Abstract The use of multiple antennas is a fundamental requirement in future wireless networks as it helps to increase the reliability and spectral efficiency of mobile radio links. In this thesis, we study convex optimization based radio resource allocation methods for the downlink of multi-antenna systems. First, the problem of admission control in the downlink of a multicell multiple-input single-output (MISO) system has been considered. The objective is to maximize the number of admitted users subject to a signal-to-interference-plus-noise ratio (SINR) constraint at each admitted user and a transmit power constraint at each base station (BS). We have cast the admission control problem as an ℓ0 minimization problem; it is known to be combinatorial, NP-hard. Centralized and distributed algorithms to solve this problem have been proposed. To develop the centralized algorithm, we have used sequential convex programming (SCP). The distributed algorithm has been derived by using the consensus-based alternating direction method of multipliers in conjunction with SCP. We have shown numerically that the proposed admission control algorithms achieve a near-to-optimal performance. Next, we have extended the admission control problem to provide fairness, where long-term fairness among the users has been guaranteed. We have focused on proportional and max-min fairness, and proposed dynamic control algorithms via Lyapunov optimization. Results show that these proposed algorithms guarantee fairness. Then, the problem of admission control for the downlink of a MISO heterogeneous networks (hetnet) has been considered, and the proposed centralized and distributed algorithms have been adapted to find a solution. Numerically, we have illustrated that the centralized algorithm achieves a near-to-optimal performance, and the distributed algorithm’s performance is closer to the optimal value. Finally, an algorithm to obtain the set of all achievable power-rate tuples for a multiple-input multiple-output hetnet has been provided. The setup consists of a single macrocell and a set of femtocells. The interference power to the macro users from the femto BSs has been kept below a threshold. To find the set of all achievable power-rate tuples, a two-dimensional vector optimization problem is formulated, where we have considered maximizing the sum-rate while minimizing the sum-power, subject to maximum power and interference threshold constraints. This problem is known to be NP-hard. A solution method is provided by using the relationship between the weighted sum-rate maximization and weighted-sum-mean-squared-error minimization problems. The proposed algorithm was used to evaluate the impact of imposing interference threshold constraints and the co-channel deployments in a hetnet. / Tiivistelmä Monen antennin käyttö on perusvaatimus tulevissa langattomissa verkoissa, koska se auttaa lisäämään matkaviestinyhteyksien luotettavuutta ja spektritehokkuutta. Tässä väitöskirjassa tutkitaan konveksiin optimointiin perustuvia radioresurssien allokointimenetelmiä moniantennijärjestelmien alalinkin suunnassa. Ensiksi on käsitelty pääsynvalvonnan ongelmaa alalinkin suuntaan monen solun moni-tulo yksi-lähtö (MISO) -verkoissa. Tavoitteena on maksimoida hyväksyttyjen käyttäjien määrä, kun hyväksytyille käyttäjille on asetettu signaali-häiriö-kohinasuhteen (SINR) rajoitus, ja tukiasemille lähetystehon rajoitus. Pääsynvalvonnan ongelma on muotoiltu ℓ0-minimointiongelmana, jonka tiedetään olevan kombinatorinen, NP-vaikea ongelma. Ongelman ratkaisemiseksi on ehdotettu keskitettyjä ja hajautettuja algoritmeja. Keskitetty optimointialgoritmi perustuu sekventiaaliseen konveksiin optimointiin. Hajautettu algoritmi pohjautuu konsensusoptimointimenetelmään ja sekventiaaliseen konveksiin optimointiin. Ehdotettujen pääsynvalvonta-algoritmien on numeerisesti osoitettu saavuttavan lähes optimaalinen suorituskyky. Lisäksi pääsynvalvontaongelma on laajennettu takaamaan pitkän aikavälin oikeudenmukaisuus käyttäjien välillä. Työssä käytetään erilaisia määritelmiä oikeudenmukaisuuden takaamiseen, ja ehdotetaan dynaamisia algoritmeja pohjautuen Lyapunov-optimointiin. Tulokset osoittavat, että ehdotetuilla algoritmeilla taataan käyttäjien välinen oikeudenmukaisuus. Tämän jälkeen käsitellään heterogeenisen langattoman MISO-verkon pääsynvalvonnan ongelmaa. Edellä ehdotettuja keskitettyjä ja hajautettuja algoritmeja on muokattu tämän ongelman ratkaisemiseksi. Työssä osoitetaan numeerisesti, että sekä keskitetyllä että hajautetulla algoritmilla saavutetaan lähes optimaalinen suorituskyky. Lopuksi on laadittu algoritmi, jolla löydetään kaikki saavutettavissa olevat teho-datanopeusparit heterogeenisessä langattomassa moni-tulo moni-lähtö (MIMO) -verkossa. Verkko koostuu yhdestä makrosolusta ja useasta piensolusta. Piensolutukiasemista makrokäyttäjiin kohdistuvan häiriön teho on pidetty tietyn rajan alapuolella. Kaikkien saavutettavien teho-datanopeusparien löytämiseksi on laadittu kaksiulotteinen vektorioptimointiongelma, jossa maksimoidaan summadatanopeus pyrkien minimoimaan kokonaisteho, kun enimmäisteholle ja häiriökynnykselle on asetettu rajoitukset. Tämän ongelman tiedetään olevan NP-vaikea. Ongelman ratkaisemiseksi käytetään painotetun summadatanopeuden maksimointiongelman, ja painotetun keskineliövirheen minimointiongelman välistä suhdetta. Ehdotettua algoritmia käytettiin arvioimaan häiriörajoitusten ja saman kanavan käyttöönoton vaikutusta heterogeenisessä langattomassa verkossa.

Cognitive radio (CR) networks and heterogeneous cellular networks are promising approaches to satisfy the demand for higher data rates and better connectivity. A CR network increases the utilization of the radio spectrum by opportunistically using it. Heterogeneous networks provide high data rates and improved connectivity by spatially reusing the spectrum and by bringing the network closer to the user. Interference presents a critical challenge for reliable communication in these networks. Accurately modeling it is essential in ensuring a successful design and deployment of these networks. We first propose modeling the aggregate interference power at a primary receiver (PU-Rx) caused from transmissions by randomly located cognitive users (CUs) in a CR network as a shifted lognormal random process. Its parameters are determined using a moment matching method. Extensive benchmarking shows that the proposed model is more accurate than the lognormal and Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, interweave and underlay modes of CR operation, and path-loss, time-correlated shad-owing and fading of the various links in the network. It leads to new expressions for the probability distribution function, level crossing rate (LCR), and average exceedance duration (AED). The impact of cooperative spectrum sensing is also characterized. We also apply and validate the proposed model by using it to redesign the primary exclusive zone to account for the time-varying nature of interference. Next we model the uplink inter-cell aggregate interference power in homogeneous and heterogeneous cellular systems as a simpler lognormal random variable. We develop a new moment generating function (MGF) matching method to determine the lognormal’s parameters. Our model accounts for the transmit power control, peak transmit power constraint, small scale fading and large scale shadowing, and randomness in the number of interfering mobile stations and their locations. In heterogeneous net-works, the random nature of the number and locations of low power base stations is also accounted for. The accuracy of the proposed model is verified for both small and large values of interference. While not perfect, it is more accurate than the conventional Gaussian and moment-matching-based lognormal and Gamma distribution models. It is also performs better than the symmetric-truncated stable and stable distribution models, except at higher user density.

Disertační práce se zabývá kryptografickými protokoly poskytující ochranu soukromí, které jsou určeny pro zabezpečení komunikačních a informačních systémů tvořících heterogenní sítě. Práce se zaměřuje především na možnosti využití nekonvenčních kryptografických prostředků, které poskytují rozšířené bezpečnostní požadavky, jako je například ochrana soukromí uživatelů komunikačního systému. V práci je stanovena výpočetní náročnost kryptografických a matematických primitiv na různých zařízeních, které se podílí na zabezpečení heterogenní sítě. Hlavní cíle práce se zaměřují na návrh pokročilých kryptografických protokolů poskytujících ochranu soukromí. V práci jsou navrženy celkově tři protokoly, které využívají skupinových podpisů založených na bilineárním párování pro zajištění ochrany soukromí uživatelů. Tyto navržené protokoly zajišťují ochranu soukromí a nepopiratelnost po celou dobu datové komunikace spolu s autentizací a integritou přenášených zpráv. Pro navýšení výkonnosti navržených protokolů je využito optimalizačních technik, např. dávkového ověřování, tak aby protokoly byly praktické i pro heterogenní sítě.

Mobile data traffic is expected to increase substantially in the coming years, with data rates 1000 times higher by 2020, having media and content as the main drivers together with a plethora of new end-user services that will challenge existing networks. Concepts and visions associated with the ICT evolution like the network society, 50 billion connected devices, Industrial Internet, Tactile Internet, etc., exemplifies the range of new services that the networks will have to handle. These new services impose extreme requirement to the network like high capacity, low latency, reliability, security, seamless connectivity, etc. In order to face these challenges, the whole end-to-end network has to evolve and adapt, pushing for advances in different areas, such as transport, cloud, core, and radio access networks. This work investigates the impact of envisioned 2020 society scenarios on transport links for mobile backhaul, emphasizing the need for an integrated and flexible/adaptive network as the way to meet the 2020 networks demands. The evolution of heterogeneous networks and ultra-dense network deployments shall also comprise the introduction of adaptive network features, such as dynamic network resource allocation, automatic integration of access nodes, etc. In order to achieve such self-management features in mobile networks, new mechanisms have to be investigated for an integrated backhaul management. First, this thesis performs a feasibility study on the mobile backhaul dimensioning for 2020 5G wireless ultra-dense networks scenarios, aiming to analyze the gap in capacity demand between 4G and 5G networks. Secondly, the concept of an integrated backhaul management is analyzed as a combination of node attachment procedures, in the context of moving networks. In addition, the dynamic network resource allocation concept, based on DWDM-centric transport architecture, was explored for 5G scenarios assuming traffic variation both in time and between different geographical areas. Finally, a short view on techno-economics and network deployments in the 2020 time frame is provided.

Globally, the number of mobile broadband subscriptions is growing and the amount of mobile data traffic is expected to continue to grow rapidly. In the next five years the number of smartphone subscriptions is expected to more than double, while the amount of mobile traffic per active subscription per month of these subscribers is expected to nearly quadruple. As a consequence, mobile network operators (MNOs) aim to increase radio network capacity and coverage through heterogeneous deployments. In such heterogeneous networks, wireless local area networks (WLANs) are integrated with wireless wide area networks (WWANs), and there exist a tight interaction between them. The almost-ubiquitous support for IEEE802.11 WLANs (usually referred to as Wi-Fi®) makes this radio access technology a potential integrated component of near-future mobile broadband. With Wi-Fi completely integrated into mobile access, MNOs would optimize user experience and use of resources by controlling device’s choice of connectivity. In addition to guaranteeing the best user experience, optimal use of access networks should care about energy-efficiency in order to extend device’s battery life. However, the performance of Wi-Fi is far from meet neither energy-efficiency nor quality of service (QoS) user’s requirements. This radio access technology employs an energy-consuming medium access control (MAC) protocol that wastes both bandwidth and device’s energy resources. Therefore, enhanced MAC protocols, cleverly combined with standardized power saving mechanisms such as automatic power save delivery (APSD), would improve both energy-efficiency and QoS in order to enhance WLANs performance and meet user’s expectations. In addition, current WLAN discovery mechanisms neither meet requirements of the integrated scenario. Handover operations must be improved in terms of energy efficiency and latency. Consequently, enhanced handover schemes should reduce overall device’s energy consumption during the process, and enable seamless handover between Wi-Fi APs and between cellular/Wi-Fi networks. During this thesis project, the main challenges of Wi-Fi towards its integration into mobile access broadband have been analyzed. Consequently, a solution has been designed in order to address the identified challenges, which have been introduced in the previous paragraphs. The solution consists of enhancements for IEEE 802.11 WLANs based on current standards that achieve energy-efficiency and QoS, and facilitate Wi-Fi/cellular networks interworking. Finally, a custom-designed simulator has been used to evaluate the proposed solution. / Globalt sett är antalet mobila bredbandsabonnemang ökar och mängden av mobil datatrafik förväntas fortsätta att växa snabbt. Under de kommande fem åren kommer antalet smartphone-abonnemang väntas mer än fördubblas, medan mängden av mobiltrafiken per aktiv prenumeration per månad för dessa abonnenter väntas nästan fyrdubbla. Som en följd av mobiloperatörer som mål att öka sin radio nätkapacitet och täckning genom heterogena distributioner. I sådana heterogena nätverk, är trådlösa lokala nätverk (WLAN) integrerad med trådlösa WAN-nätverk (WWAN), och det finns en tät interaktion mellan dem. För att möta denna efterfrågan ämnar operatörer av mobila nätverk att öka kapacitet och täckning genom att bygga ut heterogena nätverk. I sådana heterogena nätverk integreras trådlösa lokala nätverk (WLAN) med nätverk med större yttäckning (cellulära nät) med täta interaktioner mellan de olika näten. Det mycket utbredda stödet för IEEE 802.11-standarden (ofta kallad för Wi-Fi®) för WLAN gör denna radioaccessteknik till en potentiell integrerad komponent för mobilt bredband i den nära framtiden. Med Wi-Fi som en integrerad i det mobila accessnätet kan mobilnätsoperatörer optimera användarupplevelsen och resursanvädningen genom att styra de mobila enheternas val av uppkoppling. Förutom att garantera den bästa användarupplevelsen så bör valet av accessnät ta hänsyn till energieffektiviteten för att förlänga batteridrifttiden för den mobila enheten. Wi-Fi är dock långt ifrån att uppfylla användarnas krav på energieffektivitet och tjänstekvalitet, eftersom denna radioaccessteknik använder ett mediumaccessprotokoll (MAC) som varken använder bandbredd eller batterienergi effektivt. Därför kan förbättrade MAC-protokoll kombinerade med standardiserade energibesparingslösningar såsom automatic power save delivery (APSD) ge bättre energieffektivitet och tjänstekvalitet, och därmed förbättra WLANs möjligheter att möta användarnas förväntningar. Dessutom har nuvarande nätverksidentifieringsmekanismer i WLAN svårt att uppfylla kraven i ett scenario med integrerade nätverk, eftersom den nuvarande sökmetoden är långsam och använder mycket energi. En förbättrad lösning bör minska energikonsumtionen under hela processen, och möjliggöra avbrottsfri övergång mellan Wi-Fi accessnoder och mellan cellulära och Wi-Fi-nätverk. Under detta examensarbete har de största utmaningarna för Wi-Fi under integrationen med mobil bredbandsaccess analyserats. En lösning har utvecklats för att lösa de identifierade problemen som beskrivits ovan. Lösningen består av förbättringar av IEEE 802.11 accessnät, som bygger vidare på existerande standardens energieffektivitets- och tjänstekvalitetslösningar och underlättar samverkan mellan Wi-Fi och cellulära nätverk. Slutligen har en egenutvecklad simulator använts för att utvärdera den föreslagna lösningen.

Dans cette thèse, nous étudions les algorithmes d’alignement d’interférence dans les réseaux hétérogènes basés sur la sélection des flux. Tout d’abord, nous considérons différents scénarios de déploiement des pico-cellules dans un contexte de connaissance parfaite des canaux de transmission au niveau des émetteurs. Deux algorithmes sont proposés respectivement pour les réseaux totalement et partiellement connectés. Afin d’assurer une équité entre les liens, les algorithmes garantissent qu’au moins un flux de chaque lien émetteur/récepteur soit sélectionné. La séquence des flux est choisie parmi un ensemble qui contient les séquences les plus souvent sélectionnées en effectuant une recherche exhaustive. Ces algorithmes sont significativement moins complexes que la recherche exhaustive tout en ayant une performance proche de celle-ci. Après la sélection d’un flux, les interférences entre ce flux et les flux qui n’ont pas encore été sélectionnées sont alignées par projections orthogonales. Dans une deuxième partie de la thèse, l’impact de la connaissance partielle des canaux de transmission sur les algorithmes proposés est analysé. Il est montré que les interférences entre flux causent alors une forte dégradation des performances en raison des erreurs de quantification. Pour réduire cette dégradation, un nouvel algorithme est développé pour ce contexte. Finalement, des schémas d’allocation adaptative des bits pour les voies de retour sont proposés afin d’augmenter les performances des algorithmes précédents. Les performances de ces schémas et de ces algorithmes sont évaluées en considérant différents scénarios avec différentes topologies des pico-cellules. Nous avons montré que les algorithmes proposés pour le cas des transmissions avec voie de retour sont significativement plus robustes et plus performants que les algorithmes d’alignement d’interférence classiques. / In this thesis, we study the stream selection based interference alignment (IA) algorithms, which can provide large multiplexing gain, to deal with the interference in the heterogeneous networks. Firstly, different deployment scenarios for the pico cells are investigated assuming perfect channel state information (CSI) at the transmitters.Two different stream selection IA algorithms are proposed for fully and partially connected interference networks and selecting at least one stream is guaranteed for each user. A stream sequence is selected among a predetermined set of sequences that mostly contribute to the sum-rate while performing an exhaustive search. In the proposed algorithms, the complexity of the exhaustive search is significantly decreased while keeping the performance relatively close. After selecting a stream, the interference generated between the selected and the unselected streams is aligned by orthogonal projections. Then, the influence of the imperfect CSI on the proposed algorithms is analyzed and it is observed that the intra-stream interference causes a significant degradation in the performance due to the quantization error. Therefore, we propose an algorithm for the limited feedback scheme. Finally, adaptive bit allocation schemes are presented to maximize the overall capacity for all the proposed algorithms. The performance evaluations are carried out considering different scenarios with different number and placements of pico cells. It is shown that the proposed algorithm for the limited feedback is more robust to channel imperfections compared to the existing IA algorithms.

[pt] Os sistemas de comunicações móveis atuais vêm enfrentando novos desafios, marcados pelo aumento do uso de novos dispositivos e pela mudança nos padrões de consumo de banda causada pelas aplicações emergentes. É por isso que a indústria de comunicações e a comunidade acadêmica vêm trabalhando tanto nas dificuldades apresentadas nas redes móveis atuais quanto nos desafios técnicos para o desenvolvimento dos esperados sistemas de quinta geração (5G). O grande aumento dos elementos da rede de acesso rádio e a implementação de cenários heterogêneos (macro e pico eNBs, Relay Nodes, etc.) são duas das principais abordagens utilizadas para melhorar a capacidade da rede. No entanto, esse acréscimo de elementos ou, densificação, traz consigo um aumento nos custos e na complexidade nas tarefas de operação e gerenciamento do sistema, já que os novos elementos de rede precisam ser adaptados, configurados e gerenciados continuamente para garantir e aumentar a eficiência da rede, melhorando a qualidade nos serviços oferecidos aos usuários. Este trabalho de pesquisa propõe a inclusão de mecanismos cognitivos, incluindo técnicas de adaptação, nas arquiteturas das redes de acesso móvel. O trabalho propõe igualmente novos mecanismos de auto-organização (Self Organizing Networks, SON) para o balanceamento de carga, empregando modelos dinâmicos capazes de tomar decisões inteligentes e aprender a partir de experiências para atingir os objetivos de desempenho desejados. / [en] Today s mobile communications systems are facing new challenges, triggered by the increased use of new devices and the growth of bandwidth hungry applications. This is why over the last years, the telecommunication industry and academic communities have been focused on research and development of technologies for the upcoming 5th generation mobile systems (5G). Among the potential candidates, network densification has attracted growing attention as a key mechanism to fulfill the objective proposed in 5G, by increasing the number of radio-base stations (on the coverage area) and introducing an additional layer of low-power access nodes (e.g., Femto, picocells, relay nodes). However, this approach has also posed new challenges in network configuration, management, and optimization tasks to ensure and increase the mobile network efficiency. This research proposes the inclusion of cognitive mechanisms and adaptive techniques in the architectures of mobile radio access networks. This work also proposes new self-organizing (SON) functions for load balancing, enhanced with capabilities of learning from previous experiences to achieve future desired performance goals.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increases energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices causes a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS.

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