MIMO optical satellite systems: Power allocation with classical optimization methods and with Deep Learning Techniques

Καψής, Θεόδωρος; Kapsis, Theodoros

dc.contributor.author	Καψής, Θεόδωρος	el
dc.contributor.author	Kapsis, Theodoros	en
dc.date.accessioned	2024-08-29T09:21:52Z
dc.date.available	2024-08-29T09:21:52Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/60040
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.27736
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/gr/	*
dc.subject	Atmospheric turbulence	en
dc.subject	Free space optical	en
dc.subject	Scintillation	en
dc.subject	Satellite communications	en
dc.subject	Power allocation	en
dc.subject	Ασύρματες οπτικές επικοινωνίες	el
dc.subject	Βέλτιστη ανάθεση ισχύος	el
dc.subject	Ατμοσφαιρικοί στροβιλισμοί	el
dc.subject	Σπινθηρισμοί	el
dc.subject	Δορυφορικά δίκτυα	el
dc.title	MIMO optical satellite systems: Power allocation with classical optimization methods and with Deep Learning Techniques	en
dc.title	Οπτικά Δορυφορικά Συστήματα ΜΙΜΟ: Ανάθεση Ισχύος με Κλασικές Μεθόδους Βελτιστοποίησης και με Τεχνικές Βαθιάς Μάθησης	el
heal.type	doctoralThesis
heal.secondaryTitle	Οπτικά Δορυφορικά Συστήματα ΜΙΜΟ: Ανάθεση Ισχύος με Κλασικές Μεθόδους Βελτιστοποίησης και με Τεχνικές Βαθιάς Μάθησης	el
heal.classification	Electrical engineering	en
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2024-04-22
heal.abstract	Fifth-generation (5G) cellular networks are engineered to satisfy the unique requirements of a variety of emerging services, each with escalating demands: Broadband services characterized by low latency, security, high-speed, diversity, and high reliability. Because of their universal coverage, connectivity, scalability, and robustness, satellite communications and non-terrestrial networks are regarded as enabling technologies towards beyond 5G (B5G). High-throughput satellites (HTS) in the Ka-band (26–40 GHz) can be employed for Internet of Things (IoT) applications and backhauling because satellite technologies are now sufficiently mature for these usages. In addition, a number of countries and international space agencies take part in the exploration of Mars, the Moon, deep-space, and near-Earth. In the new space sector, optimizing satellite communications is another crucial field. Conventional radio frequency (RF) lines are unable to offer such high regulation because of the restricted spectrum available. In the satellite community, there has been a growing interest in free space optical (FSO) communication as an alternative to RF communication. Nonetheless, FSO is susceptible to the detrimental effects of scintillation, pointing errors, and clear air turbulence. This Thesis focuses on the study of optical satellite communication systems and in particular on the modeling of the optical downlink (DL) channel and the optimization of power allocation in multiple-input multiple-output (MIMO) optical satellite networks. Emphasis is placed on the adverse effects faced by the laser beam from propagating in the Earth's atmosphere and on their mitigation techniques. First, for the accurate prediction of DL optical channel irradiance scintillations, a methodology was developed that generates time series using stochastic differential equations and validates them in terms of first and second-order statistics (probability density function, cumulative distribution function, power spectral density). Then, all-optical MIMO satellite system scenarios are considered, and optimal and efficient power allocation algorithms are proposed. The primary problem is formulated as a convex optimization problem with maximum allowed transmit power constraints to maximize capacity and then decomposed into independent convex sub-problems. The entire proposed methodology is based on the water-filling algorithm and satisfies the Karush-Kuhn-Tucker (KKT) conditions. Moreover, optimal power control in hybrid satellite relays is investigated. A dual-hop decode-and-forward optical DL link for a geostationary satellite source is considered. Spatial correlation, correlation matrices and, coefficients are included. Additionally, the power optimization problem is formulated and solved non-linearly for hybrid automatic repeat request (HARQ) schemes in low-earth orbit (LEO) satellites. Then, the power optimization problem incorporates the pointing errors, and a robust maximin methodology is proposed to deal with optical jitter uncertainty. Finally, the Dissertation concludes with the study of neural networks, deep learning, and deep reinforcement learning algorithms. A model-free learning algorithm is proposed that accurately predicts the optimal power distribution in each optical channel.	en
heal.advisorName	Παναγόπουλος, Αθανάσιος	el
heal.committeeMemberName	Παναγόπουλος, Αθανάσιος	el
heal.committeeMemberName	Κωττής, Παναγιώτης	el
heal.committeeMemberName	Φικιώρης, Γεώργιος	el
heal.committeeMemberName	Ματσόπουλος, Γεώργιος	el
heal.committeeMemberName	Ρουσσάκη, Ιωάννα	el
heal.committeeMemberName	Γκίκας, Βασίλειος	el
heal.committeeMemberName	Νισταζάκης, Έκτορας	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών	el
heal.academicPublisherID	ntua
heal.numberOfPages	166 σ.	el
heal.fullTextAvailability	false