Call Admission Control in Mobile and Wireless Networks

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Design and analysis of digital communication within an SoC-based control system for trapped-ion quantum computing

Electronic control systems used for quantum computing have become increasingly complex as multiple qubit technologies employ larger numbers of qubits with higher fidelity targets. Whereas the control systems for different technologies share some similarities, parameters like pulse duration, throughput, real-time feedback, and latency requirements vary widely depending on the qubit type. In this paper, we evaluate the performance of modern System-on-Chip (SoC) architectures in meeting the control demands associated with performing quantum gates on trapped-ion qubits, particularly focusing on communication within the SoC. A principal focus of this paper is the data transfer latency and throughput of several high-speed on-chip mechanisms on Xilinx multi-processor SoCs, including those that utilize direct memory access (DMA). They are measured and evaluated to determine an upper bound on the time required to reconfigure a gate parameter. Worst-case and average-case bandwidth requirements for a custom gate sequencer core are compared with the experimental results. The lowest-variability, highest-throughput data-transfer mechanism is DMA between the real-time processing unit (RPU) and the PL, where bandwidths up to 19.2 GB/s are possible. For context, this enables reconfiguration of qubit gates in less than 2\mics\!, comparable to the fastest gate time. Though this paper focuses on trapped-ion control systems, the gate abstraction scheme and measured communication rates are applicable to a broad range of quantum computing technologies

Optimal resource allocation in multi-service wireless networks

The PhD thesis addresses the problem of optimal resource allocation in the uplink of multi-service wireless networks of third, fourth and next generation. Particular emphasis is placed on the fulfillment of users’ Quality of Service (QoS) prerequisites, either requesting real-time or non-real time services, which requires compliance with strict short-term and long-term delay and data rate constraints, respectively. Taking into account these restrictions, various optimization problems are modeled and solved aiming at allocating the resources to the users, covering the research gap in the recent literature.Initially, the problem of utility-based optimal power control in CDMA wireless networks with real-time services is introduced. The problem is further generalized to the uplink power control in QoS-aware multi-service (i.e. real-time services and data services) CDMA wireless networks, while the concept of convex pricing of user’s uplink transmission power is introduced in order to obtain a socially efficient power allocation. Then, the joint utility-based uplink power and rate control problem is addressed in the uplink of CDMA wireless networks with multiple services. The problem is treated as a two variable game and the unique equilibrium point considering both system resources is determined.Furthermore, the study is extended to SC-FDMA wireless networks via proposing a heuristic utility-based uplink joint power and subcarrier allocation. The results of the proposed approach are improved by adopting the bargaining theory, which concludes to an energy-efficient subcarrier allocation in SC-FDMA wireless networks, while user’s transmission power is allocated in an optimal way.Finally, the research is extended to the two-tier femtocell wireless networks. Initially, the problem of efficient uplink power control in multi-service two-tier femtocell networks via a game theoretic approach was investigated via considering not only the type of service being requested, but also the two-tier architecture. The research is completed by addressing the combined power and rate allocation problem in multi-service two-tier femtocell networks via a game theoretic approach.Η παρούσα διδακτορική διατριβή πραγματεύεται το πρόβλημα της βέλτιστης κατανομής πόρων και εξυπηρέτησης πολλαπλών υπηρεσιών σε ασύρματα δίκτυα τρίτης, τέταρτης και επόμενης γενιάς. Ιδιαίτερη έμφαση δίδεται στη ζεύξη ανόδου και στην ικανοποίηση των κριτηρίων ποιότητας υπηρεσίας των χρηστών με υπηρεσίες πραγματικού χρόνου και υπηρεσίες δεδομένων, οι οποίες απαιτούν την τήρηση αυστηρών βραχυπρόθεσμων κριτηρίων καθυστέρησης και μακροπρόθεσμων κριτηρίων ρυθμού μετάδοσης δεδομένων, αντίστοιχα. Λαμβάνοντας υπόψη τις παραπάνω ιδιαιτερότητες, πραγματοποιείται μοντελοποίηση και επίλυση προβλημάτων βελτιστοποίησης κατανομής των πόρων του δικτύου στους χρήστες καλύπτοντας το μέχρι τώρα ερευνητικό κενό στη διεθνή βιβλιογραφία.Αρχικά εισάγεται το πρόβλημα της βέλτιστης κατανομής ισχύος εκπομπής στη ζεύξη ανόδου CDMA ασύρματων δικτύων με την εξυπηρέτηση υπηρεσιών πραγματικού χρόνου. Στη συνέχεια, το πρόβλημα γενικεύεται και έχει ως στόχο τη βέλτιστη κατανομή ισχύος εκπομπής με την ταυτόχρονη εξυπηρέτηση πολλαπλών υπηρεσιών (δηλαδή υπηρεσιών πραγματικού χρόνου και υπηρεσιών δεδομένων). Έπειτα στα δύο προγενέστερα προβλήματα εισάγεται η έννοια της κυρτής κοστολόγησης ως προς την ισχύ εκπομπής των χρηστών με στόχο τη βελτίωση της λύσης του προβλήματος, με γνώμονα το κοινωνικό όφελος των χρηστών. Επιπρόσθετα, μοντελοποιείται το πρόβλημα της συνδυαστικής κατανομής ισχύος εκπομπής και ρυθμού μετάδοσης στη ζεύξη ανόδου CDMA ασύρματων δικτύων με την εξυπηρέτηση πολλαπλών υπηρεσιών. Το πρόβλημα αντιμετωπίζεται ως ένα διπαραμετρικό πρόβλημα και καταλήγει στην εύρεση μοναδικού σημείου ισορροπίας και ως προς τους δύο πόρους του συστήματος που κατανέμονται στους χρήστες.Η μελέτη επεκτείνεται σε ασύρματα δίκτυα τέταρτης και επόμενης γενιάς με χρήση τεχνολογίας SC-FDMA και προτείνεται ένας ευρεστικός αλγόριθμος συνδυαστικής κατανομής ισχύος εκπομπής και υποφερουσών στους χρήστες. Η προτεινόμενη προσέγγιση βελτιώνεται με τη χρήση μοντέλων διαπραγμάτευσης, τα οποία συνεισφέρουν στην αποδοτικότερη κατανομή των υποφερουσών στους χρήστες, ενώ έπειτα η ισχύς εκπομπής κατανέμεται στους χρήστες κατά το βέλτιστο τρόπο.Τέλος, η έρευνα επεκτείνεται σε διεπίπεδα φεμτοκυψελωτά ασύρματα δίκτυα, όπου αρχικά επιτυγχάνεται η βέλτιστη κατανομή ισχύος εκπομπής στους χρήστες, λαμβάνοντας ταυτόχρονα υπόψη το είδος της υπηρεσίας που αυτοί αιτούνται, αλλά και το επίπεδο της αρχιτεκτονικής του δικτύου στο οποίο ανήκουν. Η έρευνα ολοκληρώνεται με την επίλυση του προβλήματος της συνδυαστικής κατανομής ισχύος εκπομπής και ρυθμού μετάδοσης σε διεπίπεδα φεμτοκυψελωτά ασύρματα δίκτυα με την ταυτόχρονη εξυπηρέτηση πολλαπλών υπηρεσιών

A user-centric economic-driven paradigm for rate allocation in non-orthogonal multiple access wireless systems

Abstract In this paper, a novel approach towards optimizing users’ rate allocation and price customization in a non-orthogonal multiple access (NOMA) wireless network under quality of service (QoS)-differentiated requested services is proposed and studied. A multi-service wireless system is considered, where each user’s QoS requirements are reflected through a utility function, alongside his willingness to pay for the corresponding service. Within this setting, in order to jointly allocate the customized price and rate, a two-variable optimization problem arises. Based on the principles of S-modular theory, the above two-variable (rate and price) optimization problem is modeled and solved as a distributed non-cooperative game. The existence and convergence to the Nash equilibrium point with reference to both user’s uplink transmission rate and price is proven. The proposed approach, allowing for decision-making at the user side, is well aligned with the self-optimization and self-adaptation objectives of future emerging 5G wireless networks. The performance evaluation of the devised framework is conducted via modeling and simulation under various scenarios, and the numerical results clearly demonstrate its superiority against other existing approaches

Centralized and Decentralized Distributed Energy Resource Access Control Implementation Considerations

A global transition to power grids with high penetrations of renewable energy generation is being driven in part by rapid installations of distributed energy resources (DER). New DER equipment includes standardized IEEE 1547-2018 communication interfaces and proprietary communications capabilities. Interoperable DER provides new monitoring and control capabilities. The existence of multiple entities with different roles and responsibilities within the DER ecosystem makes the Access Control (AC) mechanism necessary. In this paper, we introduce and compare two novel architectures, which provide a Role-Based Access Control (RBAC) service to the DER ecosystem’s entities. Selecting an appropriate RBAC technology is important for the RBAC administrator and users who request DER access authorization. The first architecture is centralized, based on the OpenLDAP, an open source implementation of the Lightweight Directory Access Protocol (LDAP). The second approach is decentralized, based on a private Ethereum blockchain test network, where the RBAC model is stored and efficiently retrieved via the utilization of a single Smart Contract. We have implemented two end-to-end Proofs-of-Concept (PoC), respectively, to offer the RBAC service to the DER entities as web applications. Finally, an evaluation of the two approaches is presented, highlighting the key speed, cost, usability, and security features

Risk-Aware Resource Management in Public Safety Networks

Modern Public Safety Networks (PSNs) are assisted by Unmanned Aerial Vehicles (UAVs) to provide a resilient communication paradigm during catastrophic events. In this context, we propose a distributed user-centric risk-aware resource management framework in UAV-assisted PSNs supported by both a static UAV and a mobile UAV. The mobile UAV is entitled to a larger portion of the available spectrum due to its capability and flexibility to re-position itself, and therefore establish better communication channel conditions to the users, compared to the static UAV. However, the potential over-exploitation of the mobile UAV-based communication by the users may lead to the mobile UAV’s failure to serve the users due to the increased levels of interference, consequently introducing risk in the user decisions. To capture this uncertainty, we follow the principles of Prospect Theory and design a user’s prospect-theoretic utility function that reflects user’s risk-aware behavior regarding its transmission power investment to the static and/or mobile UAV-based communication option. A non-cooperative game among the users is formulated, where each user determines its power investment strategy to the two available communication choices in order to maximize its expected prospect-theoretic utility. The existence and uniqueness of a Pure Nash Equilibrium (PNE) is proven and the convergence of the users’ strategies to it is shown. An iterative distributed and low-complexity algorithm is introduced to determine the PNE. The performance of the proposed user-centric risk-aware resource management framework in terms of users’ achievable data rate and spectrum utilization, is achieved via modeling and simulation. Furthermore, its superiority and benefits are demonstrated, by comparing its performance against other existing approaches with regards to UAV selection and spectrum utilization

Multicell Interference Management in Device to Device Underlay Cellular Networks

In this paper, the problem of interference mitigation in a multicell Device to Device (D2D) underlay cellular network is addressed. In this type of network architectures, cellular users and D2D users share common Resource Blocks (RBs). Though such paradigms allow potential increase in the number of supported users, the latter comes at the cost of interference increase that in turn calls for the design of efficient interference mitigation methodologies. To treat this problem efficiently, we propose a two step approach, where the first step concerns the efficient RB allocation to the users and the second one the transmission power allocation. Specifically, the RB allocation problem is formulated as a bilateral symmetric interaction game. This assures the existence of a Nash Equilibrium (NE) point of the game, while a distributed algorithm, which converges to it, is devised. The power allocation problem is formulated as a linear programming problem per RB, and the equivalency between this problem and the total power minimization problem is shown. Finally, the operational effectiveness of the proposed approach is evaluated via numerical simulations, while its superiority against state of the art approaches existing in the recent literature is shown in terms of increased number of supported users, interference reduction and power minimization

Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach

Unmanned Aerial Vehicle (UAV)-assisted Multi-access Edge Computing (MEC) systems have emerged recently as a flexible and dynamic computing environment, providing task offloading service to the users. In order for such a paradigm to be viable, the operator of a UAV-mounted MEC server should enjoy some form of profit by offering its computing capabilities to the end users. To deal with this issue in this paper, we apply a usage-based pricing policy for allowing the exploitation of the servers’ computing resources. The proposed pricing mechanism implicitly introduces a more social behavior to the users with respect to competing for the UAV-mounted MEC servers’ computation resources. In order to properly model the users’ risk-aware behavior within the overall data offloading decision-making process the principles of Prospect Theory are adopted, while the exploitation of the available computation resources is considered based on the theory of the Tragedy of the Commons. Initially, the user’s prospect-theoretic utility function is formulated by quantifying the user’s risk seeking and loss aversion behavior, while taking into account the pricing mechanism. Accordingly, the users’ pricing and risk-aware data offloading problem is formulated as a distributed maximization problem of each user’s expected prospect-theoretic utility function and addressed as a non-cooperative game among the users. The existence of a Pure Nash Equilibrium (PNE) for the formulated non-cooperative game is shown based on the theory of submodular games. An iterative and distributed algorithm is introduced which converges to the PNE, following the learning rule of the best response dynamics. The performance evaluation of the proposed approach is achieved via modeling and simulation, and detailed numerical results are presented highlighting its key operation features and benefits