With the increasing maturity of unmanned aerial vehicles (UAVs), also known as drones, wireless ecosystem is experiencing an unprecedented paradigm shift. These aerial platforms are specifically appealing for a variety of applications due to their rapid and flexible deployment, cost-effectiveness, and high chance of forming line-of-sight (LoS) links to the ground nodes. As with any new technology, the benefits of incorporating UAVs in existing cellular networks cannot be characterized without completely exploring the underlying trade space. This requires a detailed system-level analysis of drone cellular networks by taking the unique features of UAVs into account, which is the main objective of this dissertation. We first focus on a static setup and characterize the performance of a three-dimensional (3D) two-hop cellular network in which terrestrial base stations (BSs) coexist with UAVs to serve a set of ground user equipment (UE). In particular, a UE connects either directly to its serving terrestrial BS by an access link or connects first to its serving UAV which is then wirelessly backhauled to a terrestrial BS (joint access and backhaul). We consider realistic antenna radiation patterns for both BSs and UAVs using practical models developed by the third generation partnership project (3GPP). We assume a probabilistic channel model for the air-to-ground transmission, which incorporates both LoS and non-LoS links. Assuming the max-power association policy, we study the performance of the network in both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols. Using tools from stochastic geometry, we analyze the joint distribution of distance and zenith angle of the closest (and serving) UAV to the origin in a 3D setting. Further, we identify and extensively study key mathematical constructs as the building blocks of characterizing the received signal-to-interference-plus-noise ratio (SINR) distribution. Using these results, we obtain exact mathematical expressions for the coverage probability in both AF and DF relaying protocols. Furthermore, considering the fact that backhaul links could be quite weak because of the downtilted antennas at the BSs, we propose and analyze the addition of a directional uptilted antenna at the BS that is solely used for backhaul purposes. The superiority of having directional antennas with wirelessly backhauled UAVs is further demonstrated via extensive simulations. Second, we turn our attention to a mobile setup and characterize the performance of several canonical mobility models in a drone cellular network in which UAV base stations serve UEs on the ground. In particular, we consider the following four mobility models: (i) straight line (SL), (ii) random stop (RS), (iii) random walk (RW), and (iv) random waypoint (RWP), among which the SL mobility model is inspired by the simulation models used by the 3GPP for the placement and trajectory of UAVs, while the other three are well-known canonical models (or their variants) that offer a useful balance between realism and tractability. Assuming the nearest-neighbor association policy, we consider two service models for the UEs: (i) UE independent model (UIM), and (ii) UE dependent model (UDM). While the serving UAV follows the same mobility model as the other UAVs in the UIM, it is assumed to fly towards the UE of interest in the UDM and hover above its location after reaching there. We then present a unified approach to characterize the point process of UAVs for all the mobility and service models. Using this, we provide exact mathematical expressions for the average received rate and the session rate as seen by the typical UE. Further, using tools from the calculus of variations, we concretely demonstrate that the simple SL mobility model provides a lower bound on the performance of other general mobility models (including the ones in which UAVs follow curved trajectories) as long as the movement of each UAV in these models is independent and identically distributed (i.i.d.). Continuing our analysis on mobile setups, we analyze the handover probability in a drone cellular network, where the initial positions of the UAVs serving the ground UEs are modeled by a homogeneous Poisson point process (PPP). Inspired by the mobility model considered in the 3GPP studies, we assume that all the UAVs follow the SL mobility model, i.e., move along straight lines in random directions. We further consider two different scenarios for the UAV speeds: (i) same speed model (SSM), and (ii) different speed model (DSM). Assuming nearest-neighbor association policy, we characterize the handover probability of this network for both mobility scenarios. For the SSM, we compute the exact handover probability by establishing equivalence with a single-tier terrestrial cellular network, in which the BSs are static while the UEs are mobile. We then derive a lower bound for the handover probability in the DSM by characterizing the evolution of the spatial distribution of the UAVs over time. After performing these system-level analyses on UAV networks, we focus our attention on the air-to-ground wireless channel and attempt to understand its unique features. For that, we first study the impact of UAV wobbling on the coherence time of the wireless channel between UAVs and a ground UE, using a Rician multi-path channel model. We consider two different scenarios for the number of UAVs: (i) single UAV scenario (SUS), and (ii) multiple UAV scenario (MUS). For each scenario, we model UAV wobbling by two random processes, i.e., the Wiener and sinusoidal processes, and characterize the channel autocorrelation function (ACF) which is then used to derive the coherence time of the channel. For the MUS, we further show that the UAV-UE channels for different UAVs are uncorrelated from each other. One key observation that is revealed from our analysis is that even for small UAV wobbling, the coherence time of the channel may degrade quickly, which may make it difficult to track the channel and establish a reliable communication link. Finally, we develop an impairments-aware air-to-ground unified channel model that incorporates the effect of both wobbling and hardware impairments, where the former is caused by random physical fluctuations of UAVs, and the latter by intrinsic radio frequency (RF) nonidealities at both the transmitter and receiver, such as phase noise, in-phase/quadrature (I/Q) imbalance, and power amplifier (PA) nonlinearity. The impact of UAV wobbling is modeled by two stochastic processes, i.e., the canonical Wiener process and the more realistic sinusoidal process. On the other hand, the aggregate impact of all hardware impairments is modeled as two multiplicative and additive distortion noise processes, which is a well-accepted model. For the sake of generality, we consider both wide-sense stationary (WSS) and nonstationary processes for the distortion noises. We then rigorously characterize the ACF of the wireless channel, using which we provide a comprehensive analysis of four key channel-related metrics: (i) power delay profile (PDP), (ii) coherence time, (iii) coherence bandwidth, and (iv) power spectral density (PSD) of the distortion-plus-noise process. Furthermore, we evaluate these metrics with reasonable UAV wobbling and hardware impairment models to obtain useful insights. Similar to our observation above, this work again demonstrates that the coherence time severely degrades at high frequencies even for small UAV wobbling, which renders air-to-ground channel estimation very difficult at these frequencies. / Doctor of Philosophy / With the increasing maturity of unmanned aerial vehicles (UAVs), also known as drones, wireless ecosystem is changing dramatically. Owing to their ease of deployment and high chance of forming direct line-of-sight (LoS) links with the other UAVs and ground users, they are very appealing for numerous wireless applications. As with any new technology, exploring the full extent of the benefits of UAVs requires careful exploration of the underlying trade space. Therefore, in this dissertation, our main focus is on the analysis of such aerial networks, their interplay with the current terrestrial networks, and the unique features of UAVs that make them different from conventional ground nodes. One important aspect of aerial communication systems is their integration into our current cellular networks. Clearly, the addition of these new aerial components has the potential of benefiting both the ground users (such as mobile users watching a concert who need cellular connectivity to share the moments) and the cellular base station (BS). Therefore, careful analysis of these ``aerial-terrestrial" networks is of utmost importance. In the first phase of this dissertation, we perform this analysis by interpreting the network as a combination of one-hop (from the BS to the user) and two-hop (from the BS to the UAV and then from the UAV to the UE) links. Since the locations of BSs, UAVs, and users are irregular in general, we use tools from stochastic geometry to carry out our analysis, which is a field of mathematics that studies random shapes and patterns. Also, because existing terrestrial BSs are primarily designed to serve the ``ground", we propose the addition of a separate set of antennas at the BS site that is solely used to serve the ``air", i.e., to communicate with the UAVs, and demonstrate the benefits of this additional infrastructure in detail. One of our assumptions in the first phase of this dissertation was that the considered network was static, i.e., the UAVs were hovering in the air and the BSs/users were also not moving. In the second phase, on the other hand, we explore the benefits and challenges of a mobile network of UAVs and characterize the performance of several canonical mobility models in a drone cellular network. In particular, one of the models that we studied extensively is the so-called straight line (SL) mobility model, which was inspired by the simulation models used by the third generation partnership project (3GPP) for the placement and trajectory of UAVs. Since the locations of UAVs could be assumed random in general, we use tools from stochastic geometry and present a unified approach to characterize the point process of UAVs, using which we obtained exact mathematical expressions for the average received rate (i.e., throughput) as seen by the users. Continuing our analysis on mobile setups and using the SL mobility model, we also analyze the handover probability in a drone cellular network, which is defined as the event when the serving UAV of a user changes. By establishing equivalence between our aerial setup with a terrestrial cellular network, we compute the exact handover probability in drone cellular networks. In the final phase of this dissertation, we focus our attention on the air-to-ground wireless channel and attempt to understand its unique features. For that, we propose an impairments-aware unified channel model for an air-to-ground wireless communication system and extensively analyze the link between a hovering UAV in the air and a static user on the ground. In particular, we consider two different types of impairments: (i) UAV wobbling, and (ii) hardware impairments, where the former is caused by random physical fluctuations, and the latter by intrinsic radio frequency (RF) nonidealities at both the transmitter and receiver. Using appropriate models for each type of impairment, we rigorously characterize the autocorrelation function (ACF) of the wireless channel, using which we provide a comprehensive analysis of key channel-related metrics, such as coherence time and coherence bandwidth. One key observation that is revealed from our analysis is that even for small UAV wobbling and low hardware impairment levels, the coherence time of the channel may degrade quickly at high frequencies, which could make it difficult to track the channel and establish a reliable communication link at these frequencies.

The proliferation of modern wireless networks increases demand for high capacity and throughput in order to provide faster, more robust, efficient and broadband services to end users. Mobile WiMAX and LTE are examples of such networks in which for some cases they have exposed limited connectivity due to harsh environment. Relay stations are preferred to overcome problems of weak or no access for such network devices, that are placed in specific positions to maintain high quality of data transfer at low cost and provide the required connectivity anywhere anytime. These stations should be equipped with an antenna system capable of establishing communication between base station (backhaul link) and end users (access link). This thesis focuses on the design and development of a new antenna system that is suitable for a relay-based wireless network. Planar geometries of microstrip patch antennas are utilized. The antenna system comprises two antenna modules: a new design of a single antenna for access link and a new design of an antenna array for backhaul link realization. Both antenna specifications are compatible with the IEEE802.16j protocol standard. Hence, relay station should be capable of pointing its radiation pattern to the base station antenna, thus to achieve the desired radiation pattern of the relay station, a new beam-forming module is proposed, designed and developed to generate the proper radiation pattern. The beam-forming module incorporating digital phase shifters and attenuator chips is fabricated and tested. The optimization process using the Least Mean Square (LMS) algorithm is considered in this study to assign the proper phase and amplitude that is necessary to each radiation element excitation current, to produce the desired steered radiation pattern. A comprehensive study on the coupling effects for several relative positions between two new backhaul and access link antenna elements is performed. Two new antenna configurations for coupling reduction are tested and the simulated and measured results in terms of antenna radiation performances were compared and commented.

We address the challenge of providing low-cost, universal access of useful information to people in different parts of the globe. We achieve this by following two strategies. First, we focus on the delivery of information through computerized devices and prototype new methods for making that delivery possible in a secure, low-cost, and universal manner. Second, we focus on the use of participatory media, such as blogs, in the context of news related content, and develop methods to recommend useful information that will be of interest to users. To achieve the first goal, we have designed a low-cost wireless system for Internet access in rural areas, and a smartphone-based system for the opportunistic use of WiFi connectivity to reduce the cost of data transfer on multi-NIC mobile devices. Included is a methodology for secure communication using identity based cryptography. For the second goal of identifying useful information, we make use of sociological theories regarding social networks in mass-media to develop a model of how participatory media can offer users effective news-related information. We then use this model to design a recommender system for participatory media content that pushes useful information to people in a personalized fashion. Our algorithms provide an order of magnitude better performance in terms of recommendation accuracy than other state-of-the-art recommender systems. Our work provides some fundamental insights into the design of low-cost communication systems and the provision of useful messages to users in participatory media through a multi-disciplinary approach. The result is a framework that efficiently and effectively delivers information to people in remote corners of the world.

We address the challenge of providing low-cost, universal access of useful information to people in different parts of the globe. We achieve this by following two strategies. First, we focus on the delivery of information through computerized devices and prototype new methods for making that delivery possible in a secure, low-cost, and universal manner. Second, we focus on the use of participatory media, such as blogs, in the context of news related content, and develop methods to recommend useful information that will be of interest to users. To achieve the first goal, we have designed a low-cost wireless system for Internet access in rural areas, and a smartphone-based system for the opportunistic use of WiFi connectivity to reduce the cost of data transfer on multi-NIC mobile devices. Included is a methodology for secure communication using identity based cryptography. For the second goal of identifying useful information, we make use of sociological theories regarding social networks in mass-media to develop a model of how participatory media can offer users effective news-related information. We then use this model to design a recommender system for participatory media content that pushes useful information to people in a personalized fashion. Our algorithms provide an order of magnitude better performance in terms of recommendation accuracy than other state-of-the-art recommender systems. Our work provides some fundamental insights into the design of low-cost communication systems and the provision of useful messages to users in participatory media through a multi-disciplinary approach. The result is a framework that efficiently and effectively delivers information to people in remote corners of the world.

Multi-standard RF front-end is a critical part of legacy and future emerging mobile architectures, where the size, the efficiency, and the integration of the elements in the RF front-end will affect the network key performance indicators (KPIs). This chapter discusses power amplifier design for both handset and base station applications for 5G and beyond. Also, this chapter deals with filter-antenna design for 5G applications that include a synthesis-based approach, differentially driven reconfigurable planar filter-antenna, and an insensitive phased array antenna with air-filled slot-loop resonators.

Le réseau mobile d’Orange France comprend plus de 100 000 antennes 2G, 3G et 4G sur plusieurs bandes de fréquences sans compter les nombreuses femto-cells fournies aux clients pour résoudre les problèmes de couverture. Ces chiffres ne feront que s’accroître pour répondre à la demande sans cesse croissante des clients pour les données mobiles. Cela illustre le défi énorme que rencontrent les opérateurs de téléphonie mobile en général à savoir gérer un réseau aussi complexe tout en limitant les coûts d’opération pour rester compétitifs. Cette thèse s’attache à utiliser le concept SON (réseaux auto-organisants) pour réduire cette complexité en automatisant les tâches répétitives ou complexes. Plus spécifiquement, nous proposons des algorithmes d’optimisation automatique pour des scénarios liés à la densification par les small cells ou les antennes actives. Nous abordons les problèmes classiques d’équilibrage de charge mais avec un lien backhaul à capacité limitée et de coordination d’interférence que ce soit dans le domaine temporel (notamment avec le eICIC) ou le domaine fréquentiel. Nous proposons aussi des algorithmes d’activation optimale de certaines fonctionnalités lorsque cette activation n’est pas toujours bénéfique. Pour la formulation mathématique et la résolution de tous ces algorithmes, nous nous appuyons sur les résultats de l’approximation stochastique et de l’optimisation convexe. Nous proposons aussi une méthodologie systématique pour la coordination de multiples fonctionnalités SON qui seraient exécutées en parallèle. Cette méthodologie est basée sur les jeux concaves et l’optimisation convexe avec comme contraintes des inégalités matricielles linéaires. / The mobile network of Orange in France comprises more than 100 000 2G, 3G and 4G antennas with severalfrequency bands, not to mention many femto-cells for deep-indoor coverage. These numbers will continue toincrease in order to address the customers’ exponentially increasing need for mobile data. This is an illustrationof the challenge faced by the mobile operators for operating such a complex network with low OperationalExpenditures (OPEX) in order to stay competitive. This thesis is about leveraging the Self-Organizing Network(SON) concept to reduce this complexity by automating repetitive or complex tasks. We specifically proposeautomatic optimization algorithms for scenarios related to network densification using either small cells orActive Antenna Systems (AASs) used for Vertical Sectorization (VeSn), Virtual Sectorization (ViSn) and multilevelbeamforming. Problems such as load balancing with limited-capacity backhaul and interference coordination eitherin time-domain (eICIC) or in frequency-domain are tackled. We also propose optimal activation algorithms forVeSn and ViSn when their activation is not always beneficial. We make use of results from stochastic approximationand convex optimization for the mathematical formulation of the problems and their solutions. We also proposea generic methodology for the coordination of multiple SON algorithms running in parallel using results fromconcave game theory and Linear Matrix Inequality (LMI)-constrained optimization.

By 2020 there will be 50 billion connected devices over the Internet. With the fast-increasing data traffic demand in both fixed and mobile networks, network operators need to migrate networks towards next generation solutions. The network migration requires the enormous investment in equipment and infrastructure, while the revenues are not expected to grow significantly. Therefore, one of the main challenges for network operators is to find out a proper cost-effective optical network solution that can match future high capacity demand and flexibly support multiple network services on a common network infrastructure. The first part of the thesis addresses the Active Optical Network (AON) and its migration strategies towards Next Generation Optical Access (NGOA) solutions. Several migration strategies are proposed from the perspective of network topology, data plane and control plane. A general methodology for Techno-Economic analysis has been developed and applied to the Total Cost of Ownership (TCO) calculation of different NGOA solutions. The thesis provides a complete cost evaluation of AON migration paths, which can be used by network operators to assess the economic feasibility of network migration. A converged Optical Transport Network (OTN) that can serve both fixed and mobile network services is beneficial from the cost-saving perspective. However, the different types of services, require different network performance. The second part of the thesis focuses on the investigation of the converged OTN that can be flexibly and timely adjusted to satisfy varying service conditions. A programmable OTN featured with Wavelength Division Multiplexing (WDM) in the data plane and Software Defined Networking (SDN) in control plane has been proposed. To demonstrate the benefits of the converged OTN, the thesis also provides a multi-domain orchestration architecture for the multiple network services.  The resource orchestration, across three network domains: OTN, mobile network and cloud, enables agile service creation and optimized resource allocation among the multiple domains. / <p>QC 20170512</p>

Abstract This thesis focuses on transceiver optimization for heterogeneous multi-user multiple-input multiple-output (MIMO) wireless communications systems. The aim is to design decentralized beamforming methods with low signaling overhead for improved spatial spectrum utilization. A wide range of transceiver optimization techniques are covered, with particular consideration of decentralized optimization, fast convergence, computational complexity and signaling limitations. The proposed methods are shown to provide improved rate of convergence, when compared to the conventional weighted minimum MSE (WMMSE) approach. This makes them suitable for time-correlated channel conditions, in which the ability to follow the changing channel conditions is essential. Coordinated beamforming under quality of service (QoS) constraints is considered for interfering broadcast channel. Decomposition based decentralized processing approaches are shown to enable the weighted sum rate maximization (WSRMax) in time-correlated channel conditions. Pilot-aided decentralized WSRMax beamformer estimation is studied for coordinated multi-point (CoMP) joint processing (JP). In stream specific estimation (SSE), all effective channels are individually estimated. The beamformers are then constructed from the locally estimated channels. On the other hand, with direct estimation (DE) of the beamformers, only the intended signal needs to be separately estimated and the covariance matrices are implicitly estimated from the received pilot training matrices. This makes the pilot design more robust to pilot contamination. These methods show that CoMP JP is feasible even in relatively fading channel conditions and with limited backhaul capacity by employing decentralized beamformer processing. In the final part of the thesis, a relay-assisted cellular system with decentralized processing is considered, in which users are served either directly by the base stations or via relays for WSRMax or sum power minimization subject to rate constraints. Zero-forcing and coordinated beamforming provide a trade-off between complexity, in-band signaling and spectrum utilization. Relays are shown to be beneficial in many scenarios when the in-band signaling is accounted for. This thesis shows that decentralized downlink MIMO transceiver design with a reasonable computational complexity is feasible in various system architectures even when signaling resources are limited and channel conditions are moderately fast fading. / Tiivistelmä Tämä väitöskirja keskittyy lähetin- ja vastaanotinoptimointiin heterogeenisissä monikäyttäjä- ja moniantennijärjestelmissä. Tavoitteena on parantaa tilatason suorituskykyä tutkimalla hajautettuja keilanmuodostusmenetelmiä, joissa ohjaussignaloinnin tarve on alhainen. Erityisesti keskitytään hajautetun keilanmuodostuksen optimointiin, nopeaan konvergenssiin, laskennalliseen kompleksisuuteen sekä signaloinnin rajoitteisiin. Esitettyjen menetelmien osoitetaan parantavan konvergenssinopeutta ja vähentävän signaloinnin tarvetta, verrattaessa tunnettuun WMMSE-menetelmään. Nämä mahdollistavat lähetyksen aikajatkuvissa kanavissa, joissa kanavan muutosten seuraaminen on erityisen tärkeää. Näiden menetelmien osoitetaan mahdollistavan hajautetun ja priorisoidun tiedonsiirtonopeuden maksimoinnin monisolujärjestelmissä sekä aikajatkuvissa kanavissa käyttäjäkohtaisilla siirtonopeustakuilla. Pilottiavusteisten lähetys- ja vastaanotinkeilojen estimointia tutkitaan yhteislähetysjärjestelmissä. Yksittäisten lähetyskanavien estimoinnissa effektiiviset kanavat estimoidaan yksitellen, ja lähetys- ja vastaanotinkovarianssimatriisit muodostetaan summaamalla paikalliset kanavaestimaatit. Suoraestimoinnissa ainoastaan oman käyttäjän effektiivinen kanava estimoimaan erikseen. Tällöin kovarianssimatriisit saadaan suoraan vastaanotetuista pilottisignaaleista. Tämä tekee estimaateista vähemmän herkkiä häiriölle. Hajautetun yhteislähetyksen osoitetaan olevan mahdollista, jopa verrattain nopeasti muuttuvissa kanavissa sekä rajallisella verkkoyhteydellä lähettimien välillä. Viimeisessä osassa tutkitaan välittäjä-avusteisia järjestelmiä, joissa käyttäjiä palvellaan joko suoraan tukiasemasta tai välittäjä-aseman kautta. Optimointikriteereinä käytetään siirtonopeuden maksimointia sekä lähetystehon minimointia siirtonopeustakuilla. Nollaanpakottava sekä koordinoitu keilanmuodostus tarjoavat valinna laskennallisen kompleksisuuden, ohjaussignaloinnin sekä suorituskyvyn välillä. Välittäjä-avusteisen lähetyksen osoitetaan olevan hyödyllisiä useissa tilanteissa, kun radiorajanpinnan yli tapahtuvan signaloinnin tarve otetaan huomioon keilanmuodostuksessa. Tässä väitöskirjassa osoitetaan hajautetun keilanmuodostuksen olevan mahdollista verrattaen vähäisillä laskennallisilla resursseilla heterogeenisissä moniantennijärjestelmissä. Esitetyt menetelmät tarjoavat ratkaisuja järjestelmiin, joissa ohjaussignalointiresurssit ovat rajallisia ja radiokanava on jatkuvasti muuttuva.

Abstract This thesis focuses on the design of coordinated downlink beamforming techniques for wireless multi-cell multi-user multi-antenna systems. In particular, cellular and cognitive radio networks are considered. In general, coordinated beamforming schemes aim to improve system performance, especially at the cell-edge area, by controlling inter-cell interference. In this work, special emphasis is put on practical coordinated beamforming designs that can be implemented in a decentralized manner by relying on local channel state information (CSI) and low-rate backhaul signaling. The network design objective is the sum power minimization (SPMin) of base stations (BSs) while providing the guaranteed minimum rate for each user. Decentralized coordinated beamforming techniques are developed for cellular multi-user multiple-input single-output (MISO) systems. The proposed iterative algorithms are based on classical primal and dual decomposition methods. The SPMin problem is decomposed into two optimization levels, i.e., BS-specific subproblems for the beamforming design and a network-wide master problem for the inter-cell interference coordination. After the acquisition of local CSI, each BS can independently compute its transmit beamformers by solving the subproblem via standard convex optimization techniques. Interference coordination is managed by solving the master problem via a traditional subgradient method that requires scalar information exchange between the BSs. The algorithms make it possible to satisfy the user-specific rate constraints for any iteration. Hence, delay and signaling overhead can be reduced by limiting the number of performed iterations. In this respect, the proposed algorithms are applicable to practical implementations unlike most of the existing decentralized approaches. The numerical results demonstrate that the algorithms provide significant performance gains over zero-forcing beamforming strategies. Coordinated beamforming is also studied in cellular multi-user multiple-input multiple-output (MIMO) systems. The corresponding non-convex SPMin problem is divided into transmit and receive beamforming optimization steps that are alternately solved via successive convex approximation method and the linear minimum mean square error criterion, respectively, until the desired level of convergence is attained. In addition to centralized design, two decentralized primal decomposition-based algorithms are proposed wherein the transmit and receive beamforming designs are facilitated by a combination of pilot and backhaul signaling. The results show that the proposed MIMO algorithms notably outperform the MISO ones. Finally, cellular coordinated beamforming strategies are extended to multi-user MISO cognitive radio systems, where primary and secondary networks share the same spectrum. Here, network optimization is performed for the secondary system with additional interference constraints imposed for the primary users. Decentralized algorithms are proposed based on primal decomposition and an alternating direction method of multipliers. / Tiivistelmä Tämä väitöskirja keskittyy yhteistoiminnallisten keilanmuodostustekniikoiden suunnitteluun langattomissa monisolu- ja moniantennijärjestelmissä, erityisesti solukko- ja kognitiiviradioverkoissa. Yhteistoiminnalliset keilanmuodostustekniikat pyrkivät parantamaan verkkojen suorituskykyä kontrolloimalla monisoluhäiriötä, erityisesti tukiasemasolujen reuna-alueilla. Tässä työssä painotetaan erityisesti käytännöllisten yhteistoiminnallisten keilanmuodostustekniikoiden suunnittelua, joka voidaan toteuttaa hajautetusti perustuen paikalliseen kanavatietoon ja tukiasemien väliseen informaationvaihtoon. Verkon suunnittelutavoite on minimoida tukiasemien kokonaislähetysteho samalla, kun jokaiselle käyttäjälle taataan tietty vähimmäistiedonsiirtonopeus. Hajautettuja yhteistoiminnallisia keilanmuodostustekniikoita kehitetään moni-tulo yksi-lähtö -solukkoverkoille. Oletuksena on, että tukiasemat ovat varustettuja monilla lähetysantenneilla, kun taas päätelaitteissa on vain yksi vastaanotinantenni. Ehdotetut iteratiiviset algoritmit perustuvat klassisiin primaali- ja duaalihajotelmiin. Lähetystehon minimointiongelma hajotetaan kahteen optimointitasoon: tukiasemakohtaisiin aliongelmiin keilanmuodostusta varten ja verkkotason pääongelmaan monisoluhäiriön hallintaa varten. Paikallisen kanavatiedon hankkimisen jälkeen jokainen tukiasema laskee itsenäisesti lähetyskeilansa ratkaisemalla aliongelmansa käyttäen apunaan standardeja konveksioptimointitekniikoita. Monisoluhäiriötä kontrolloidaan ratkaisemalla pääongelma käyttäen perinteistä aligradienttimenetelmää. Tämä vaatii tukiasemien välistä informaationvaihtoa. Ehdotetut algoritmit takaavat käyttäjäkohtaiset tiedonsiirtonopeustavoitteet jokaisella iterointikierroksella. Tämä mahdollistaa viiveen pienentämisen ja tukiasemien välisen informaatiovaihdon kontrolloimisen. Tästä syystä ehdotetut algoritmit soveltuvat käytännön toteutuksiin toisin kuin useimmat aiemmin ehdotetut hajautetut algoritmit. Numeeriset tulokset osoittavat, että väitöskirjassa ehdotetut algoritmit tuovat merkittävää verkon suorituskyvyn parannusta verrattaessa aiempiin nollaanpakotus -menetelmiin. Yhteistoiminnallista keilanmuodostusta tutkitaan myös moni-tulo moni-lähtö -solukkoverkoissa, joissa tukiasemat sekä päätelaitteet ovat varustettuja monilla antenneilla. Tällaisessa verkossa lähetystehon minimointiongelma on ei-konveksi. Optimointiongelma jaetaan lähetys- ja vastaanottokeilanmuodostukseen, jotka toistetaan vuorotellen, kunnes algoritmi konvergoituu. Lähetyskeilanmuodostusongelma ratkaistaan peräkkäisillä konvekseilla approksimaatioilla. Vastaanottimen keilanmuodostus toteutetaan summaneliövirheen minimoinnin kautta. Keskitetyn algoritmin lisäksi tässä työssä kehitetään myös kaksi hajautettua algoritmia, jotka perustuvat primaalihajotelmaan. Hajautettua toteutusta helpotetaan pilottisignaloinnilla ja tukiasemien välisellä informaationvaihdolla. Numeeriset tulokset osoittavat, että moni-tulo moni-lähtö -tekniikoilla on merkittävästi parempi suorituskyky kuin moni-tulo yksi-lähtö -tekniikoilla. Lopuksi yhteistoiminnallista keilanmuodostusta tarkastellaan kognitiiviradioverkoissa, joissa primaari- ja sekundaarijärjestelmät jakavat saman taajuuskaistan. Lähetystehon optimointi suoritetaan sekundaariverkolle samalla minimoiden primaarikäyttäjille aiheuttamaa häiriötä. Väitöskirjassa kehitetään kaksi hajautettua algoritmia, joista toinen perustuu primaalihajotelmaan ja toinen kerrointen vaihtelevan suunnan menetelmään.