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Multicast transmission is an attractive solution when a large number of users receive the same content in a wide area, for example, as with mobile TV. Ever since the multimedia broadcast multicast service (MBMS) was introduced in the 3rd Generation Partnership Project (3GPP), continuing work on the multicast transmission has been done and its importance is growing in the fifth generation (5G) cellular networks. The use cases of multicast transmission have been enlarged from mobile TV and public safety to vehicular-to-everything (V2X) and unmanned aerial vehicles (UAV). Recently, for group communications in public safety networks and for geographical information sharing in automotive, airborne and social networks, multicast transmission has been targeted at fewer users in a relatively small area, which has stimulated extensive research on the single-cell multicast transmission scheme. In the proposed single-cell multicast transmission scheme, a supplementary multicast channel is additionally assigned in a single-cell multicast transmission scheme to exploit channel diversity. The resource allocation is adaptive to the channel variations of the users (responsive to users QoS needs), using channel feedback from the users, in contrast with previous approaches where resources were determined conservatively. An optimal resource allocation problem to minimize the required bandwidth while enabling every user to obtain the target multicast rate is formulated as a convex problem and an iterative algorithm is proposed in a computationally efficient way. Performance is evaluated mathematically and through intensive simulations, where other cell interference is considered using a fluid model. The proposed single-cell multicast transmission scheme provides benefits in comparison to existing multicast schemes in the simulations, under a set of various parameters including the number of multicast users and channel correlation between the multicast channels.

Recently, Device-to-Device (D2D) has been brought inside mobile (cellular) networks with the introduction of the LTE-D2D standard into the 5G ecosystem. This cellular D2D operates in the same operator's frequencies used for regular communications with access points (i.e., base stations). In D2D mode, terminals can communicate directly and do not need to go through a base station. However, D2D communications are authorized and controlled by operators to implement their requirements and policies. A notable example of D2D is data offloading, which helps in reducing traffic congestion in mobile networks. In this scenario, terminals collaborate using their D2D connections to carry data, usually over multiple D2D hops, using other terminals as relays and avoiding base stations. However, the latter still must decide on routing (e.g., which devices should be part of the path) and wireless resource allocation (which frequencies to use by devices). Also, base stations must manage interferences between D2D and cellular communication since they all share the same spectrum. Besides, there is also the energy issue in employing battery-constrained terminals as relays. Another concern, in offloading designs, is how they scale when terminals density increases, such as in crowded-platform scenarios. These scenarios include mobile users in waiting halls of airports and train stations, or stadiums. In such situations, the decision problems mentioned before must be solved rapidly. Doing so avoids long delays in communications that can affect user experience or limit responsiveness. In this thesis, we address the problem of optimizing routing and wireless resource allocation in multihop D2D systems with a focus on data offloading. Our proposals to solve the problem consider practical aspects of the LTE-D2D standard. Moreover, we also address the mentioned energy and scalability concerns. We propose three contributions to deal with these problems. In the first contribution, we propose a novel method (JRW-D2D) to solve jointly routing and resource allocation in the aim of offloading unicast flows inside one cell over the LTE-D2D relaying system. The proposal JRW-D2D is based on Integer Linear Programming (ILP) and gives good results in terms of reliability, latency, and acceptance ratio. In the second contribution, we present two methods to solve the same problem for both unicast and multicast traffic. In the first step, we introduce an optimal ILP-based method (JRW-D2D-MC) to solve routing and resource allocation jointly. Next, to address the scalability issue in JRW-D2D-MC, we propose another scalable method (JRW-D2D-CG) based on the Column-Generation technique. Finally, our third contribution considers the energy issue, where we put forward two energy-aware schemes to solve routing and resource allocation. Initially, we propose an ILP-based method for Energy-Efficient Joint Routing and Resource Allocation (JRRA-EE). In the next step, we highlight the non-scalability of JRRA-EE and introduce a novel parametric three-stage method called Heuristic Energy-aware Routing and Resource Allocation (HERRA). Both JRRA-EE and HERRA consider energy consumption using a state-of-the-art empirical model for LTE-D2D terminals. Moreover, we evaluate the performance of our contributions based on network simulations in NS-3, which we have extended to support the LTE-D2D standard., Récemment, D2D (Device-to-Device) a été intégré aux réseaux mobiles avec l'introduction de la norme LTE-D2D dans l'écosystème 5G. Ce D2D cellulaire fonctionne aux mêmes fréquences que l’opérateur utilisé pour les communications régulières avec les points d’accès (c.à.d. les stations de base). En mode D2D, les terminaux peuvent communiquer directement et n’ont pas besoin de passer par une station de base. Cependant, les communications D2D sont autorisées et contrôlées par les opérateurs pour mettre en œuvre leurs exigences et leurs politiques. Le délestage de données est un exemple notable de D2D, qui aide à réduire la congestion du trafic dans les réseaux mobiles. Dans ce scénario, les terminaux collaborent en utilisant leurs connexions D2D pour transporter les données, généralement sur plusieurs sauts D2D, en utilisant d'autres terminaux comme relais et en évitant les stations de base. Toutefois, ces derniers doivent décider du routage (par exemple, quels terminaux devraient faire partie du chemin) et de l’allocation de ressources sans fil (quelles fréquences à utiliser par les terminaux). De plus, les stations de base doivent gérer les interférences entre les communications, D2D et cellulaires, car elles partagent toutes le même spectre. En outre, il y a aussi le problème énergétique lié à l'utilisation de relais soumis aux contraintes de batterie. Un autre enjeu, dans ces conceptions de délestage, concerne la manière dont elles évoluent lorsque la densité des terminaux augmente (p. ex., dans les scénarios de plate-forme surpeuplée). Ces scénarios incluent des utilisateurs mobiles dans les halls d’attente des aéroports et des gares, ou des stades. Dans de telles situations, les problèmes de décision susmentionnés doivent être résolus rapidement. Cela évite de longs délais dans les communications qui peuvent affecter l'expérience utilisateur ou limiter la réactivité. Dans cette thèse, nous abordons le problème de l'optimisation du routage et de l'allocation de ressources sans fil dans les systèmes D2D multi-sauts en mettant l'accent sur le délestage de données. Nos propositions pour résoudre le problème prennent en compte les aspects pratiques de la norme LTE-D2D. De plus, nous répondons également aux enjeux mentionnés en matière d’énergie et d’évolutivité. Nous proposons trois contributions pour traiter ces problèmes. Dans la première contribution, nous proposons une nouvelle méthode (JRW-D2D) pour résoudre conjointement le routage et l’allocation de ressources afin de délester des flux unicast sur un système de relais LTE-D2D. La proposition JRW-D2D est basée sur la programmation linéaire en nombres entiers (ILP) et donne de bons résultats en termes de fiabilité, de latence et de taux d’acceptation. Dans la deuxième contribution, nous présentons deux méthodes pour résoudre le même problème pour les trafics unicast et multicast. Dans la première étape, nous présentons une méthode optimale basée sur ILP (JRW-D2D-MC) pour résoudre conjointement le routage et l’allocation de ressources. Ensuite, pour résoudre le problème de non-évolutivité de JRW-D2D-MC, nous proposons une autre méthode évolutive (JRW-D2D-CG) basée sur la génération de colonnes. Enfin, notre troisième contribution aborde la question de l’énergie, dans laquelle nous avons présenté deux systèmes axés sur l’énergie pour résoudre les problèmes de routage et d’allocation de ressources. Dans un premier temps, nous proposons une méthode (JRRA-EE) basée sur ILP. Dans l'étape suivante, nous mettons en évidence la non-évolutivité de JRRA-EE et présentons une nouvelle méthode paramétrique à trois étapes appelée (HERRA) et basée sur l’heuristique. Les deux méthodes JRRA-EE et HERRA considèrent la consommation d'énergie à l'aide d'un modèle empirique de pointe pour les terminaux LTE-D2D. De plus, nous évaluons la performance de nos contributions sur la base de simulations de réseau dans NS-3 que nous avons étendu pour prendre en charge la norme LTE-D2D.

Narrowband Internet of Things (NB-IoT) is the prominent technology that fits the requirements of future Internet of Things (IoT) networks. However, due to the limited spectrum (i.e., 180 kHz) availability for NB-IoT systems, one of the key issues is how to efficiently use these resources to support massive IoT devices? Furthermore, in NB-IoT, to reduce the computation complexity and to provide coverage extension, the concept of time offset and repetition has been introduced. Considering these new features, the existing resource management schemes are no longer applicable. Moreover, the allocation of frequency band for NB-IoT within LTE band, or as a standalone, might not be synchronous in all the cells, resulting in intercell interference (ICI) from the neighbouring cells’ LTE users or NB-IoT users (synchronous case). In this paper, first a theoretical framework for the upper bound on the achievable data rate is formulated in the presence of control channel and repetition factor. From the conducted analysis, it is shown that the maximum achievable data rates are 89.2 Kbps and 92 Kbps for downlink and uplink, respectively. Secondly, we propose an interference aware resource allocation for NB-IoT by formulating the rate maximization problem considering the overhead of control channels, time offset and repetition factor. Due to the complexity of finding the globally optimum solution of the formulated problem, a sub-optimal solution with an iterative algorithm based on cooperative approaches is proposed. The proposed algorithm is then evaluated to investigate the impact of repetition factor, time offset and ICI on the NB-IoT data rate and energy consumption. Furthermore, a detailed comparison between the non-cooperative, cooperative, and optimal scheme (i.e., no repetition) is also presented. It is shown through the simulation results that the cooperative scheme provides up to 8% rate improvement and 17% energy reduction as compared to the non-cooperative scheme.

Personalized content retrieval service has become a major information service that consumes a large portion of mobile Internet traffic. Joint content recommendation and delivery is a promising design philosophy that could effectively improve the overall user experience with personalized content retrieval services. Existing research mostly focused on a push-type design paradigm called proactive caching, which, however, has multiple inherent drawbacks such as high device cost and low energy efficiency. This paper proposes a novel, interactive joint content recommendation and delivery system as an alternative to overcome the drawbacks of proactive caching systems. We present several optimal and heuristic algorithms for the proposed system and analyze the system performance in terms of user interest and transmission outage probability. Some theoretical performance bounds of the system are also derived. The effectiveness of the proposed system and algorithms is validated by simulation results.

Device-to-Device (D2D) communications enable user equipments (UEs) in proximity to each other to exchange information by taking advantage of high data-rate and low energy consumption. When D2D transmissions share the radio resources with the cellular UEs, efficient admission control (AC) and radio resource allocation (RRA) strategies play a key-role in controlling the co-channel interference and allowing quality of service (QoS) provision to UEs. This paper proposes a novel joint AC and RRA strategy that provides long-term QoS support to cellular and D2D communications. The AC algorithm derives the best set of cellular and D2D links by maximizing the revenues of the service provider under QoS constraints. The RRA algorithm assigns the available channels and transmits powers to admitted users on the short-term, in order to maximize an average weighted sum-rate under the same QoS constraints of the AC. Due to the NP-hard nature of the optimization problem, we propose an AC greedy algorithm that achieves near-optimal results for reasonable numbers of D2D links. Then, we propose a low-complexity RRA algorithm that decouples channel and power allocation. Numerical results show that the proposed joint AC and RRA strategy outperforms existing frameworks by increasing up to 40% the number of satisfied cellular and D2D links and by reducing energy consumption by more than 50%.

Fifth Generation (5G) systems are expected to deploy massive Multiple Input Multiple Output (MIMO) antennas and operate with millimeter waves in order to support a significantly increasing data traffic. With more antennas and wider bandwidth, Channel Quality Indicator (CQI) estimation and reporting will be computationally demanding, increasing signaling between Base Stations (BSs) and User Equipments (UEs). In this context, the present thesis analyzes two strategies to address both problems: increasing data traffic and signaling. The first strategy is to exploit the reduction of channel fluctuations due to the use of narrow beams with large antenna arrays, i.e., the channel “hardens”. When this phenomenon happens, upper layer functions related to measurements can be optimized and signaling reduced. The second strategy concerns the adoption of a tight integration between 5G NR and LTE. More precisely, the UEs would be allowed to be simultaneously connected to both Radio Access Technologies (RATs), the so-called Dual Connectivity (DC). Before addressing these two strategies, we present an overview of the main 5G features used in this thesis and standardized in 3rd Generation Partnership Project (3GPP) specification release 15. After that, we present general analyses related to DC and Channel Hardening (CH) occurrence. Finally, we investigate these concepts from the perspective of Radio Resource Allocation (RRA). More specifically, frameworks related to CQI measurement and reporting based on CH occurrence are proposed. Besides, we also propose procedures for base station selection and resource assignment in a multi-RAT multi-connectivity system. Numerical analyses considering 5G system parameters are presented validating the proposed methods and showing that they improve system performance. Sistemas 5G serão baseados na implantação de largos conjuntos de antenas operando no espectro de ondas milimétricas para suportar o aumento significativo no tráfego de dados. Com mais antenas e maior largura de banda, a estimação da qualidade do canal e o envio dessas medidas do usuário para a estação rádio base serão processos computacionalmente mais complexos que os atuais e envolverão maior sinalização. Neste contexto, a presente tese analisa duas estratégias para tratar ambos os problemas: aumento de tráfego de dados e de sinalização. A primeira estratégia consiste em explorar a redução das flutuações do canal devido ao uso de feixes estreitos com largos conjuntos de antenas (o canal “endurece”). Quando este fenômeno ocorre, funções de camadas superiores baseadas em medições podem ser otimizadas. A segunda estratégia é relacionada à integração entre sistemas 5G e LTE. Mais precisamente, os usuários têm a capacidade de se conectarem simultaneamente a sistemas de ambas as tecnologias. Isto é chamado conexão dual. Antes de abordar essas duas estratégias, apresentamos uma visão geral das principais características do 5G usadas nessa tese e padronizadas pelas especificações do 3GPP versão 15. Depois disso, apresentamos análises gerais relacionadas à conexão dual e ao endurecimento do canal. Finalmente, investigamos esses dois conceitos da perspectiva da alocação de recursos de rádio. Mais especificamente, propomos soluções baseadas no endurecimento do canal e relacionadas à medição da qualidade do canal e ao envio destes dados. Além disso, também apresentamos soluções para seleção de estação rádio base e alocação de recursos em sistemas com múltiplas tecnologias e múltiplas conexões. Análises numéricas considerando parâmetros 5G são apresentadas para validar os métodos propostos.

Non-orthogonal multiple access based on superposition coding (SC) for 5G cellular systems without relays is gaining increasing interest from both academia and industries. Since relay stations will be an integral part of future cellular networks, we propose evolved non-orthogonal multi-access schemes for both direct and relayed users. Our schedulers are built upon SC-relaying schemes with practical discrete hierarchical modulations (HMs), where the messages of two selected users are superposed into different HM layers, each layer being allocated an optimized amount of power and bearing a message flow to be decoded through either a direct or relayed link. As opposed to conventional schedulers that allocate orthogonal resources to each user in wireless relaying systems, our non-orthogonal schedulers allow a pair of selected users to simultaneously share their allocated resource unit. Moreover, unlike the SC-relaying schemes in the literature based on Gaussian codebooks, the proposed schemes are designed and analyzed under the practical constraints of discrete HMs. In spite of the complexity of the power optimization under discrete HMs, we provide a simple and near-optimal power allocation method for sum-rate maximization and proportional fairness. The simulation results show that the conventional orthogonal schedulers are outperformed by the proposed schedulers in terms of sum rate and fairness, even under the practical assumption of HMs.

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.

International audience; The paper presents the studies that have been led toward the integration of device-to-device (D2D) communications within LTE networks in the frame of the project ACCENT5 (Advanced Waveforms, MAC Design and Dynamic Radio Resource Allocation for Device-to-Device in 5G Wireless Networks) supported by the French National Research Agency. The solutions presented in this paper cover several aspects of D2D communications; they are the result of a close cooperation between four partners Thales Communications and Security, CNAM, TeamCast and CentraleSupélec. Physical Layer aspects have been investigated, especially concerning waveforms envisioned for D2D communications within 5G networks. Also, a new MAC protocol has been designed to address the issues raised by the integration of D2D transmissions within LTE cells. The solution coming out of the study guarantees a minimum QoS for both types of users (D2D users and regular users) and aims at reusing spectrum while offloading the burden on the base station. © 2017 IEEE.

International audience; The paper presents the studies that have been led toward the integration of device-to-device (D2D) communications within LTE networks in the frame of the project ACCENTS (Advanced Waveforms, MAC Design and Dynamic Radio Resource Allocation for Device-to-Device in SG Wireless Networks) supported by the French National Research Agency. The solutions presented in this paper cover several aspects of D2D communications; they are the result of a close cooperation between four partners: Thales Communications and Security, CNAM, TeamCast and CentraleSupelec. Physical Layer aspects have been investigated, especially concerning waveforms envisioned for D2D communications within SG networks. Also, a new MAC protocol has been designed to address the issues raised by the integration of D2D transmissions within LTE cells. The solution coming out of the study guarantees a minimum QoS for both types of users (D2D users and regular users) and aims at reusing spectrum while offloading the burden on the base station.

Até 2020 espera-se que as redes celulares aumentam em dez vezes a área de cobertura, suporte cem vezes mais equipamentos de usuários e eleve a capacidade da taxa de dados em mil vezes, comparada as redes celulares atuais. A densa implantação de pequenas células é considerada uma solução promissora para alcançar essas melhorias, uma vez que aproximar as antenas dos usuários proporciona maiores taxas de dados, devido à qualidade do sinal em curtas distâncias. No entanto, operar um grande número de antenas pode aumentar significativamente o consumo de energia da infraestrutura de rede. Além disso, a grande inserção de novos rádios pode ocasionar maior interferência espectral entre as células. Nesse cenário, a gestão dos recursos de rádio é essencial devido ao impacto na qualidade do serviço prestado aos usuários. Por exemplo, baixas potências de transmissão podem deixar usuários sem conexão, enquanto altas potências elevam a possibilidade de ocorrência de interferência. Além disso, a reutilização não planejada dos recursos de rádio causa a ocorrência de interferência, resultando em baixa capacidade de transmissão, enquanto a subutilização de recursos limita a capacidade total de transmissão de dados. Uma solução para controlar a potência de transmissão, atribuir os recursos de rádio e garantir o serviço aos usuários é essencial. Nesta dissertação, é proposto um algoritmo adaptativo de Monte Carlo para realizar alocação global de recursos de forma eficiente em termos de energia, para arquiteturas Heterogeneous Cloud Radio Access Network (H-CRAN), projetadas como futuras redes de quinta geração (5G). Uma solução eficiente para a alocação de recursos em cenários de alta e baixa densidade é proposta. Nossas contribuições são triplas: (i) proposta de uma abordagem global para o problema de atribuição de recursos de rádio na arquitetura HCRAN, cujo caráter estocástico garante uma amostragem geral de espaço de solução; (ii) uma comparação crítica entre nossa solução global e um modelo local; (iii) a demonstração de que, para cenários de alta densidade, a Eficiência Energética não é uma medida adequada para alocação eficiente, considerando a capacidade de transmissão, justiça e total de usuários atendidos. Além disso, a proposta é comparada em relação a três algoritmos de alocação de recursos de última geração para redes 5G. Up until 2020 it is expected that cellular networks must raise the coverage area in 10-fold, support a 100-fold more user equipments, and increase the data rate capacity by a 1000-fold in comparison with current cellular networks. The dense deployment of small cells is considered a promising solution to reach such aggressive improvements, once it moves the antennas closer to the users, achieving higher data rates due to the signal quality at short distances. However, operating a massive number of antennas can significantly increase the energy consumption of the network infrastructure. Furthermore, the large insertion of new radios brings greater spectral interference between the cells. In this scenery, the optimal management of radio resources turn an exaction due to the impact on the quality of service provided to the users. For example, low transmission powers can leave users without connection, while high transmission powers can contribute to inter radios interference. Furthermore, the interference can be raised on the unplanned reuse of the radio resources, resulting in low data transmission per radio resource, as the under-reuse of radio resources limits the overall data transmission capacity. A solution to control the transmission power, assign the spectral radio resources, and ensure the service to the users is essential. In this thesis, we propose an Adaptive Monte Carlo algorithm to perform global energy efficient resource allocation for Heterogeneous Cloud Radio Access Network (HCRAN) architectures, which are forecast as future fifth-generation (5G) networks. We argue that our global proposal offers an efficient solution to the resource allocation for both high and low density scenarios. Our contributions are threefold: (i) the proposal of a global approach to the radio resource assignment problem in H-CRAN architecture, whose stochastic character ensures an overall solution space sampling; (ii) a critical comparison between our global solution and a local model; (iii) the demonstration that, for high density scenarios, Energy Efficiency is not a well suited metric for efficient allocation, considering data rate capacity, fairness, and served users. Moreover, we compare our proposal against three state-of-the-art resource allocation algorithms for 5G networks.

The enriched service scope, the steep increase in mobile traffic volume, and the ever increasing number of connected devices in mobile networks coupled with the scarcity of electromagnetic spectrum have raised the importance of designing flexible and ingenious means to guarantee high user satisfaction levels. Therefore, in order to capture and maintain a representative share of the wireless communication market, effective ways to manage the scarce physical resources of cellular networks are fundamental for cellular network operators. The Radio Resource Allo- cation (RRA) algorithms are responsible for performing such a relevant and arduous task. The efficiency of such algorithms is essential so that there exists a fair resource allocation among users and the Quality of Service (QoS) requirements of each individual user are met, thus guar- anteeing high user satisfaction levels. The recent scenarios of cellular networks are composed of a wide range of available services for mobile users, which demand conflicting QoS requirements. In order to achieve the objective of user satisfaction maximization in such networks, we formulate a utility-based cross-layer opti- mization problem targeted at maximizing the user satisfaction in multi-service cellular networks. The optimal solution of the proposed problem is very hard to be found. Thus, we mathematically manipulate the problem and derive a low complexity suboptimal solution from which we design an adaptive RRA technique. Our technique is composed of user weights and an innovative ser- vice weight that is adapted to meet the satisfaction target of the most prioritized service chosen by the network operator. Furthermore, the proposed algorithm is scalable to several classes of service and can be employed in the current and future generations of wireless systems. The performance evaluation of the proposed algorithm was conducted by means of system-level simulations in various scenarios. The evaluation was performed considering different multi- service scenarios. Then, the performance was evaluated considering imperfect Channel State Information (CSI) estimation at the transmitter. Significant gains in the overall system capacity were obtained in comparison with four benchmarking algorithms from the literature, demon- strating that the adaptability and service prioritization of the proposed algorithm are effective towards the objective of simultaneously maximizing the user satisfaction for multiple services. O escopo enriquecido de serviços, o aumento acentuado do volume de tráfego móvel e o nú- mero cada vez maior de dispositivos conectados nas redes móveis, acompanhado pela escassez do espectro eletromagnético, aumentaram a importância de projetar meios flexíveis e engenho- sos para garantir altos níveis de satisfação dos usuários. Portanto, para capturar e manter uma participação representativa no mercado das comunicações sem fio, mecanismos efetivos para gerenciar os recursos físicos escassos das redes celulares são fundamentais para as operadoras das redes celulares. Os algoritmos de alocação dos recursos de rádio (do inglês, Radio Resource Allocation (RRA)) são os responsáveis por executar essa tarefa tão relevante e árdua. A eficiên- cia desses algoritmos é essencial para que exista uma alocação justa de recursos entre os usuários e os requisitos individuais de qualidade de serviço (do inglês, Quality of Service (QoS)) de cada usuário sejam atendidos, garantindo assim altos níveis de satisfação dos usuários. Os cenários atuais das redes celulares são compostos por uma ampla gama de serviços disponí- veis para usuários móveis, que exigem requisitos de QoS conflitantes. Para alcançar o objetivo de maximizar a satisfação dos usuários nessas redes, formulamos um problema de otimização baseado na teoria da utilidade considerando múltiplas camadas que visa maximizar a satisfação dos usuários em redes celulares com múltiplos serviços. A solução ótima do problema proposto é muito difícil de ser encontrada. Dessa forma, nós manipulamos matematicamente o problema e derivamos uma solução subótima de baixa complexidade a partir da qual nós desenvolvemos um mecanismo adaptativo de RRA. Nosso mecanismo é composto por prioridades relacionadas aos usuários e uma inovadora prioridade relacionada ao serviço que é adaptada para atender um objetivo de satisfação dos usuários de um serviço com maior prioridade escolhido pela opera- dora da rede. Além disso, o algoritmo proposto é escalável para várias classes de serviço e pode ser empregado nas gerações atuais e futuras de sistemas celulares. A avaliação de desempenho do algoritmo proposto foi realizada por meio de simulações sistêmi- cas em vários cenários. A avaliação foi realizada considerando diferentes cenários com múltiplos serviços. Então, o desempenho foi avaliado considerando estimativa imperfeita da informação do estado de canal (do inglês, Channel State Information (CSI)) no transmissor. Ganhos signi- ficativos foram obtidos na capacidade total do sistema em comparação com quatro algoritmos encontrados da literatura, demonstrando que a adaptabilidade e priorização do serviço feita pelo algoritmo proposto são eficazes para atingir o objetivo de maximizar simultaneamente a satisfa- ção dos usuários para múltiplos serviços.

3GPP has recently introduced new features to the long term evolution (LTE) cellular technology enabling direct vehicle-to-vehicle (V2V) communications, also known as LTE-V2V. This new technology aims at supporting a large number of applications, most of them based on the broadcasting of periodic messages by all vehicles to inform the neighborhood about relevant information such as vehicle position, direction, and speed. Since resources are inevitably scarce and vehicles move relatively fast, the optimization of the LTE resource allocation represents a crucial topic of research. In this paper, we focus on network-controlled resource management based on the knowledge of the position of vehicles by the network and we propose an algorithm based on the concept of reuse distance. Apart from the ideal case where the position is perfectly estimated, the performance in terms of blocking rate, error rate and packet reception ratio is evaluated also in realistic cases where the position is known with some inaccuracy. In addition, a margin to the reuse distance is proposed to reach the maximum communication distance with a given quality of service. Results, obtained through simulations in a realistic highway scenario, show that there are minimum differences in terms of blocking rate between the different positioning errors, while there might be a significant worsening of the error rate. In addition, the use of an optimized margin is shown with the aim of improving the maximum communication distance of up to 20%.

Underlaying Device-to-Device (D2D) communications can increase the spectral efficiency of cellular networks when sharing part of the spectrum with cellular users. This requires radio resource allocation policies capable to limit and control the interference between D2D and cellular communications. Many of the proposed policies are centralized, and require the base station to decide which resources should be allocated to each D2D transmission. Centralized schemes can efficiently control interference levels, but their feasibility can be compromised by their complexity and signaling overhead. To address this constraint, this paper proposes DiRAT, a distributed radio resource allocation scheme for D2D communications underlaying cellular networks. With DiRAT, the D2D nodes locally select their radio resources from a pool created by the cellular network in order to control the interference generated to the primary cellular users. DiRAT includes a control mechanism to ensure that the user QoS requirements are satisfied. This study demonstrates that DiRAT can increase the network capacity while avoiding or limiting the degradation of the performance of the primary cellular users. DiRAT also significantly reduces the complexity and overhead compared to existing centralized and distributed schemes. This work was supported by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects TEC2014-57146-R This work was supported by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects TEC2014-56469-REDT This work was supported by Generalitat Valenciana under the project GV/2016/049

Device-to-Device (D2D) communications can increase the spectral efficiency of future cellular networks when sharing part of the cellular spectrum. Radio resource allocation mechanisms are then necessary to control the interference that D2D and cellular transmissions can generate to each other. Most of the existing allocation schemes rely on the knowledge of the channel gain of all possible links between cellular and D2D nodes. This paper proposes to reduce the complexity cost and signalling overhead of the allocation process by using location information available at the network level. Using this information, the base station assigns radio resources to new D2D transmissions with the objective to control and limit the interference to the primary cellular users and existing D2D transmissions. The proposed radio resource allocation scheme continuously monitors that the user QoS requirements are satisfied. If it is not the case, it dynamically modifies the resource allocation to the interfering D2D transmissions. The proposed scheme achieves performance levels similar to that obtained with an optimized centralized allocation scheme, but with a significantly lower complexity cost and signaling overhead This work has been supported in part by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects TEC2014-57146-R This work has been supported in part by the Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects TEC2014-56469-REDT This work has been supported by Generalitat Valenciana under the project GV/2016/049.

Vehicle-to-everything (V2X) communications may radically change the transportation system allowing a real-time and highly reliable exchange of information, which can be processed by vehicles in the neighborhood or by the road-side infrastructure to enable safety, mobility and environmental applications. In this context, 3GPP-based cellular networks, and especially long term evolution (LTE), are offering progressively higher performance and enabling a wider set of operations. To this aim, vehicle-to-vehicle (V2V) has been recently added as a new feature to LTE, but the usage of radio resources still needs to be optimized and is subject of extensive research activities. In this work, we focus on autonomous V2V resource reselection schemes, which allow communications also in out-of-coverage areas, we propose MAP-RP, a reselection procedure based on the embedding of a map of resources, as detected by each receiving vehicle, in the broadcasted packet, and we compare it to two sensing-based benchmark algorithms found in the literature. Results are achieved through simulations performed on a realistic highway scenario and demonstrate that the proposed solution guarantees a lower update delay and allows to achieve up to 20% of improvement in terms of packet reception ratio, with respect to the best-performing benchmark algorithm.

Cooperative awareness, consisting in the periodic broadcasting of messages, called beacons, to inform neighboring vehicles about maneuvers, changes of direction and other relevant mobility information, represents the core requirement to enable applications that may increase road safety and transportation efficiency. Up to few months ago, when latest 3GPP Release added to long term evolution (LTE) the support of vehicle-to-vehicle (V2V) communications, the only suitable standard was IEEE 802.11p in the U.S. and the corresponding ITS-G5 in Europe. The choice regarding the worldwide adoption of one of the two technologies is still under discussion, since both show advantages and drawbacks. In this work, we analyze IEEE 802.11p and LTE-V2V and evaluate their performance for the cooperative awareness service through simulations in a realistic highway scenario. Both in-coverage and out-of-coverage conditions are considered for LTE-V2V. Results reveal that LTE-V2V in-coverage is the best solution in terms of packet reception ratio for all the considered values of beacon size and communication range. As far as the beacon update delay is concerned, we observe that LTE-V2V in-coverage still provides the best performance when small packets are transmitted, while IEEE 802.11p gives the best results for values of the communication range higher than 100 m when the packet size is increased.

With the increasing needs of the automotive industry, 3GPP is developing new functionalities in the long term evolution (LTE) cellular technology to specifically address vehicle-to-everything (V2X) connectivity, including in particular vehicle-to-vehicle (V2V) direct communications. At the basis of most enabled applications, either dealing with safety, traffic management or infotainment, it is of particular importance the cooperative awareness service, corresponding to messages sent periodically in broadcast by all vehicles to inform about their status and intentions. To optimize the usage of radio resources, allocations of packets are required to be smartly performed, following algorithms that currently represent a challenging open issue. Having in mind to face the design and validation of resource allocation in LTE-V2V networks when cooperative awareness is addressed, we implemented a simulator, called LTEV2Vsim, which will be shared with all the interested researchers. LTEV2Vsim is written in MATLAB and manages vehicles mobility either following simple models or more complex and realistic input files, and performs allocations following different implemented algorithms, both network controlled and autonomous. Finally, to demonstrate the possibilities of LTEV2Vsim, some example results are provided.

The current trend towards heterogeneous networks requires some sort of self-organization capability, in terms of self-optimization and self-configuration. The basic steps enabling self-optimization typically require listening to the environment, learning and adapting resource allocation consequently. In this work, we propose a joint optimization of sensing parameters and radio resource allocation in order to maximize the opportunistic throughput, under the constraint of limiting undue interference towards primary users. The method applies to wireless networks where the sensing nodes are allowed to cooperate to improve their local decision capabilities using a fully decentralized approach based on distributed consensus. The proposed optimization maximizes the opportunistic throughput, taking into account decision errors, sensing time and time necessary to achieve a consensus over the sensed variables. Because of the lack of knowledge of the channel between the cognitive users and the macro-users, the interference constraint is formulated in probabilistic form, depending on the spatial distribution of the nodes and on the channel fading model. Our formulation allows us to find the optimal false alarm rate and, consequently, the optimal decision thresholds jointly with the optimal power/bit allocation. Finally, we show that, given a total power budget constraint, there is an optimal way of distributing the available power between the power spent to achieve consensus and the power spent for transmitting the data payload.

Device-to-Device communications have the great potential to bring significant performance boost to the conventional heterogeneous network by reusing cellular resources. In cellular networks, Device-to-Device communication is defined as two user equipments in a close range communicating directly with each other without going through the base station, thus offloading cellular traffic from cellular networks. In addition to improve network spectral efficiency, D2D communication can also improve energy efficiency and user experience. However, the co-existence of D2D communication on the same spectrum with cellular users can cause severe interference to the primary cellular users. Thus the performance of cellular users must be assured when supporting underlay D2D users. In this work, we have investigated cross-layer optimization, resource allocation and interference management schemes to improve user experience, system spectral efficiency and energy efficiency for D2D communication underlaying heterogeneous networks. By exploiting frequency reuse and multi-user diversity, this research work aims to design wireless system level algorithms to utilize the spectrum and energy resources efficiently in the next generation wireless heterogeneous network.

Optimized resource allocation of the Downlink (DL) in wireless systems utilizing Multi-Carrier (MC) transmission requires Channel State Information (CSI) feedback for each user/subchannel to the Base Station (BS), consuming a high amount of Uplink (UL) radio resources. To alleviate this problem, several works have considered contention-based CSI feedback in the UL control channel. We propose such a feedback scheme for a generic MC system, based on the idea of variable collision protection, where the probability that a feedback information experiences a collision depends on its importance. By partitioning the CSI into orthogonal layers of priority, and allocating different numbers of feedback slots to each layer, this scheme ensures that the feedback success probability is higher for the CSI with better quality, which is more likely to be used by the scheduler. Furthermore, we present a theoretical performance analysis of the proposed scheme, assuming Maximum CSI (Max CSI) and normalized Proportional Fair Scheduler (PFS), where a tight approximation of the achievable throughput is obtained assuming discrete Adaptive Modulation (AM) and CSI feedback which are relevant for the practical systems. Analytical and simulation results show that our proposed scheme provides an excellent trade-off between system performance and feedback overhead.

We consider Downlink (DL) scheduling for a multi-user cooperative cellular system with fixed relays. The conventional scheduling trend is to avoid interference by allocating orthogonal radio resources to each user, although simultaneous allocation of users on the same resource has been proven to be superior in, e.g., the broadcast channel. Therefore, we design a scheduler where in each frame, two selected relayed users are supported simultaneously through the Superposition Coding (SC) based scheme proposed in this paper. In this scheme, the messages destined to the two users are superposed in the modulation domain into three SC layers, allowing them to benefit from their high quality relayed links, thereby increasing the sum-rate. We derive the optimal power allocation over these three layers that maximizes the sum-rate under an equal rates' constraint. By integrating this scheme into the proposed scheduler, the simulation results show that our proposed SC scheduler provides high throughput and rate outage probability performance, indicating a significant fairness improvement. This validates the approach of simultaneous allocation versus orthogonal allocation in the cooperative cellular system.