D2D-Based Grouped Random Access to Mitigate Mobile Access Congestion in 5G Sensor Networks

The Fifth Generation (5G) wireless service of sensor networks involves significant challenges when dealing with the coordination of ever-increasing number of devices accessing shared resources. This has drawn major interest from the research community as many existing works focus on the radio access network congestion control to efficiently manage resources in the context of device-to-device (D2D) interaction in huge sensor networks. In this context, this paper pioneers a study on the impact of D2D link reliability in group-assisted random access protocols, by shedding the light on beneficial performance and potential limitations of approaches of this kind against tunable parameters such as group size, number of sensors and reliability of D2D links. Additionally, we leverage on the association with a Geolocation Database (GDB) capability to assist the grouping decisions by drawing parallels with recent regulatory-driven initiatives around GDBs and arguing benefits of the suggested proposal. Finally, the proposed method is approved to significantly reduce the delay over random access channels, by means of an exhaustive simulation campaign.Comment: First submission to IEEE Communications Magazine on Oct.28.2017. Accepted on Aug.18.2019. This is the camera-ready versio

Enhanced mobility management mechanisms for 5G networks

Many mechanisms that served the legacy networks till now, are being identified as being grossly sub-optimal for 5G networks. The reason being, the increased complexity of the 5G networks compared previous legacy systems. One such class of mechanisms, important for any wireless standard, is the Mobility Management (MM) mechanisms. MM mechanismsensure the seamless connectivity and continuity of service for a user when it moves away from the geographic location where it initially got attached to the network. In this thesis, we firstly present a detailed state of the art on MM mechanisms. Based on the 5G requirements as well as the initial discussions on Beyond 5G networks, we provision a gap analysis for the current technologies/solutions to satisfy the presented requirements. We also define the persistent challenges that exist concerning MM mechanisms for 5G and beyond networks. Based on these challenges, we define the potential solutions and a novel framework for the 5G and beyond MM mechanisms. This framework specifies a set of MM mechanisms at the access, core and the extreme edge network (users/devices) level, that will help to satisfy the requirements for the 5G and beyond MM mechanisms. Following this, we present an on demand MM service concept. Such an on-demand feature provisions the necessary reliability, scalability and flexibility to the MM mechanisms. It's objective is to ensure that appropriate resources and mobility contexts are defined for users who will have heterogeneous mobility profiles, versatile QoS requirements in a multi-RAT network. Next, in this thesis we tackle the problem of core network signaling that occurs during MM in 5G/4G networks. A novel handover signaling mechanism has been developed, which eliminates unnecessary handshakes during the handover preparation phase, while allowing the transition to future softwarized network architectures. We also provide a handover failure aware handover preparation phase signaling process. We then utilize operator data and a realistic network deployment to perform a comparative analysis of the proposed strategy and the 3GPP handover signaling strategy on a network wide deployment scenario. We show the benefits of our strategy in terms of latency of handover process, and the transmission and processing cost incurred. Lastly, a novel user association and resource allocation methodology, namely AURA-5G, has been proposed. AURA-5G addresses scenarios wherein applications with heterogeneous requirements, i.e., enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC), are present simultaneously. Consequently, a joint optimization process for performing the user association and resource allocation while being cognizant of heterogeneous application requirements, has been performed. We capture the peculiarities of this important mobility management process through the various constraints, such as backhaul requirements, dual connectivity options, available access resources, minimum rate requirements, etc., that we have imposed on a Mixed Integer Linear Program (MILP). The objective function of this established MILP problem is to maximize the total network throughput of the eMBB users, while satisfying the minimum requirements of the mMTC and eMBB users defined in a given scenario. Through numerical evaluations we show that our approach outperforms the baseline user association scenario significantly. Moreover, we have presented a system fairness analysis, as well as a novel fidelity and computational complexity analysis for the same, which express the utility of our methodology given the myriad network scenarios.Muchos mecanismos que sirvieron en las redes actuales, se están identificando como extremadamente subóptimos para las redes 5G. Esto es debido a la mayor complejidad de las redes 5G. Un tipo de mecanismo importante para cualquier estándar inalámbrico, consiste en el mecanismo de gestión de la movilidad (MM). Los mecanismos MM aseguran la conectividad sin interrupciones y la continuidad del servicio para un usuario cuando éste se aleja de la ubicación geográfica donde inicialmente se conectó a la red. En esta tesis, presentamos, en primer lugar, un estado del arte detallado de los mecanismos MM. Bas ándonos en los requisitos de 5G, así como en las discusiones iniciales sobre las redes Beyond 5G, proporcionamos un análisis de las tecnologías/soluciones actuales para satisfacer los requisitos presentados. También definimos los desafíos persistentes que existen con respecto a los mecanismos MM para redes 5G y Beyond 5G. En base a estos desafíos, definimos las posibles soluciones y un marco novedoso para los mecanismos 5G y Beyond 5G de MM. Este marco especifica un conjunto de mecanismos MM a nivel de red acceso, red del núcleo y extremo de la red (usuarios/dispositivos), que ayudarán a satisfacer los requisitos para los mecanismos MM 5G y posteriores. A continuación, presentamos el concepto de servicio bajo demanda MM. Tal característica proporciona la confiabilidad, escalabilidad y flexibilidad necesarias para los mecanismos MM. Su objetivo es garantizar que se definan los recursos y contextos de movilidad adecuados para los usuarios que tendrán perfiles de movilidad heterogéneos, y requisitos de QoS versátiles en una red multi-RAT. Más adelante, abordamos el problema de la señalización de la red troncal que ocurre durante la gestión de la movilidad en redes 5G/4G. Se ha desarrollado un nuevo mecanismo de señalización de handover, que elimina los intercambios de mensajes innecesarios durante la fase de preparación del handover, al tiempo que permite la transición a futuras arquitecturas de red softwarizada. Utilizamos los datos de operadores y consideramos un despliegue de red realista para realizar un análisis comparativo de la estrategia propuesta y la estrategia de señalización de 3GPP. Mostramos los beneficios de nuestra estrategia en términos de latencia del proceso de handover y los costes de transmisión y procesado. Por último, se ha propuesto una nueva asociación de usuarios y una metodología de asignación de recursos, i.e, AURA-5G. AURA-5G aborda escenarios en los que las aplicaciones con requisitos heterogéneos, i.e., enhanced Mobile Broadband (eMBB) y massive Machine Type Communications (mMTC), están presentes simultáneamente. En consecuencia, se ha llevado a cabo un proceso de optimización conjunta para realizar la asociación de usuarios y la asignación de recursos mientras se tienen en cuenta los requisitos de aplicaciónes heterogéneas. Capturamos las peculiaridades de este importante proceso de gestión de la movilidad a través de las diversas restricciones impuestas, como son los requisitos de backhaul, las opciones de conectividad dual, los recursos de la red de acceso disponibles, los requisitos de velocidad mínima, etc., que hemos introducido en un Mixed Integer Linear Program (MILP). La función objetivo de este problema MILP es maximizar el rendimiento total de la red de los usuarios de eMBB, y a la vez satisfacer los requisitos mínimos de los usuarios de mMTC y eMBB definidos en un escenario dado. A través de evaluaciones numéricas, mostramos que nuestro enfoque supera significativamente el escenario de asociación de usuarios de referencia. Además, hemos presentado un análisis de la justicia del sistema, así como un novedoso análisis de fidelidad y complejidad computacional para el mismo, que expresa la utilidad de nuestra metodología.Postprint (published version

Enhanced mobility management mechanisms for 5G networks

Many mechanisms that served the legacy networks till now, are being identified as being grossly sub-optimal for 5G networks. The reason being, the increased complexity of the 5G networks compared previous legacy systems. One such class of mechanisms, important for any wireless standard, is the Mobility Management (MM) mechanisms. MM mechanismsensure the seamless connectivity and continuity of service for a user when it moves away from the geographic location where it initially got attached to the network. In this thesis, we firstly present a detailed state of the art on MM mechanisms. Based on the 5G requirements as well as the initial discussions on Beyond 5G networks, we provision a gap analysis for the current technologies/solutions to satisfy the presented requirements. We also define the persistent challenges that exist concerning MM mechanisms for 5G and beyond networks. Based on these challenges, we define the potential solutions and a novel framework for the 5G and beyond MM mechanisms. This framework specifies a set of MM mechanisms at the access, core and the extreme edge network (users/devices) level, that will help to satisfy the requirements for the 5G and beyond MM mechanisms. Following this, we present an on demand MM service concept. Such an on-demand feature provisions the necessary reliability, scalability and flexibility to the MM mechanisms. It's objective is to ensure that appropriate resources and mobility contexts are defined for users who will have heterogeneous mobility profiles, versatile QoS requirements in a multi-RAT network. Next, in this thesis we tackle the problem of core network signaling that occurs during MM in 5G/4G networks. A novel handover signaling mechanism has been developed, which eliminates unnecessary handshakes during the handover preparation phase, while allowing the transition to future softwarized network architectures. We also provide a handover failure aware handover preparation phase signaling process. We then utilize operator data and a realistic network deployment to perform a comparative analysis of the proposed strategy and the 3GPP handover signaling strategy on a network wide deployment scenario. We show the benefits of our strategy in terms of latency of handover process, and the transmission and processing cost incurred. Lastly, a novel user association and resource allocation methodology, namely AURA-5G, has been proposed. AURA-5G addresses scenarios wherein applications with heterogeneous requirements, i.e., enhanced Mobile Broadband (eMBB) and massive Machine Type Communications (mMTC), are present simultaneously. Consequently, a joint optimization process for performing the user association and resource allocation while being cognizant of heterogeneous application requirements, has been performed. We capture the peculiarities of this important mobility management process through the various constraints, such as backhaul requirements, dual connectivity options, available access resources, minimum rate requirements, etc., that we have imposed on a Mixed Integer Linear Program (MILP). The objective function of this established MILP problem is to maximize the total network throughput of the eMBB users, while satisfying the minimum requirements of the mMTC and eMBB users defined in a given scenario. Through numerical evaluations we show that our approach outperforms the baseline user association scenario significantly. Moreover, we have presented a system fairness analysis, as well as a novel fidelity and computational complexity analysis for the same, which express the utility of our methodology given the myriad network scenarios.Muchos mecanismos que sirvieron en las redes actuales, se están identificando como extremadamente subóptimos para las redes 5G. Esto es debido a la mayor complejidad de las redes 5G. Un tipo de mecanismo importante para cualquier estándar inalámbrico, consiste en el mecanismo de gestión de la movilidad (MM). Los mecanismos MM aseguran la conectividad sin interrupciones y la continuidad del servicio para un usuario cuando éste se aleja de la ubicación geográfica donde inicialmente se conectó a la red. En esta tesis, presentamos, en primer lugar, un estado del arte detallado de los mecanismos MM. Bas ándonos en los requisitos de 5G, así como en las discusiones iniciales sobre las redes Beyond 5G, proporcionamos un análisis de las tecnologías/soluciones actuales para satisfacer los requisitos presentados. También definimos los desafíos persistentes que existen con respecto a los mecanismos MM para redes 5G y Beyond 5G. En base a estos desafíos, definimos las posibles soluciones y un marco novedoso para los mecanismos 5G y Beyond 5G de MM. Este marco especifica un conjunto de mecanismos MM a nivel de red acceso, red del núcleo y extremo de la red (usuarios/dispositivos), que ayudarán a satisfacer los requisitos para los mecanismos MM 5G y posteriores. A continuación, presentamos el concepto de servicio bajo demanda MM. Tal característica proporciona la confiabilidad, escalabilidad y flexibilidad necesarias para los mecanismos MM. Su objetivo es garantizar que se definan los recursos y contextos de movilidad adecuados para los usuarios que tendrán perfiles de movilidad heterogéneos, y requisitos de QoS versátiles en una red multi-RAT. Más adelante, abordamos el problema de la señalización de la red troncal que ocurre durante la gestión de la movilidad en redes 5G/4G. Se ha desarrollado un nuevo mecanismo de señalización de handover, que elimina los intercambios de mensajes innecesarios durante la fase de preparación del handover, al tiempo que permite la transición a futuras arquitecturas de red softwarizada. Utilizamos los datos de operadores y consideramos un despliegue de red realista para realizar un análisis comparativo de la estrategia propuesta y la estrategia de señalización de 3GPP. Mostramos los beneficios de nuestra estrategia en términos de latencia del proceso de handover y los costes de transmisión y procesado. Por último, se ha propuesto una nueva asociación de usuarios y una metodología de asignación de recursos, i.e, AURA-5G. AURA-5G aborda escenarios en los que las aplicaciones con requisitos heterogéneos, i.e., enhanced Mobile Broadband (eMBB) y massive Machine Type Communications (mMTC), están presentes simultáneamente. En consecuencia, se ha llevado a cabo un proceso de optimización conjunta para realizar la asociación de usuarios y la asignación de recursos mientras se tienen en cuenta los requisitos de aplicaciónes heterogéneas. Capturamos las peculiaridades de este importante proceso de gestión de la movilidad a través de las diversas restricciones impuestas, como son los requisitos de backhaul, las opciones de conectividad dual, los recursos de la red de acceso disponibles, los requisitos de velocidad mínima, etc., que hemos introducido en un Mixed Integer Linear Program (MILP). La función objetivo de este problema MILP es maximizar el rendimiento total de la red de los usuarios de eMBB, y a la vez satisfacer los requisitos mínimos de los usuarios de mMTC y eMBB definidos en un escenario dado. A través de evaluaciones numéricas, mostramos que nuestro enfoque supera significativamente el escenario de asociación de usuarios de referencia. Además, hemos presentado un análisis de la justicia del sistema, así como un novedoso análisis de fidelidad y complejidad computacional para el mismo, que expresa la utilidad de nuestra metodología

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Self-organised multi-objective network clustering for coordinated communications in future wireless networks

The fifth generation (5G) cellular system is being developed with a vision of 1000 times more capacity than the fourth generation (4G) systems to cope with ever increasing mobile data traffic. Interference mitigation plays an important role in improving the much needed overall capacity especially in highly interference-limited dense deployment scenarios envisioned for 5G. Coordinated multi-point (CoMP) is identified as a promising interference mitigation technique where multiple base stations (BS) can cooperate for joint transmission/reception by exchanging user/control data and perform joint signal processing to mitigate inter-cell interference and even exploit it as a useful signal. CoMP is already a key feature of long term evolution-advanced (LTE-A) and envisioned as an essential function for 5G. However, CoMP cannot be realized for the whole network due to its computational complexity, synchronization requirement between coordinating BSs and high backhaul capacity requirement. BSs need to be clustered into smaller groups and CoMP can be activated within these smaller clusters. This PhD thesis aims to investigate optimum dynamic CoMP clustering solutions in 5G and beyond wireless networks with massive small cell (SC) deployment. Truly self-organised CoMP clustering algorithms are investigated, aiming to improve much needed spectral efficiency and other network objectives especially load balancing in future wireless networks. Low complexity, scalable, stable and efficient CoMP clustering algorithms are designed to jointly optimize spectral efficiency, load balancing and limited backhaul availability. Firstly, we provide a self organizing, load aware, user-centric CoMP clustering algorithm in a control and data plane separation architecture (CDSA) proposed for 5G to maximize spectral efficiency and improve load balancing. We introduce a novel re-clustering algorithm for user equipment (UE) served by highly loaded cells and show that unsatisfied UEs due to high load can be significantly reduced with minimal impact on spectral efficiency. Clustering with load balancing algorithm exploits the capacity gain from increase in cluster size and also the traffic shift from highly loaded cells to lightly loaded neighbours. Secondly, we develop a novel, low complexity, stable, network-centric clustering model to jointly optimize load balancing and spectral efficiency objectives and tackle the complexity and scalability issues of user-centric clustering. We show that our clustering model provide high spectral efficiency in low-load scenario and better load distribution in high-load scenario resulting in lower number of unsatisfied users while keeping spectral efficiency at comparably high levels. Unsatisfied UEs due to high load are reduced by $68.5\%$ with our algorithm when compared to greedy clustering model. In this context, the unique contribution of this work that it is the first attempt to fill the gap in literature for multi-objective, network-centric CoMP clustering, jointly optimizing load balancing and spectral efficiency. Thirdly, we design a novel multi-objective CoMP clustering algorithm to include backhaul-load awareness and tackle one of the biggest challenges for the realization of CoMP in future networks i.e. the demand for high backhaul bandwidth and very low latency. We fill the gap in literature as the first attempt to design a clustering algorithm to jointly optimize backhaul/radio access load and spectral efficiency and analyze the trade-off between them. We employ 2 novel coalitional game theoretic clustering methods, 1-a novel merge/split/transfer coalitional game theoretic clustering algorithm to form backhaul and load aware BS clusters where spectral efficiency is still kept at high level, 2-a novel user transfer game model to move users between clusters to improve load balancing further. Stability and complexity analysis is provided and simulation results are presented to show the performance of the proposed method under different backhaul availability scenarios. We show that average system throughout is increased by 49.9% with our backhaul-load aware model in high load scenario when compared to a greedy model. Finally, we provide an operator's perspective on deployment of CoMP. Firstly, we present the main motivation and benefits of CoMP from an operator's viewpoint. Next, we present operational requirements for CoMP implementation and discuss practical considerations and challenges of such deployment. Possible solutions for these experienced challenges are reviewed. We then present initial results from a UL CoMP trial and discuss changes in key network performance indicators (KPI) during the trial. Additionally, we propose further improvements to the trialed CoMP scheme for better potential gains and give our perspective on how CoMP will fit into the future wireless networks