningapproach to learn the content popularities since it allowsthe system to leverage the trade-off between explorationand exploitation. Exploration refers to caching new fileswhereas exploitation use known files to cache, to achievea good cache hit ratio. In this paper, we mainly focus tolearn popularities as fast as possible while guaranteeing anoperational cache hit ratio constraint. The effectiveness ofproposed learning and caching policies are demonstratedvia simulation results as a function of variance, cache hitratio and used storage. [less ▲]

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See detailActive Content Popularity Learning via Query-by-Committee for Edge Caching
Bommaraveni, Srikanth UL; Vu, Thang; Vuppala, Satyanarayana et al

Scientific Conference (2019, November 03)

Edge caching has received much attention as an effective solution to face the stringent latency requirements in 5G networks due to the proliferation of handset devices as well as data-hungry applications ... [more ▼]

Edge caching has received much attention as an effective solution to face the stringent latency requirements in 5G networks due to the proliferation of handset devices as well as data-hungry applications. One of the challenges in edge caching systems is to optimally cache strategic contents to maximize the percentage of total requests served by the edge caches. To enable the optimal caching strategy, we propose an Active Learning approach (AL) to learn and design an accurate content request prediction algorithm. Specifically, we use an AL based Query-by-committee (QBC) matrix completion algorithm with a strategy of querying the most informative missing entries of the content popularity matrix. The proposed AL framework leverage's the trade-off between exploration and exploitation of the network, and learn the user's preferences by posing queries or recommendations. Later, it exploits the known information to maximize the system performance. The effectiveness of proposed AL based QBC content learning algorithm is demonstrated via numerical results. [less ▲]

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