Degrees of Freedom of Full-Duplex Multiantenna Cellular Networks

We study the degrees of freedom (DoF) of cellular networks in which a full duplex (FD) base station (BS) equipped with multiple transmit and receive antennas communicates with multiple mobile users. We consider two different scenarios. In the first scenario, we study the case when half duplex (HD) users, partitioned to either the uplink (UL) set or the downlink (DL) set, simultaneously communicate with the FD BS. In the second scenario, we study the case when FD users simultaneously communicate UL and DL data with the FD BS. Unlike conventional HD only systems, inter-user interference (within the cell) may severely limit the DoF, and must be carefully taken into account. With the goal of providing theoretical guidelines for designing such FD systems, we completely characterize the sum DoF of each of the two different FD cellular networks by developing an achievable scheme and obtaining a matching upper bound. The key idea of the proposed scheme is to carefully allocate UL and DL information streams using interference alignment and beamforming techniques. By comparing the DoFs of the considered FD systems with those of the conventional HD systems, we establish the DoF gain by enabling FD operation in various configurations. As a consequence of the result, we show that the DoF can approach the two-fold gain over the HD systems when the number of users becomes large enough as compared to the number of antennas at the BS.Comment: 21 pages, 16 figures, a shorter version of this paper has been submitted to the IEEE International Symposium on Information Theory (ISIT) 201

Improving decision making for incentivised and weather-sensitive projects

The field of project management has originated from the domain of operational research, which focuses on the mathematical optimization of operational problems. However, in recent decades an increasingly broad perspective has been applied to the field of project management. As such, project management has spawned a number of very active sub- domains, which focus not solely on the scheduling of the project’s baseline, but also on the analysis of risk, as well as the controlling of project execution. This dissertation focuses on two areas where existing literature is still lacking. The first area is the use of incentivised contractual agreements between the owner of a project, and the contractor who is hired to execute the project. Whereas this area has received growing attention in recent years, the majority of studies remained strongly descriptive. Hence, the aim of the first part of this dissertation is to develop a more prescriptive approach from both the owner’s and the contractor’s perspective. The second part of this dissertation investigates the use of dedicated weather models to improve operational performance of weather-sensitive projects. During recent decades, significant effort has been made to improve the quality of weather simulation models. Moreover, the amount of available weather data has been steadily increasing. This opens up a lot of new possibilities for using more precise weather models in order to support operational decision making. In spite of this, the number of applications of these weather models in operational research has remained rather limited. As such, the aim of the second part of this dissertation is to leverage these weather models to improve the scheduling of offshore construction projects, as well as preventive maintenance of offshore wind turbines

A column generation algorithm for disrupted airline schedules

We consider the recovery of an airline schedule after an unforeseen event, called {\em disruption}, that makes the planned schedule unfeasible. In particular we consider the aircraft recovery problem for a heterogeneous fleet of aircrafts, made of regular and reserve planes, where the aircrafts' maintenances are planned in an optimal way in order to satisfy the operational regulations. We propose a column generation scheme, where the pricing problem is modeled as a commodity flow problem on a dedicated network, one for each plane of the fleet. We present a dynamic programming algorithm to build the underlying networks and a dynamic programming algorithm for resource constrained elementary shortest paths to solve the pricing problem. We provide some computational results on real world instances

Allocation of Communication and Computation Resources in Mobile Networks

Konvergence komunikačních a výpočetních technologií vedlo k vzniku Multi-Access Edge Computing (MEC). MEC poskytuje výpočetní výkon na tzv. hraně mobilních sítí (základnové stanice, jádro mobilní sítě), který lze využít pro optimalizaci mobilních sítí v reálném čase. Optimalizacev reálném čase je umožněna díky nízkému komunikačnímu zpoždění například v porovnání s Mobile Cloud Computing (MCC). Optimalizace mobilních sítí vyžaduje informace o mobilní síti od uživatelských zařízeních, avšak sběr těchto informací využívá komunikační prostředky, které jsou využívány i pro přenos uživatelských dat. Zvyšující se počet uživatelských zařízení, senzorů a taktéž komunikace vozidel tvoří překážku pro sběr informací o mobilních sítích z důvodu omezeného množství komunikačních prostředků. Tudíž je nutné navrhnout řešení, která umožní sběr těchto informací pro potřeby optimalizace mobilních sítí. V této práci je navrženo řešení pro komunikaci vysokého počtu zařízeních, které je postaveno na využití přímé komunikace mezi zařízeními. Pro motivování uživatelů, pro využití přeposílání dat pomocí přímé komunikace mezi uživateli je navrženo přidělování komunikačních prostředků jenž vede na přirozenou spolupráci uživatelů. Dále je provedena analýza spotřeby energie při využití přeposílání dat pomocí přímé komunikace mezi uživateli pro ukázání jejích výhod z pohledu spotřeby energie. Pro další zvýšení počtu komunikujících zařízení je využito mobilních létajících základových stanic (FlyBS). Pro nasazení FlyBS je navržen algoritmus, který hledá pozici FlyBS a asociaci uživatel k FlyBS pro zvýšení spokojenosti uživatelů s poskytovanými datovými propustnostmi. MEC lze využít nejen pro optimalizaci mobilních sítí z pohledu mobilních operátorů, ale taktéž uživateli mobilních sítí. Tito uživatelé mohou využít MEC pro přenost výpočetně náročných úloh z jejich mobilních zařízeních do MEC. Z důvodu mobility uživatel je nutné nalézt vhodně přidělení komunikačních a výpočetních prostředků pro uspokojení uživatelských požadavků. Tudíž je navržen algorithmus pro výběr komunikační cesty mezi uživatelem a MEC, jenž je posléze rozšířen o přidělování výpočetných prostředků společně s komunikačními prostředky. Navržené řešení vede k snížení komunikačního zpoždění o desítky procent.The convergence of communication and computing in the mobile networks has led to an introduction of the Multi-Access Edge Computing (MEC). The MEC combines communication and computing resources at the edge of the mobile network and provides an option to optimize the mobile network in real-time. This is possible due to close proximity of the computation resources in terms of communication delay, in comparison to the Mobile Cloud Computing (MCC). The optimization of the mobile networks requires information about the mobile network and User Equipment (UE). Such information, however, consumes a significant amount of communication resources. The finite communication resources along with the ever increasing number of the UEs and other devices, such as sensors, vehicles pose an obstacle for collecting the required information. Therefore, it is necessary to provide solutions to enable the collection of the required mobile network information from the UEs for the purposes of the mobile network optimization. In this thesis, a solution to enable communication of a large number of devices, exploiting Device-to-Device (D2D) communication for data relaying, is proposed. To motivate the UEs to relay data of other UEs, we propose a resource allocation algorithm that leads to a natural cooperation of the UEs. To show, that the relaying is not only beneficial from the perspective of an increased number of UEs, we provide an analysis of the energy consumed by the D2D communication. To further increase the number of the UEs we exploit a recent concept of the flying base stations (FlyBSs), and we develop a joint algorithm for a positioning of the FlyBS and an association of the UEs to increase the UEs satisfaction with the provided data rates. The MEC can be exploited not only for processing of the collected data to optimize the mobile networks, but also by the mobile users. The mobile users can exploit the MEC for the computation offloading, i.e., transferring the computation from their UEs to the MEC. However, due to the inherent mobility of the UEs, it is necessary to determine communication and computation resource allocation in order to satisfy the UEs requirements. Therefore, we first propose a solution for a selection of the communication path between the UEs and the MEC (communication resource allocation). Then, we also design an algorithm for joint communication and computation resource allocation. The proposed solution then lead to a reduction in the computation offloading delay by tens of percent

Hierarchical decision making with supply chain applications

Hierarchical decision making is a decision system, where multiple decision makers are involved and the process has a structure on the order of levels. It gains interest not only from a theoretical point of view but also from real practice. Its wide applications in supply chain management are the main focus of this dissertation.The first part of the work discusses an application of continuous bilevel programming in a remanufacturing system. Under intense competitive pressures to lower production costs, coupled with increasing environmental concerns, used products can often be collected via customer returns to retailers in supply chains and remanufactured by producers, in orderto bring them back into “as-new” condition for resale. In this part, hierarchical models are developed to determine optimal decisions involving inventory replenishment, retail pricingand collection price for returns. Based on the simplified assumption of a single manufacturer and a single retailer dealing with a single recoverable item under deterministic conditions,all of these decisions are examined in an integrated manner. Models depicting decentralized, as well as centralized policies are explored. Analytical results are derived and detailed sensitivity analysis is performed via an extensive set of numerical computations.In the second part of this dissertation, a discrete bilevel problem is illustrated by investigating a biofuel production problem. The issues of governmental incentives, industry decisions of price, and farm management of land are incorporated. While fixed costs are natural components of decision making in operations management, such discrete phenomena have not received sufficient research attention in the current literature on bilevel programming, due to a variety of theoretical and algorithmic difficulties. When such costs are taken into account, it is not easy to derive optimality conditions and explore convergence properties due to discontinuities and the combinatorial nature of this problem, which is NP-hard. In order to solve this problem, a derivative-free search technique is used to arrive at a solution to this bilevel problem. A new heuristic methodology is developed, which integrates sensitivity analysis and warm-starts to improve the efficiency of the algorithm.Ph.D., Decision Sciences -- Drexel University, 201

Publications of the Jet Propulsion Laboratory, 1979

This bibliography includes 1004 technical reports, released during calendar year 1979, that resulted from scientific and engineering work performed, or managed, by the Jet Propulsion Laboratory. Three classes of publications are included: (1) JPL Publications; (2) articles published in the open literature; and (3) articles from the bimonthly Deep Space Network Progress Report. The publications are indexed by: (1) author, (2) subject, and (3) publication type and number. A descriptive entry appears under the name of each author of each publication; an abstract is included with the entry for the primary (first listed) author. Unless designated otherwise, all publications listed are unclassified

Combining robustness and recovery for airline schedules

In this thesis, we address different aspects of the airline scheduling problem. The main difficulty in this field lies in the combinatorial complexity of the problems. Furthermore, as airline schedules are often faced with perturbations called disruptions (bad weather conditions, technical failures, congestion, crew illness…), planning for better performance under uncertainty is an additional dimension to the complexity of the problem. Our main focus is to develop better schedules that are less sensitive to perturbations and, when severe disruptions occur, are easier to recover. The former property is known as robustness and the latter is called recoverability. We start the thesis by addressing the problem of recovering a disrupted schedule. We present a general model, the constraint-specific recovery network, that encodes all feasible recovery schemes of any unit of the recovery problem. A unit is an aircraft, a crew member or a passenger and its recovery scheme is a new route, pairing or itinerary, respectively. We show how to model the Aircraft Recovery Problem (ARP) and the Passenger Recovery Problem (PRP), and provide computational results for both of them. Next, we present a general framework to solve problems subject to uncertainty: the Uncertainty Feature Optimization (UFO) framework, which implicitly embeds the uncertainty the problem is prone to. We show that UFO is a generalization of existing methods relying on explicit uncertainty models. Furthermore, we show that by implicitly considering uncertainty, we not only save the effort of modeling an explicit uncertainty set: we also protect against possible errors in its modeling. We then show that combining existing methods using explicit uncertainty characterization with UFO leads to more stable solutions with respect to changes in the noise's nature. We illustrate these concepts with extensive simulations on the Multi-Dimensional Knapsack Problem (MDKP). We then apply the UFO to airline scheduling. First, we study how robustness is defined in airline scheduling and then compare robustness of UFO models against existing models in the literature. We observe that the performance of the solutions closely depend on the way the performance is evaluated. UFO solutions seem to perform well globally, but models using explicit uncertainty have a better potential when focusing on a specific metric. Finally, we study the recoverability of UFO solutions with respect to the recovery algorithm we develop. Computational results on a European airline show that UFO solutions are able to significantly reduce recovery costs

Application of parameter estimation to aircraft stability and control: The output-error approach

The practical application of parameter estimation methodology to the problem of estimating aircraft stability and control derivatives from flight test data is examined. The primary purpose of the document is to present a comprehensive and unified picture of the entire parameter estimation process and its integration into a flight test program. The document concentrates on the output-error method to provide a focus for detailed examination and to allow us to give specific examples of situations that have arisen. The document first derives the aircraft equations of motion in a form suitable for application to estimation of stability and control derivatives. It then discusses the issues that arise in adapting the equations to the limitations of analysis programs, using a specific program for an example. The roles and issues relating to mass distribution data, preflight predictions, maneuver design, flight scheduling, instrumentation sensors, data acquisition systems, and data processing are then addressed. Finally, the document discusses evaluation and the use of the analysis results

Cooperative diversity techniques for high-throughput wireless relay networks

Relay communications has attracted a growing interest in wireless communications with application to various enhanced technologies. This thesis considers a number of issues related to data throughput in various wireless relay network models. Particularly, new implementations of network coding (NC) and space-time coding (STC) techniques are investigated to offer various means of achieving high-throughput relay communications. Firstly, this thesis investigates different practical automatic repeat request (ARQ) retransmission protocols based on NC for two-way wireless relay networks to improve throughput efficiency. Two improved NC-based ARQ schemes are designed based on go-back-N and selective-repeat (SR) protocols. Addressing ARQ issues in multisource multidestination relay networks, a new NC-based ARQ protocol is proposed and two packet-combination algorithms are developed for retransmissions at relay and sources to significantly improve the throughput. In relation to the concept of channel quality indicator (CQI) reporting in two-way relay networks, two new efficient CQI reporting schemes are designed based on NC to improve the system throughput by allowing two terminals to simultaneously estimate the CQI of the distant terminal-relay link without incurring additional overhead. The transmission time for CQI feedback at the relays is reduced by half while the increase in complexity and the loss of performance are shown to be negligible. Furthermore, a low-complexity relay selection scheme is suggested to reduce the relay searching complexity. For the acknowledgment (ACK) process, this thesis proposes a new block ACK scheme based on NC to significantly reduce the ACK overheads and therefore produce an enhanced throughput. The proposed scheme is also shown to improve the reliability of block ACK transmission and reduce the number of data retransmissions for a higher system throughput. Additionally, this thesis presents a new cooperative retransmission scheme based on relay cooperation and NC to considerably reduce the number of retransmission packets and im- prove the reliability of retransmissions for a more power efficient and higher throughput system with non-overlapped retransmissions. Moreover, two relay selection schemes are recommended to determine the optimised number of relays for the retransmission. Finally, with respect to cognitive wireless relay networks (CWRNs), this thesis proposes a new cooperative spectrum sensing (CSS) scheme to improve the spectrum sensing performance and design a new CSS scheme based on NC for three-hop CWRNs to improve system throughput. Furthermore, a new distributed space-time-frequency block code (DSTFBC) is designed for a two- hop nonregenerative CWRN over frequency-selective fading channels. The proposed DSTFBC design achieves higher data rate, spatial diversity gain, and decoupling detection of data blocks at all destination nodes with a low-complexity receiver structure