Radio resource management for OFDMA systems under practical considerations.

Orthogonal frequency division multiple access (OFDMA) is used on the downlink of broadband wireless access (BWA) networks such as Worldwide Interoperability for Microwave Access (WiMAX) and Long Term Evolution (LTE) as it is able to offer substantial advantages such as combating channel impairments and supporting higher data rates. Also, by dynamically allocating subcarriers to users, frequency domain diversity as well as multiuser diversity can be effectively exploited so that performance can be greatly improved. The main focus of this thesis is on the development of practical resource allocation schemes for the OFDMA downlink. Imperfect Channel State Information (CSI), the limited capacity of the dedicated link used for CSI feedback, and the presence of a Connection Admission Control (CAC) unit are issues that are considered in this thesis to develop practical schemes. The design of efficient resource allocation schemes heavily depends on the CSI reported from the users to the transmitter. When the CSI is imperfect, a performance degradation is realized. It is therefore necessary to account for the imperfectness of the CSI when assigning radio resources to users. The first part of this thesis considers resource allocation strategies for OFDMA systems, where the transmitter only knows the statistical knowledge of the CSI (SCSI). The approach used shows that resources can be optimally allocated to achieve a performance that is comparable to that achieved when instantaneous CSI (ICSI) is available. The results presented show that the performance difference between the SCSI and ICSI based resource allocation schemes depends on the number of active users present in the cell, the Quality of Service (QoS) constraint, and the signal-to- noise ratio (SNR) per subcarrier. In practical systems only SCSI or CSI that is correlated to a certain extent with the true channel state can be used to perform resource allocation. An approach to quantifying the performance degradation for both cases is presented for the case where only a discrete number of modulation and coding levels are available for adaptive modulation and coding (AMC). Using the CSI estimates and the channel statistics, the approach can be used to perform resource allocation for both cases. It is shown that when a CAC unit is considered, CSI that is correlated with its present state leads to significantly higher values of the system throughput even under high user mobility. Motivated by the comparison between the correlated and statistical based resource allocation schemes, a strategy is then proposed which leads to a good tradeoff between overhead consumption and fairness as well as throughput when the presence of a CAC unit is considered. In OFDMA networks, the design of efficient CAC schemes also relies on the user CSI. The presence of a CAC unit needs to be considered when designing practical resource allocation schemes for BWA networks that support multiple service classes as it can guarantee fairness amongst them. In this thesis, a novel mechanism for CAC is developed which is based on the user channel gains and the cost of each service. This scheme divides the available bandwidth in accordance with a complete partitioning structure which allocates each service class an amount of non-overlapping bandwidth resource. In summary, the research results presented in this thesis contribute to the development of practical radio resource management schemes for BWA networks

Connection admission control and packet scheduling for IEEE 802.16 networks

Includes bibliographical references.The IEEE 802.16 standard introduced as one of the Wireless Metropolitan Area Networks (WMAN) for Broadband Wireless Access (BWA) which is known as Worldwide Interoperability for Microwave Access (WiMAX), provides a solution of broadband connectivity to areas where wired infrastructure is economically and technically infeasible. Apart from the advantage of having high speeds and low costs, IEEE 802.16 has the capability to simultaneously support various service types with required QoS characteristics. ... While IEEE 802.16 standard defines medium access control (MAC) and physical (PHY) layers specification, admission control and packet scheduling mechanisms which are important elements of QoS provisioning are left to vendors to design and implement for service differentiation and QoS support

An Innovative RAN Architecture for Emerging Heterogeneous Networks: The Road to the 5G Era

The global demand for mobile-broadband data services has experienced phenomenal growth over the last few years, driven by the rapid proliferation of smart devices such as smartphones and tablets. This growth is expected to continue unabated as mobile data traffic is predicted to grow anywhere from 20 to 50 times over the next 5 years. Exacerbating the problem is that such unprecedented surge in smartphones usage, which is characterized by frequent short on/off connections and mobility, generates heavy signaling traffic load in the network signaling storms . This consumes a disproportion amount of network resources, compromising network throughput and efficiency, and in extreme cases can cause the Third-Generation (3G) or 4G (long-term evolution (LTE) and LTE-Advanced (LTE-A)) cellular networks to crash. As the conventional approaches of improving the spectral efficiency and/or allocation additional spectrum are fast approaching their theoretical limits, there is a growing consensus that current 3G and 4G (LTE/LTE-A) cellular radio access technologies (RATs) won\u27t be able to meet the anticipated growth in mobile traffic demand. To address these challenges, the wireless industry and standardization bodies have initiated a roadmap for transition from 4G to 5G cellular technology with a key objective to increase capacity by 1000Ã? by 2020 . Even though the technology hasn\u27t been invented yet, the hype around 5G networks has begun to bubble. The emerging consensus is that 5G is not a single technology, but rather a synergistic collection of interworking technical innovations and solutions that collectively address the challenge of traffic growth. The core emerging ingredients that are widely considered the key enabling technologies to realize the envisioned 5G era, listed in the order of importance, are: 1) Heterogeneous networks (HetNets); 2) flexible backhauling; 3) efficient traffic offload techniques; and 4) Self Organizing Networks (SONs). The anticipated solutions delivered by efficient interworking/ integration of these enabling technologies are not simply about throwing more resources and /or spectrum at the challenge. The envisioned solution, however, requires radically different cellular RAN and mobile core architectures that efficiently and cost-effectively deploy and manage radio resources as well as offload mobile traffic from the overloaded core network. The main objective of this thesis is to address the key techno-economics challenges facing the transition from current Fourth-Generation (4G) cellular technology to the 5G era in the context of proposing a novel high-risk revolutionary direction to the design and implementation of the envisioned 5G cellular networks. The ultimate goal is to explore the potential and viability of cost-effectively implementing the 1000x capacity challenge while continuing to provide adequate mobile broadband experience to users. Specifically, this work proposes and devises a novel PON-based HetNet mobile backhaul RAN architecture that: 1) holistically addresses the key techno-economics hurdles facing the implementation of the envisioned 5G cellular technology, specifically, the backhauling and signaling challenges; and 2) enables, for the first time to the best of our knowledge, the support of efficient ground-breaking mobile data and signaling offload techniques, which significantly enhance the performance of both the HetNet-based RAN and LTE-A\u27s core network (Evolved Packet Core (EPC) per 3GPP standard), ensure that core network equipment is used more productively, and moderate the evolving 5G\u27s signaling growth and optimize its impact. To address the backhauling challenge, we propose a cost-effective fiber-based small cell backhaul infrastructure, which leverages existing fibered and powered facilities associated with a PON-based fiber-to-the-Node/Home (FTTN/FTTH)) residential access network. Due to the sharing of existing valuable fiber assets, the proposed PON-based backhaul architecture, in which the small cells are collocated with existing FTTN remote terminals (optical network units (ONUs)), is much more economical than conventional point-to-point (PTP) fiber backhaul designs. A fully distributed ring-based EPON architecture is utilized here as the fiber-based HetNet backhaul. The techno-economics merits of utilizing the proposed PON-based FTTx access HetNet RAN architecture versus that of traditional 4G LTE-A\u27s RAN will be thoroughly examined and quantified. Specifically, we quantify the techno-economics merits of the proposed PON-based HetNet backhaul by comparing its performance versus that of a conventional fiber-based PTP backhaul architecture as a benchmark. It is shown that the purposely selected ring-based PON architecture along with the supporting distributed control plane enable the proposed PON-based FTTx RAN architecture to support several key salient networking features that collectively significantly enhance the overall performance of both the HetNet-based RAN and 4G LTE-A\u27s core (EPC) compared to that of the typical fiber-based PTP backhaul architecture in terms of handoff capability, signaling overhead, overall network throughput and latency, and QoS support. It will also been shown that the proposed HetNet-based RAN architecture is not only capable of providing the typical macro-cell offloading gain (RAN gain) but also can provide ground-breaking EPC offloading gain. The simulation results indicate that the overall capacity of the proposed HetNet scales with the number of deployed small cells, thanks to LTE-A\u27s advanced interference management techniques. For example, if there are 10 deployed outdoor small cells for every macrocell in the network, then the overall capacity will be approximately 10-11x capacity gain over a macro-only network. To reach the 1000x capacity goal, numerous small cells including 3G, 4G, and WiFi (femtos, picos, metros, relays, remote radio heads, distributed antenna systems) need to be deployed indoors and outdoors, at all possible venues (residences and enterprises)

A multi-traffic inter-cell interference coordination scheme in dense cellular networks

This paper proposes a novel semi-distributed and practical ICIC scheme based on the Almost Blank Sub-Frame (ABSF) approach specified by 3GPP. We define two mathematical programming problems for the cases of guaranteed and best-effort traffic, and use game theory to study the properties of the derived ICIC distributed schemes, which are compared in detail against unaffordable centralized schemes. Based on the analysis of the proposed models, we define Distributed Multi-traffic Scheduling (DMS), a unified distributed framework for adaptive interference-aware scheduling of base stations in future cellular networks, which accounts for both guaranteed and best-effort traffic. DMS follows a two-tier approach, consisting of local ABSF schedulers, which perform the resource distribution between the guaranteed and best effort traffic, and a light-weight local supervisor, which coordinates ABSF local decisions. As a result of such a two-tier design, DMS requires very light signaling to drive the local schedulers to globally efficient operating points. As shown by means of numerical results, DMS allows to: (i) maximize radio resources resue; (ii) provide requested quality for guaranteed traffic; (iii) minimize the time dedicated to guaranteed traffic to leave room for best-effort traffic; and (iv) maximize resource utilization efficiency for the best-effort traffic.The work of A. Banchs was supported by the H2020 5GMoNArch project (Grant Agreement No. 761445) and the 5GCity project of the Spanish Ministry of Economy and Competitiveness (TEC2016-76795-C6-3-R). The work of V. Mancuso has been supported by a Ramon y Cajal grant (ref: RYC-2014-16285) in part by the Spanish Ministry of Science, Innovation and Universities under grant TIN2017-88749-R and by the Madrid Regional Government through the TIGRE5-CM program (S2013/ICE-2919)

Resource Allocation and Service Management in Next Generation 5G Wireless Networks

The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

Modelling and Optimisation of GSM and UMTS Radio Access Networks

The size and complexity of mobile communication networks have increased in the last years making network management a very complicated task. GSM/EDGE Radio Access Network (GERAN) systems are in a mature state now. Thus, non-optimal performance does not come from typical network start-up problems, but, more likely, from the mismatching between traffic, network or propagation models used for network planning, and their real counterparts. Such differences cause network congestion problems both in signalling and data channels. With the aim of maximising the financial benefits on their mature networks, operators do not solve anymore congestion problems by adding new radio resources, as they usually did. Alternatively, two main strategies can be adopted, a) a better assignment of radio resources through a re-planning approach, and/or b) the automatic configuration (optimisation, in a wide sense) of network parameters. Both techniques aim to adapt the network to the actual traffic and propagation conditions. Moreover, a new heterogenous scenario, where several services and Radio Access Technologies (RATs) coexist in the same area, is now common, causing new unbalanced traffic scenarios and congestion problems. In this thesis, several optimisation and modelling methods are proposed to solve congestion problems in data and signalling channels for single- and multi-RAT scenarios

Joint access-backhaul mechanisms in 5G cell-less architectures

Older generations of wireless networks, such as 1G and 2G were deployed using leased line, copper or fibre line as backhaul. Later, in 3G and 4G, microwave wireless links have also worked as backhaul links while the backbone of the network was still wireline-based. However, due to multiple different use cases and deployment scenarios of 5G, solo wireline based backhaul network is not a cost-efficient option for the operators anymore. For cost-efficient and fast deployment, wireless backhaul options are very attractive. As drawbacks, wireless backhaul links have capacity and distance limitations. To take the advantages of both the solutions, i.e., wired and wireless, 5G transport networks are anticipated to be a heterogeneous, complex, and with stringent performance requirements. To address the aforementioned challenges, wireless backhaul options are providing more attractive solutions, and hence, technologies using the same resources (e.g., frequency channels) may be used by both access and backhaul networks. In this scenario, blurring the separation line between access and backhaul networks allows resource sharing and cooperation between both the networks and minimizes the network deployment and maintenance cost significantly. Therefore, in 5G, the access and backhaul networks cannot be seen as separate entities; rather, we seek to integrate them together to ensure the best use of resources. In this thesis, firstly, we investigate the challenges and potential technologies of 5G transport network. Later, to address these challenges, we identify and present different approaches to perform joint access-backhaul mechanism. An initial performance evaluation of access-aware backhaul optimization is presented, where backhaul network is dynamically assigned with the required resources to serve the dynamic requirements of a 5G access network. The evaluation results and discussions manifest the resource efficiency of joint access-backhaul mechanisms. Functional splits in different layers of the access network comes as an intelligent solution to reduce the enormous capacity requirements of the transport network in a centralized radio access network approach, which tends to centralize almost all the functionalities into a central unit, leaving only radio frequency functions at the access points. From the joint access-backhaul mechanism perspective, we propose a novel technique, which takes the benefit of functional splits at physical layer, to design a heterogeneous transport network in an economical budget-limited and capacity-limited scenario. Till today, the limited capacity of the wireless backhaul links remains a challenge, and hence, frequency spectrum becomes scarce, and requires efficient utilization. To address this challenge, a joint spectrum sharing technique to implement joint accessbackhaul mechanism is presented. Evaluation results show that our proposed joint spectrum sharing technique, where spectrum allocation in the backhaul network follows the access network's traffic load, is fair and efficient in terms of spectrum utilization. We also propose a machine learning technique, which analyses data from a real network and estimates access network's traffic pattern, and subsequently, assigns bandwidth in the access network according to the traffic estimations. Presented evaluation results show that a well-trained machine learning model can be very efficient to obtain an efficient utilization of frequency spectrum.Las primeras generaciones de redes móviles, se implementaron utilizando líneas de cobre o fibra para la conexión entre la red de acceso y el núcleo de la red (conexión backhaul). Más tarde, los enlaces inalámbricos también han funcionado como backhaul mientras que la columna vertebral de la red seguía basada en cable. Sin embargo, debido a los múltiples escenarios de implementación de 5G, una red de backhaul basada solamente en cable ya no es una opción rentable para los operadores. Para una implementación rentable y rápida, las opciones de backhaul inalámbrico son muy atractivas. Como inconvenientes, los enlaces backhaul inalámbricos tienen limitaciones de capacidad y distancia. Para aprovechar las ventajas de ambas soluciones, es decir, cableadas e inalámbricas, se prevé que las redes de transporte 5G sean heterogéneas, complejas y con estrictos requisitos de rendimiento. Para abordar los desafíos antes mencionados, las opciones de backhaul inalámbrico brindan soluciones más atractivas y, por lo tanto, las tecnologías que usan los mismos recursos (por ejemplo, canales de frecuencia) pueden usarse tanto en las redes de acceso como en las de backhaul. En este escenario, desdibujar la línea de separación entre las redes de acceso y backhaul permite el intercambio de recursos y la cooperación entre ambas redes, y minimiza significativamente los costes de implementación y mantenimiento de la red. Por lo tanto, en 5G las redes de acceso y backhaul no pueden verse como entidades separadas; más bien consideraremos su integración para asegurar el mejor uso de los recursos. En esta tesis, en primer lugar, investigamos los desafíos y las tecnologías potenciales para la implementación de la red de backhaul 5G. Más tarde, para abordar dichos desafíos, identificamos diferentes enfoques para un mecanismo conjunto de gestión de la red de acceso y backhaul. Se presenta una evaluación de rendimiento inicial para la optimización de backhaul que tiene en cuenta el estado de la red de acceso, donde la red de backhaul se equipa dinámicamente con los recursos necesarios para cumplir con los requisitos de la red de acceso 5G. Los resultados de la evaluación manifiestan la mayor eficiencia de los mecanismos de gestión de recursos que consideran redes de acceso y backhaul conjuntamente. Las divisiones funcionales en diferentes capas de la red de acceso (functional splits) se presentan como una solución inteligente para reducir los enormes requisitos de capacidad de la red de transporte en un enfoque de red de acceso, que tiende a centralizar casi todas las funcionalidades en una unidad central, dejando solo las funciones más relacionadas con la transmisión/recepción de señales en los puntos de acceso. Desde la perspectiva del mecanismo conjunto de red de acceso y backhaul, proponemos una técnica novedosa, que aprovecha las divisiones funcionales en la capa física para diseñar una red de transporte heterogénea con un presupuesto económico y un escenario de capacidad limitada. Hasta el día de hoy, la capacidad limitada de los enlaces inalámbricos sigue siendo un desafío, dado que el espectro de frecuencias es escaso y requiere una utilización eficiente. Para hacer frente a este desafío, se presenta una técnica de gestión de recursos espectrales compartidos entre red de acceso y backhaul. Los resultados de la evaluación muestran que nuestra propuesta, donde la asignación de espectro en la red de backhaul se hace de acuerdo a la carga de tráfico de la red de acceso, es justa y eficiente. También proponemos una técnica de aprendizaje automático, que analiza datos de una red real y estima el patrón de tráfico de la red de acceso para, posteriormente, asignar ancho de banda en la red de acceso de acuerdo con dichas estimaciones. Los resultados de la evaluación presentados muestran que un modelo de aprendizaje automático bien entrenado puede ser una herramienta muy útil a la hora de obtener una utilización eficiente del espectro de frecuencias.Postprint (published version

Lightweight mobile and wireless systems: technologies, architectures, and services

1Department of Information and Communication Systems Engineering (ICSE), University of the Aegean, 81100 Mytilene, Greece 2Department of Information Engineering and Computer Science (DISI), University of Trento, 38123 Trento, Italy 3Department of Informatics, Alexander Technological Educational Institute of Thessaloniki, Thessaloniki, 574 00 Macedonia, Greece 4Centre Tecnologic de Telecomunicacions de Catalunya (CTTC), 08860 Barcelona, Spain 5North Carolina State University (NCSU), Raleigh, NC 27695, US