Las redes inal´ambricas actuales exhiben caracter´ısticas heterog´eneas de acceso m´ultiple mediante el despliegue, la coexistencia y la cooperaci´on de varias Tecnolog ´ıas de Acceso Radio (RAT2). En este escenario, la prestaci´on de servicios multimedia garantizando una cierta calidad de servicio (QoS3) es obligatoria. El objetivo global de las redes heterog´eneas de acceso inal´ambrico consiste en sustentar la realizaci´on del concepto ABC (del ingl´es Always Best Connected), en el que un usuario est´a siempre conectado a la RAT que mejor satisface sus necesidades de servicio en cualquier momento, en cualquier lugar, de cualquier modo. En este sentido, las estrat´egias de gesti´on de recursos radio comunes [del ingl´es, Common Radio Resource Management (CRRM)] se dise˜nan para proporcionar una utilizaci´on eficiente de los recursos radio y de espectro radioel´ectrico dentro de la red heterog´enea, ofreciendo un mejor rendimiento en comparaci´on con la realizaci´on independiente de RRM en cada RAT. Adem´as, los recursos de espectro asignados a cada una de las RATs deben ser utilizado de manera eficiente, ya que se trata de un recurso escaso y costoso. En este sentido, conceptos y metodolog´ıas de radio cognitiva (del ingl´es Cognitive Radio o CR) se han aplicado a la gesti´on del espectro, permitiendo una compartici´on dinamico-oportunista del mismo. En estos casos, el espectro sujeto a licencia se abre hacia el acceso de usuarios sin licencia siempre que no perjudiquen y que el funcionamiento libre de interferencias est´e garantizado. Esta tesis analiza estrategias de gesti´on de recursos radio y de espectro para ofrecer un uso mayor y eficiente de los escasos recursos radio y de espectro con el objetivo final de aumentar al m´aximo la capacidad de usuario, garantizando los requerimientos de QoS. En concreto, estas tesis se centra primero en como seleccionar una RAT al inicio de una llamada/sesi´on (en adelante, selecci´on inicial de RAT) en una red de acceso heterog´enea. Un modelo de Markov ha sido desarrollado para definir la asignaci´on de m´ultiples servicios (multi-servicio) en m´ultiples RATs (multi-acceso). En este marco, varias pol´ıticas de selecci´on de RAT son propuestas y evaluadas, gen´ericamente clasific´andose en pol´ıticas basadas en servicio (SB4) y basadas en balanceo de carga (LB5). Adem´as, el rendimiento de las pol´ıticas de selecci´on de RATs en escenarios de acceso limitado debido a la deficiente cobertura radio, la falta de disponibilidad de terminales multi-modo y la incompatibilidad entre RAT y servicios tambi´en es evaluada. Principios espec´ıficos para la asignaci´on de servicios a RATs ser´an provistos en los escenarios antes mencionados con el objetivo general de aumentar la capacidad de usuarios, garantizando los requisitos m´ınimos de calidad de servicio. Finalmente, la congesti´on en el acceso radio tambi´en se trata en este escenario multi-acceso/multi-servicio y el impacto de la selecci´on de RAT evaluado. Los principios para la asignaci´on inicial de RAT con tal de evitar la congesti´on radio ser´an tambi´en proporcionados. En segundo lugar, esta tesis investiga sobre la forma de maximizar el uso eficiente del espectro sujeto a licencia (o licenciado) por medio del acceso din´amicooportunista de espectro a usuarios sin licencia. En este sentido, se concibe un modelo de Markov para captar el problema del uso compartido de espectro entre usuarios con y sin licencia. Un modelo basado en sensado de espectro se propone con el fin de detectar porciones de espectro no utilizados (en ingl´es white spaces) que pueden ser usados por los usuarios sin licencia mientras este siga libre. En este marco, los beneficios obtenidos de la compartici´on del espectro son investigados y las ventajas que implican evaluadas. En concreto, se eval´ua el rendimiento obtenido al ajustar el punto de funcionamiento (en ingl´es operating point ) del mecanismo de sensado, el cual determina los errores de no-detecci´on y falsa-alarma. Por otra parte, sistemas de canalizaci´on de espectro fijos versus adaptativos ser´an propuestos y analizados bajo dos disciplinas de servicio diferentes, cuya duraci´on (o tiempo de permanencia en el sistema) esta basada en tiempo y en contenido respectivamente. / Current wireless networks exhibit heterogeneous multi-access features by means of the coexisting and cooperative deployment of several Radio Access Technologies (RATs). In this scenario, the provision of multimedia services with ensured Quality of Service (QoS) is mandatory. The overall goal of heterogeneous wireless access networks is to enable the realization of the Always Best Connected concept in which a user is seamlessly connected to the RAT best suiting its service requirements anytime, anywhere, anyhow. In this sense, Common Radio Resource Management (CRRM) strategies are devoted to provide an efficient utilization of radio resources within the heterogeneous network offering improved performances as opposed to performing stand-alone RRM in each RAT. In addition, allocated spectrum resources to each RAT must be efficiently utilized since it is a scarce and expensive resource. In this respect, cognitive radio concepts and methodologies have been applied to spectrum management by enabling dynamic/opportunistic spectrum sharing. In these scenarios, licensed spectrum is opened towards unlicensed access provided a non-harmful operation is guaranteed. This dissertation discusses both radio resource and spectrum management strategies to provide an utmost and efficient use of scarce radio/spectrum resources with the overall goal of maximizing user capacity while guaranteeing QoS constraints.Specifically, the thesis is first focused on how to select an appropriate RAT upon call/session initiation (henceforth, initial RAT selection) in a heterogeneous access network. A Markovian framework is developed to such extent supporting the allocation of multiple service-type users (multi-service) on multiple RATs (multi-access). Under this framework, several RAT selection policies are proposed and evaluated, broadly categorized into service-based (SB) and load-balancing (LB). In addition, the performance of RAT selection policies in access-limited scenarios due to poor radio coverage, non multi-mode terminal availability and RAT-service incompatibility is also evaluated. Specific guiding principles for the allocation of services on several RATs are provided in the abovementioned scenarios with the overall goal of increasing user capacity while guaranteeing minimum QoS requirements. Finally, radio access congestion is also addressed in this multi-access/multi-service scenario and the impact RAT selection assessed. Suitable allocation principles avoiding congestion are also provided.Secondly, this dissertation investigates on how to efficiently maximize the use of licensed spectrum by means of dynamic/opportunistic unlicensed spectrum access. Hereof, a Markovian framework is also devised to capture the problem of licensed spectrum sharing towards unlicensed users. A sensing-based spectrum awareness model is proposed in order to detect unused spectrum (so-called white spaces) which may be accessed by unlicensed users while remaining unused. Under this framework, the benefits of spectrum sharing are investigated and the involved gains assessed. Specifically, the sensing-throughput tradeoff and the adjustment of the sensing mechanism’s operating point, which tradeoffs missed-detection and false-alarm errors, is evaluated. Moreover, fixed vs. adaptive spectrum channelization schemes are proposed and analyzed under two different service disciplines considering time-based and volume-based content delivery.

<p>The traditional way of increasing capacity in a wirelesscommunication system has been cell splitting and fixedchannel-allocation based on prediction tools. However, theplanning complexity increases rapidly with the number of cellsand the method is not suitable for the large temporal andspatial traffic variations expected in the future. A lot ofresearch has therefore been performed regarding adaptivechannel allocation, where a channel can be used anywhere aslong as the signal-to-interference ratio (SIR) is acceptable. Acommon opinion is that these solutions must be decentralizedsince a centralized one would be overly complex.</p><p>In this thesis, we study the locally centralized<i>bunch concept</i>for radio resource management (RRM) in aManhattan environment and show that it can give a very highcapacity both for outdoor users and for indoor users covered byoutdoor base stations. We show how measurement limitations anderrors affect the performance and wepropose methods to handlethese problems, e.g. averaging of measured values, robustchannel selection algorithms, and increased SIR margins. Wealso study the computational and signaling complexities andshow that they can be reduced by splitting large bunches, usingsparse matrix calculations, and by using a simplified admissionalgorithm. However, a reduction of the complexity often means areduction of the system capacity.</p><p>The measurements needed for RRM can also be used to find amobile terminal's geographical position. We propose and studysome simple yet accurate methods for this purpose. We alsostudy if position information can enhance RRM as is oftensuggested in the literature. In the studied scenario, thisinformation seems to be of limited use. One possible use is toestimate the mobile user's speed, to assist handover decisions.Another use is to find the location of user hotspots in anarea, which is beneficial for system planning.</p><p>Our results show that the bunch concept is a promisingcandidate for radio resource management in future wirelesssystems. We believe that the complexity is manageable and themain price we have to pay for high capacity is frequentreallocation of connections.</p><p><b>Keywords:</b>bunch concept, radio resource management,network-assisted resource management, base station selection,dynamic channel allocation, DCA, channel selection,least-interfered, interference avoidance, interferenceaveraging, handover, power control, path-loss measurements,signal strength, link-gain matrix, TD-CDMA, UTRA TDD, Manhattanscenario, microcells, mobile positioning, position accuracy,trilateration, triangulation, speed estimation</p>

D. Tech. Electrical Engineering. / Objectives of the study is to propose a suitable feature extraction and classication approach that is capable of adapting to the non-linear nature and the noise contained in the time series data. The end goal of subscriber classication in this study is to utilise the subscriber information extracted for a new radio resource optimisation model that focuses on the Channel Allocation Problem CAP. Although there they have been various models proposed in literature for solving of the CAP problem, the utilisation of subscriber related information in the CAP has not been directly considered.

The world of information technology and communications is in a stage of continuous improvement. These new developments are accompanied by a very rapid data traffic growth, particularly for mobile wireless networks. An important effect is the increase of the consumed energy by the network, particularly the radio access section, i.e. the base station systems. This latter issue causes that operational costs associated to energy consumption become more significant for telecommunication operators. In addition to the question of the availability of energy, this problem has an ecological aspect, due to the CO2 emissions associated with the operation of the network but also an issue related to public health given the effects of electromagnetic radiation from wireless transmission. For these reasons, great research efforts in the so-called field of Green Radio are being done in the recent years. The aim of this thesis consisted of finding ways to reduce the energy consumption in wireless and mobile networks respecting the QoS levels assigned to users. After a study of the state of the art analysing the possible approaches, we proposed a set of energy efficient techniques supported on the cell breathing and hybrid cellular networks (macro/femtocells). Our proposed decision making mechanisms include distributed strategies and other features such as the use of a novel multimetric approach. In our work, we also take into account the energy consumption of mobile devices, an issue that to the best of our knowledge was not quite analysed so far. The use of renewable energy sources is also considered into our proposals. Our thesis work includes the study of the consequences of our radio resource management algorithms on the electromagnetic radiation taking into account the acceptable EM exposure thresholds. In the perspectives of future work, we can mention the improvement of our techniques with learning mechanisms and cognitive radio.

Les communications sans fil prolifèrent dans presque chaque aspect de la société humaine : puissants ‘smart-phones' et ‘tablets', accès haut débit sans fil, et communications ‘machine-to-machine' ont généré des volumes de trafic de données imprévisibles quelques années en arrière. Dans ce nouveau paradigme, l'industrie des télécommunications se doit de garantir à la fois la durabilité économique des communications sans fil à large bande ainsi que la qualité de son service. En outre, il y a une forte incitation sociale à réduire les émissions de C02 duent aux communications mobiles, qui a augmenté notamment dans la dernière décennie. Dans ce contexte, l'intégration des ‘femtocells' dans les réseaux cellulaires est une solution à faible coût pour offrir une qualité de service élevée et en même temps de décharger le réseau macrocellule. Cependant, le déploiement massif et chaotique des points d'accès femtocell et leurs opérations non coordonnées peuvent conduire à une augmentation de l'interférence co-canal. De plus, un nombre élevé de cellules faiblement chargées augmente la consommation énergétique du réseau. Dans cette thèse, nous avons étudié les effets du déploiement de femtocells sur l'efficacité énergétique du réseau cellulaire. Par ailleurs, nous investiguons sur les mécanismes d'adaptation pour les réseaux des femtocells comme un moyen pour améliorer l'efficacité des communications mobiles. Notre objectif est de répondre dynamiquement à la demande des ressources afin de limiter la consommation d'énergie moyenne et l'interférence co-canal, tout en garantissant la qualité de service. Nous profitons du contexte inhabituel de communication ‘femtocellulaire' pour proposer des mécanismes d'allocation des ressources et des systèmes de gestion de réseau qui coordonne l'activité des points d'accès, la consommation d'énergie et de la couverture. Les résultats des simulations montrent que nos propositions améliorent l'efficacité énergétique et les performances perçues par les utilisateurs du système dans les réseaux ‘femtocellulaires' coopératives et autonomes. / Wireless communication proliferates into nearly each aspect of the human society, driving to the exponential growth in number of permanently connected devices. Powerful smart-phones and tablets, ubiquitous wireless broadband access, and machine-to-machine communications gen- erate volumes of data traffic that were unpredictable few years back. In this novel paradigm, the telecommunication industry has to simultaneously guarantee the economical sustainability of broadband wireless communications and users' quality of experience. Additionally, there is a strong social incentive to reduce the carbon footprint due to mobile communications, which has notably increased in the last decade. In this context, the integration of femtocells in cellular networks is a low-power, low-cost solution to offer high data rates to indoor customers and simultaneously offload the macrocell network. However, the massive and unplanned deployment of femtocell access points and their uncoordinated operations may result in harmful co-channel interference. Moreover, a high number of lightly loaded cells increases the network energy consumption. In this thesis, we investigate the effects of femtocells deployment on the cellular network energy efficiency. Moreover, we look into adaptive mechanisms for femtocell networks as a means to pave the way towards agile and economically viable mobile communications. Our goal is to dynamically match resource demand and offered capacity in order to limit the average power consumption and co-channel interference while guaranteeing quality of service constraints. We take advantage of the unusual communication context of femtocells to propose resource allocation and network management schemes that coordinate the access points activity, power consumption, and coverage. Simulation results show that our proposals improve system energy efficiency and users' performance in both networked and stand-alone femtocell deployment scenarios.

Abstract The aim of this thesis is to devise novel cooperative paradigms that allow small base stations (SBSs) to perform joint optimizations in the field of interference and spectral resource management, in an automated, self-organizing way. Fostering cooperation requires a careful negotiation process and incurs additional operational costs that can ultimately limit the scalability of such an approach. Hence, we design cooperative models around the self-organizing functions of small cell networks, through which each SBS dynamically adapts its own cooperative strategy to the current network status. In the first part of the thesis, we study the co-tier interference in the downlink of an underlay small cell tier. Showing that mutual interference is a limiting factor, we propose a cooperative scheme based on the concept of interference alignment. Thereby, the SBSs autonomously devise their cooperative strategy, select partner small base stations and suppress the mutual interference via alignment. In the second part, we extend the above problem by considering additional constraints posed by non-cooperative macro cell users sharing the spectrum with the SBSs. Due to the dimension of such a problem, we show that interference alignment solutions do not often exist, hence, we propose a distributed solution based on the concept of interference draining for solving the interfering signals in the space-frequency domain. Finally, we focus on inter-tier cooperation and propose an adaptive hybrid access policy based on spectrum leasing, which jointly enhances the SBSs' transmission capacity and the macro cell users' QoS . In the studied scenarios, we highlight how SBSs' individual performance is network-dependent, due to the shared nature of the spectrum and the network infrastructure. For addressing such issues, we use novel concepts from coalitional games in partition form in which the strategic decisions are optimized by accounting for external effects, such as interference or dynamic spectrum allocation. Based on the properties of optimality of coalitional games in partition form, the proposed cooperative solutions show two key features. First, by leveraging on decentralized strategic decisions, complex interference management techniques, such as interference alignment or draining, can be implemented in practical, scalable way. Second, although notable cooperative solutions exists for certain problem dimensions, the proposed algorithms are shown to be effective for a wide range of network sizes, by achieving significant data rate enhancement and low overhead. / Tiivistelmä Työssä käsitellään merkittäviä häiriön ja radioresurssien hallintaongelmia ja ehdotetaan käytännöllisiä yhteistoiminnallisuusmalleja, jotka tuottavat merkittäviä suorituskykyparannuksia, ja samaan aikaan ottavat huomioon yhteistyön kustannukset ja strategisten päätösten vaikutuksen piensolujen keskinäiseen suorituskykyyn. Työn ensimmäisessa osassa tutkitaan makro- ja piensoluverkon välistä häiriötä laskevalla siirtosuunnalla. Koska keskinäishäiriö osoittautuu merkittäväksi rajoittavaksi tekijäksi, ehdotetaan yhteistyömenetelmää, joka perustuu ns. häiriön laskostamiseen. Tällaisessa menetelmässä pientukiasemat päättävät itsenäisesti yhteistyöstrategiansa ja valitsevat ne tukiasemat, joiden kanssa tehdään yhteistyötä ja vaimennetaan keskinäishäiriötä laskostamalla. Työn toisessa osassa edellämainittua ongelmaa laajennataan ottamalla huomioon rajoitteet, jotka aiheutuvat samoja taajuusresursseja jakavista, mutta piensolutukiasemien kanssa yhteistyötä tekemättömistä makrosoluista. Ongelman laajuudesta havaitaan, että yleensä häiriön laskostusratkaisua ei löydy tällaisessa ongelmassa. Niinpä ehdotetaan hajautettua häiriön kohdennukseen perustuvaa ratkaisua, jossa häiriösignaalit lomitellaan tila-taajuustasossa. Työn viimeisessä osassa keskitytään eri tyyppisten tukiasemasolujen kesken käytävään yhteistyöhön ja ehdotetaan mukautuvaa taajuusspektrin vuokraamiseen perustuvaa hybridi-käyttöoikeusmenetelmää, joka parantaa piensolujen kapasiteettia ja makrosolukäyttäjien palvelun laatua. Kaikissa tutkituissa menetelmissä korostetaan kuinka yksittäisen pientukiaseman suorituskyky on verkosta riippuvainen johtuen jaetusta taajuuskaistasta ja verkkoinfrastuktuurista. Näissä skenaarioissa käytetään uusia ositukseen perustuvia ns. liittoumapelikonsepteja. Tämän tyyppisissä peleissä strategiset päätökset on optimoitu ottamalla huomioon ulkoiset tekijät kuten häiriö ja dynaaminen taajuuden allokointi. Ositukseen perustuvien liitoumapelien optimaalisuus- ja stabiilisuusominaisuuksien pohjalta ehdotetaan hajautettuja algoritmeja tutkittuihin ongelmiin. Ehdotetut yhteistoiminnalliset ratkaisut osoittavat kaksi avaintekijää. Ensinnäkin käyttämällä hajautettuja strategisia päätöksiä kompleksiset häiriönhallintatekniikat, kuten häiriön lomittelu ja kohdennus, voidaan toteuttaa käytännöllisesti siten, että hyöty-kustannussuhde on tasapainossa. Toiseksi, vaikka merkittäviä yhteistyöratkaisuja on olemassa tietyn dimensioisiin ongelmiin, ehdotetut algoritmit ovat osoittautuneet tehokkaiksi hyvin erikokoisissa verkoissa. Samalla on saavutettu merkittäviä datanopeusparannuksia ja hyvä skaalautuvuus.

Hoy en día existen varias tecnologías que coexisten en una misma zona formando un sistema heterogéneo. Además, este hecho se espera que se vuelva más acentuado con todas las nuevas tecnologías que se están estandarizando actualmente. Hasta ahora, generalmente son los usuarios los que eligen la tecnología a la que se van a conectar, ya sea configurando sus terminales o usando terminales distintos. Sin embargo, esta solución es incapaz de aprovechar al máximo todos los recursos. Para ello es necesario un nuevo conjunto de estrategias. Estas estrategias deben gestionar los recursos radioeléctricos conjuntamente y asegurar la satisfacción de la calidad de servicio de los usuarios. Siguiendo esta idea, esta Tesis propone dos nuevos algoritmos. El primero es un algoritmo de asignación dinámica de recusos conjunto (JDRA) capaz de asignar recursos a usuarios y de distribuir usuarios entre tecnologías al mismo tiempo. El algoritmo está formulado en términos de un problema de optimización multi-objetivo que se resuelve usando redes neuronales de Hopfield (HNNs). Las HNNs son interesantes ya que se supone que pueden alcanzar soluciones sub-óptimas en cortos periodos de tiempo. Sin embargo, implementaciones reales de las HNNs en ordenadores pierden esta rápida respuesta. Por ello, en esta Tesis se analizan las causas y se estudian posibles mejoras. El segundo algoritmo es un algoritmo de control de admisión conjunto (JCAC) que admite y rechaza usuarios teniendo en cuenta todas las tecnologías al mismo tiempo. La principal diferencia con otros algorimos propuestos es que éstos últimos toman las dicisiones de admisión en cada tecnología por separado. Por ello, se necesita de algún mecanismo para seleccionar la tecnología a la que los usuarios se van a conectar. Por el contrario, la técnica propuesta en esta Tesis es capaz de tomar decisiones en todo el sistema heterogéneo. Por lo tanto, los usuarios no se enlazan con ninguna tecnología antes de ser admitidos. / Calabuig Soler, D. (2010). Common Radio Resource Management Strategies for Quality of Service Support in Heterogeneous Wireless Networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/7348 / Palancia

Abstract Future cellular networks need to support the ever-increasing demand of bandwidth-intensive applications and interconnection of people, devices, and vehicles. Small cell network (SCN)-based communication together with proximity- and social-aware connectivity is conceived as a vital component of these networks to enhancing spectral efficiency, system capacity, and quality-of-experience (QoE). To cope with diverse application needs for the heterogeneous ecosystem, radio resource management (RRM) is one of the key research areas for the fifth-generation (5G) network. The key goals of this thesis are to develop novel, self-organizing, and low-complexity resource management algorithms for emerging device-to-device (D2D) and vehicle-to-vehicle (V2V) wireless systems while explicitly modeling and factoring network contextual information to satisfy the increasingly stringent requirements. Towards achieving this goal, this dissertation makes a number of key contributions. First, the thesis focuses on interference management techniques for D2D-enabled macro network and D2D-enabled SCNs in the downlink, while leveraging users’ social-ties, dynamic clustering, and user association mechanisms for network capacity maximization. A flexible social-aware user association technique is proposed to maximize network capacity. The second contribution focuses on ultra-reliable low-latency communication (URLLC) in vehicular networks in which interference management and resource allocation techniques are investigated, taking into account traffic and network dynamics. A joint power control and resource allocation mechanism is proposed to minimize the total transmission power while satisfying URLLC constraints. To overcome these challenges, novel algorithms are developed by combining several methodologies from graph theory, matching theory and Lyapunov optimization. Extensive simulations validate the performance of the proposed approaches, outperforming state-of-the-art solutions. Notably, the results yield significant performance gains in terms of capacity, delay reductions, and improved reliability as compared with conventional approaches. / Tiivistelmä Tulevaisuuden solukkoverkkojen pitää pystyä tukemaan yhä suurempaa kaistanleveyttä vaativia sovelluksia sekä yhteyksiä ihmisten, laitteiden ja ajoneuvojen välillä. Piensoluverkkoihin (SCN) pohjautuvaa tietoliikennettä yhdistettynä paikka- ja sosiaalisen tietoisuuden huomioiviin verkkoratkaisuihin pidetään yhtenä elintärkeänä osana tulevaisuuden solukkoverkkoja, joilla pyritään tehostamaan spektrinkäytön tehokkuutta, järjestelmän kapasiteettia sekä kokemuksen laatua (QoE). Radioresurssien hallinta (RRM) on eräs keskeisistä viidennen sukupolven (5G) verkkoihin liittyvistä tutkimusalueista, joilla pyritään hallitsemaan heterogeenisen ekosysteemin vaihtelevia sovellustarpeita. Tämän väitöstyön keskeisinä tavoitteina on kehittää uudenlaisia itseorganisoituvia ja vähäisen kompleksisuuden resurssienhallinta-algoritmeja laitteesta-laitteeseen (D2D) ja ajoneuvosta-ajoneuvoon (V2V) toimiville uusille langattomille järjestelmille, sekä samalla mallintaa ja tuottaa verkon kontekstikohtaista tietoa vastaamaan koko ajan tiukentuviin vaatimuksiin. Tämä väitöskirja edistää näiden tavoitteiden saavuttamista usealla keskeisellä tuloksella. Aluksi väitöstyössä keskitytään häiriönhallinnan tekniikoihin D2D:tä tukevissa makroverkoissa ja laskevan siirtotien piensoluverkoissa. Käyttäjän sosiaalisia yhteyksiä, dynaamisia ryhmiä sekä osallistamismekanismeja hyödynnetään verkon kapasiteetin maksimointiin. Verkon kapasiteettia voidaan kasvattaa käyttämällä joustavaa sosiaaliseen tietoisuuteen perustuvaa osallistamista. Toinen merkittävä tulos keskittyy huippuluotettavaan lyhyen viiveen kommunikaatioon (URLLC) ajoneuvojen verkoissa, joissa tehtävää resurssien allokointia ja häiriönhallintaa tutkitaan liikenteen ja verkon dynamiikka huomioiden. Yhteistä tehonsäädön ja resurssien allokoinnin mekanismia ehdotetaan kokonaislähetystehon minimoimiseksi samalla, kun URLLC rajoitteita noudatetaan. Jotta esitettyihin haasteisiin voidaan vastata, väitöstyössä on kehitetty uudenlaisia algoritmeja yhdistämällä graafi- ja sovitusteorioiden sekä Lyapunovin optimoinnin menetelmiä. Laajat tietokonesimuloinnit vahvistavat ehdotettujen lähestymistapojen suorituskyvyn, joka on parempi kuin uusimmilla nykyisillä ratkaisuilla. Tulokset tuovat merkittäviä suorituskyvyn parannuksia erityisesti kapasiteetin lisäämisen, viiveiden vähentämisen ja parantuneen luotettavuuden suhteen verrattuna perinteisiin lähestymistapoihin.

Radio resource allocation in communication networks is essential to achieve optimal performance and resource utilization. In modern interference networks the corresponding optimization problems are often nonconvex and their solution requires significant computational resources. Hence, practical systems usually use algorithms with no or only weak optimality guarantees for complexity reasons. Nevertheless, asserting the quality of these methods requires the knowledge of the globally optimal solution. State-of-the-art global optimization approaches mostly employ Tuy's monotonic optimization framework which has some major drawbacks, especially when dealing with fractional objectives or complicated feasible sets. In this thesis, two novel global optimization frameworks are developed. The first is based on the successive incumbent transcending (SIT) scheme to avoid numerical problems with complicated feasible sets. It inherently differentiates between convex and nonconvex variables, preserving the low computational complexity in the number of convex variables without the need for cumbersome decomposition methods. It also treats fractional objectives directly without the need of Dinkelbach's algorithm. Benchmarks show that it is several orders of magnitude faster than state-of-the-art algorithms. The second optimization framework is named mixed monotonic programming (MMP) and generalizes monotonic optimization. At its core is a novel bounding mechanism accompanied by an efficient BB implementation that helps exploit partial monotonicity without requiring a reformulation in terms of difference of increasing (DI) functions. While this often leads to better bounds and faster convergence, the main benefit is its versatility. Numerical experiments show that MMP can outperform monotonic programming by a few orders of magnitude, both in run time and memory consumption. Both frameworks are applied to maximize throughput and energy efficiency (EE) in wireless interference networks. In the first application scenario, MMP is applied to evaluate the EE gain rate splitting might provide over point-to-point codes in Gaussian interference channels. In the second scenario, the SIT based algorithm is applied to study throughput and EE for multi-way relay channels with amplify-and-forward relaying. In both cases, rate splitting gains of up to 4.5% are observed, even though some limiting assumptions have been made.

Thesis ( M.Sc. (Computer Science)) -- University of Limpopo, 2019 / Cognitive radio network, which enables dynamic spectrum access, addresses the shortage of radio spectrum caused by ever-increasing wireless technology. This allows efficient utilisation of underutilised licenced spectrum by allowing cognitive radios to opportunistically make use of available licenced spectrum. Cognitive radios (CR), also known as secondary users, must constantly sense the spectrum band to avoid interfering with the transmission of the licenced users, known as primary users. Cognitive radios must cooperate in sensing the spectrum environment to avoid environmental issues that can affect the spectrum sensing. However, cooperative spectrum sensing is vulnerable to Byzantine attacks where selfish CR falsify the spectrum reports. Hence, there is a need to design and implement a defence mechanism that will thwart the Byzantine attacks and guarantee correct available spectrum access decisions. The use of extreme studentized deviate (ESD) test together with consensus algorithms are proposed in this study to combat the results of the availability of Byzantine attack in a cognitive radio network. The ESD test was used to detect and isolate falsified reports from selfish cognitive radios during the information sharing phase. The consensus algorithm was used to combine sensing reports at each time k to arrive at a consensus value which will be used to decide the spectrum availability. The proposed scheme, known extreme studentized cooperative consensus spectrum sensing (ESCCSS), was implemented in an ad hoc cognitive radio networks environment where the use of a data fusion centre (DFC) is not required. Cognitive radios make their own data fusion and make the final decision about the availability of the spectrum on their sensed reports and reports from their neighbouring nodes without any assistance from the fusion centre. MATLAB was used to implement and simulate the proposed scheme. We compared our scheme with Attack-Proof Cooperative Spectrum Sensing to check its effectiveness in combating the effect of byzantine attack.