Formulation, implementation considerations, and first performance evaluation of algorithmic solutions - D4.1

Deliverable D4.1 del projecte Europeu OneFIT (ICT-2009-257385)This deliverable contains a first version of the algorithmic solutions for enabling opportunistic networks. The presented algorithms cover the full range of identified management tasks: suitability, creation, QoS control, reconfiguration and forced terminations. Preliminary evaluations complement the proposed algorithms. Implementation considerations towards the practicality of the considered algorithms are also included.Preprin

Eficiência energética avançada para sistema OFDMA CoMP coordenação multiponto

Doutoramento em Engenharia EletrotécnicaThe ever-growing energy consumption in mobile networks stimulated by the expected growth in data tra ffic has provided the impetus for mobile operators to refocus network design, planning and deployment towards reducing the cost per bit, whilst at the same time providing a signifi cant step towards reducing their operational expenditure. As a step towards incorporating cost-eff ective mobile system, 3GPP LTE-Advanced has adopted the coordinated multi-point (CoMP) transmission technique due to its ability to mitigate and manage inter-cell interference (ICI). Using CoMP the cell average and cell edge throughput are boosted. However, there is room for reducing energy consumption further by exploiting the inherent exibility of dynamic resource allocation protocols. To this end packet scheduler plays the central role in determining the overall performance of the 3GPP longterm evolution (LTE) based on packet-switching operation and provide a potential research playground for optimizing energy consumption in future networks. In this thesis we investigate the baseline performance for down link CoMP using traditional scheduling approaches, and subsequently go beyond and propose novel energy e fficient scheduling (EES) strategies that can achieve power-e fficient transmission to the UEs whilst enabling both system energy effi ciency gain and fairness improvement. However, ICI can still be prominent when multiple nodes use common resources with di fferent power levels inside the cell, as in the so called heterogeneous networks (Het- Net) environment. HetNets are comprised of two or more tiers of cells. The rst, or higher tier, is a traditional deployment of cell sites, often referred to in this context as macrocells. The lower tiers are termed small cells, and can appear as microcell, picocells or femtocells. The HetNet has attracted signiffi cant interest by key manufacturers as one of the enablers for high speed data at low cost. Research until now has revealed several key hurdles that must be overcome before HetNets can achieve their full potential: bottlenecks in the backhaul must be alleviated, as well as their seamless interworking with CoMP. In this thesis we explore exactly the latter hurdle, and present innovative ideas on advancing CoMP to work in synergy with HetNet deployment, complemented by a novel resource allocation policy for HetNet tighter interference management. As system level simulator has been used to analyze the proposed algorithm/protocols, and results have concluded that up to 20% energy gain can be observed.O aumento do consumo de energia nas TICs e em particular nas redes de comunicação móveis, estimulado por um crescimento esperado do tráfego de dados, tem servido de impulso aos operadores m oveis para reorientarem os seus projectos de rede, planeamento e implementa ção no sentido de reduzir o custo por bit, o que ao mesmo tempo possibilita um passo signicativo no sentido de reduzir as despesas operacionais. Como um passo no sentido de uma incorporação eficaz em termos destes custos, o sistema móvel 3GPP LTE-Advanced adoptou a técnica de transmissão Coordenação Multi-Ponto (identificada na literatura com a sigla CoMP) devido à sua capacidade de mitigar e gerir Interferência entre Células (sigla ICI na literatura). No entanto a ICI pode ainda ser mais proeminente quando v arios n os no interior da célula utilizam recursos comuns com diferentes níveis de energia, como acontece nos chamados ambientes de redes heterogéneas (sigla Het- Net na literatura). As HetNets são constituídas por duas ou mais camadas de células. A primeira, ou camada superiora, constitui uma implantação tradicional de sítios de célula, muitas vezes referidas neste contexto como macrocells. Os níveis mais baixos são designados por células pequenas, e podem aparecer como microcells, picocells ou femtocells. A HetNet tem atra do grande interesse por parte dos principais fabricantes como sendo facilitador para transmissões de dados de alta velocidade a baixo custo. A investigação tem revelado at e a data, vários dos principais obstáculos que devem ser superados para que as HetNets possam atingir todo o seu potencial: (i) os estrangulamentos no backhaul devem ser aliviados; (ii) bem como sua perfeita interoperabilidade com CoMP. Nesta tese exploramos este ultimo constrangimento e apresentamos ideias inovadoras em como a t ecnica CoMP poder a ser aperfeiçoada por forma a trabalhar em sinergia com a implementação da HetNet, complementado ainda com uma nova perspectiva na alocação de recursos rádio para um controlo e gestão mais apertado de interferência nas HetNets. Com recurso a simulação a níível de sistema para analisar o desempenho dos algoritmos e protocolos propostos, os resultados obtidos concluíram que ganhos at e a ordem dos 20% poderão ser atingidos em termos de eficiência energética

Optimising energy efficiency and spectral efficiency in multi-tier heterogeneous networks:performance and tradeoffs

The exponential growth in the number of cellular users along with their increasing demand of higher transmission rate and lower power consumption is a dilemma for the design of future generation networks. The spectral efficiency (SE) can be improved by better utilisation of the network resources at the cost of reduction in the energy efficiency (EE) due to the enormous increase in the network power expenditure arising from the densification of the network. One of the possible solutions is to deploy Heterogeneous Networks (HetNets) consisting of several tiers of small cell BSs overlaid within the coverage area of the macrocells. The HetNets can provide better coverage and data rate to the cell edge users in comparison to the macrocells only deployment. One of the key requirements for the next generation networks is to maintain acceptable levels of both EE and SE. In order to tackle these challenges, this thesis focuses on the analysis of the EE, SE and their tradeoff for different scenarios of HetNets. First, a joint network and user adaptive selection mechanism in two-tier HetNets is proposed to improve the SE using game theory to dynamically re-configure the network while satisfying the user's quality-of-service (QoS) requirements. In this work, the proposed scheme tries to offload the traffic from the heavily loaded small cells to the macrocell. The user can only be admitted to a network which satisfies the call admission control procedures for both the uplink and downlink transmission scheme. Second, an energy efficient resource allocation scheme is designed for a two-tier HetNets. The proposed scheme uses a low-complexity user association and power allocation algorithm to improve the uplink system EE performance in comparison to the traditional cellular systems. In addition, an opportunistic joint user association and power allocation algorithm is proposed in an uplink transmission scheme of device to device (D2D) enabled HetNets. In this scheme, each user tries to maximise its own Area Spectral Efficiency (ASE) subject to the required Area Energy Efficiency (AEE) requirements. Further, a near-optimal joint user association and power allocation approach is proposed to investigate the tradeoff between the two conflicting objectives such as achievable throughput and minimising the power consumption in two-tier HetNets for the downlink transmission scheme. Finally, a multi-objective optimization problem is formulated that jointly maximizes the EE and SE in two-tier HetNets. In this context, a joint user association and power allocation algorithm is proposed to analyse the tradeoff between the achievable EE and SE in two-tier HetNets. The formulated problem is solved using convex optimisation methods to obtain the Pareto-optimal solution for the various network parameters

Open Cell-less Network Architecture and Radio Resource Management for Future Wireless Communication Systems

In recent times, the immense growth of wireless traffic data generated from massive mobile devices, services, and applications results in an ever-increasing demand for huge bandwidth and very low latency, with the future networks going in the direction of achieving extreme system capacity and ultra reliable low latency communication (URLLC). Several consortia comprising major international mobile operators, infrastructure manufacturers, and academic institutions are working to develop and evolve the current generation of wireless communication systems, i.e., fifth generation (5G) towards a sixth generation (6G) to support improved data rates, reliability, and latency. Existing 5G networks are facing the latency challenges in a high-density and high-load scenario for an URLLC network which may coexist with enhanced mobile broadband (eMBB) services. At the same time, the evolution of mobile communications faces the important challenge of increased network power consumption. Thus, energy efficient solutions are expected to be deployed in the network in order to reduce power consumption while fulfilling user demands for various user densities. Moreover, the network architecture should be dynamic according to the new use cases and applications. Also, there are network migration challenges for the multi-architecture coexistence networks. Recently, the open radio access network (O-RAN) alliance was formed to evolve RANs with its core principles being intelligence and openness. It aims to drive the mobile industry towards an ecosystem of innovative, multi-vendor, interoperable, and autonomous RAN, with reduced cost, improved performance and greater agility. However, this is not standardized yet and still lacks interoperability. On the other hand, the cell-less radio access network (RAN) was introduced to boost the system performance required for the new services. However, the concept of cell-less RAN is still under consideration from the deployment point of view with the legacy cellular networks. The virtualization, centralization and cooperative communication which enables the cell-less RAN can further benefit from O-RAN based architecture. This thesis addresses the research challenges facing 5G and beyond networks towards 6G networks in regard to new architectures, spectral efficiency, latency, and energy efficiency. Different system models are stated according to the problem and several solution schemes are proposed and developed to overcome these challenges. This thesis contributes as follows. Firstly, the cell-less technology is proposed to be implemented through an Open RAN architecture, which could be supervised with the near real-time RAN intelligent controller (near-RT-RIC). The cooperation is enabled for intelligent and smart resource allocation for the entire RAN. Secondly, an efficient radio resource optimization mechanism is proposed for the cell-less architecture to improve the system capacity of the future 6G networks. Thirdly, an optimized and novel resource scheduling scheme is presented that reduces latency for the URLLC users in an efficient resource utilization manner to support scenarios with high user density. At the same time, this radio resource management (RRM) scheme, while minimizing the latency, also overcomes another important challenge of eMBB users, namely the throughput of those who coexist in such a highly loaded scenario with URLLC users. Fourthly, a novel energy-efficiency enhancement scheme, i.e., (3 × E) is designed to increase the transmission rate per energy unit, with stable performance within the cell-less RAN architecture. Our proposed (3 × E) scheme activates two-step sleep modes (i.e., certain phase and conditional phase) through the intelligent interference management for temporarily switching access points (APs) to sleep, optimizing the network energy efficiency (EE) in highly loaded scenarios, as well as in scenarios with lower load. Finally, a multi-architecture coexistence (MACO) network model is proposed to enable inter-connection of different architectures through coexistence and cooperation logical switches in order to enable smooth deployment of a cell-less architecture within the legacy networks. The research presented in this thesis therefore contributes new knowledge in the cellless RAN architecture domain of the future generation wireless networks and makes important contributions to this field by investigating different system models and proposing solutions to significant issues.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidenta: Matilde Pilar Sánchez Fernández.- Secretario: Alberto Álvarez Polegre.- Vocal: José Francisco Monserrat del Rí

Data Processing and Fusion For Multi-Source Wireless Systems

The constant evolution of the telecommunication technologies is one fundamental aspect that characterizes the modern era. In the context of healthcare and security, different scenarios are characterized by the presence of multiple sources of information that can support a large number of innovative services. For example, in emergency scenarios, reliable transmission of heterogeneous information (health conditions, ambient and diagnostic videos) can be a valid support for managing the first-aid operations. The presence of multiple sources of information requires a careful communication management, especially in case of limited transmission resource availability. The objective of my Ph.D. activity is to develop new optimization techniques for multimedia communications, considering emergency scenarios characterized by wireless connectivity. Different criteria are defined in order to prioritize the available heterogeneous information before transmission. The proposed solutions are based on the modern concept of content/context awareness: the transmission parameters are optimized taking into account the informative content of the data and the general context in which the information sources are located. To this purpose, novel cross-layer adaptation strategies are proposed for multiple SVC videos delivered over wireless channel. The objective is to optimize the resource allocation dynamically adjusting the overall transmitted throughput to meet the actual available bandwidth. After introducing a realistic camera network, some numerical results obtained with the proposed techniques are showed. In addition, through numerical simulations the benefits are showed, in terms of QoE, introduced by the proposed adaptive aggregation and transmission strategies applied in the context of emergency scenarios. The proposed solution is fully integrated in European research activities, including the FP7 ICT project CONCERTO. To implement, validate and demonstrate the functionalities of the proposed solutions, extensive transmission simulation campaigns are performed. Hence, the presented solutions are integrated on a common system simulator which is been developed within the CONCERTO project

A Machine Learning Enhanced Scheme for Intelligent Network Management

The versatile networking services bring about huge influence on daily living styles while the amount and diversity of services cause high complexity of network systems. The network scale and complexity grow with the increasing infrastructure apparatuses, networking function, networking slices, and underlying architecture evolution. The conventional way is manual administration to maintain the large and complex platform, which makes effective and insightful management troublesome. A feasible and promising scheme is to extract insightful information from largely produced network data. The goal of this thesis is to use learning-based algorithms inspired by machine learning communities to discover valuable knowledge from substantial network data, which directly promotes intelligent management and maintenance. In the thesis, the management and maintenance focus on two schemes: network anomalies detection and root causes localization; critical traffic resource control and optimization. Firstly, the abundant network data wrap up informative messages but its heterogeneity and perplexity make diagnosis challenging. For unstructured logs, abstract and formatted log templates are extracted to regulate log records. An in-depth analysis framework based on heterogeneous data is proposed in order to detect the occurrence of faults and anomalies. It employs representation learning methods to map unstructured data into numerical features, and fuses the extracted feature for network anomaly and fault detection. The representation learning makes use of word2vec-based embedding technologies for semantic expression. Next, the fault and anomaly detection solely unveils the occurrence of events while failing to figure out the root causes for useful administration so that the fault localization opens a gate to narrow down the source of systematic anomalies. The extracted features are formed as the anomaly degree coupled with an importance ranking method to highlight the locations of anomalies in network systems. Two types of ranking modes are instantiated by PageRank and operation errors for jointly highlighting latent issue of locations. Besides the fault and anomaly detection, network traffic engineering deals with network communication and computation resource to optimize data traffic transferring efficiency. Especially when network traffic are constrained with communication conditions, a pro-active path planning scheme is helpful for efficient traffic controlling actions. Then a learning-based traffic planning algorithm is proposed based on sequence-to-sequence model to discover hidden reasonable paths from abundant traffic history data over the Software Defined Network architecture. Finally, traffic engineering merely based on empirical data is likely to result in stale and sub-optimal solutions, even ending up with worse situations. A resilient mechanism is required to adapt network flows based on context into a dynamic environment. Thus, a reinforcement learning-based scheme is put forward for dynamic data forwarding considering network resource status, which explicitly presents a promising performance improvement. In the end, the proposed anomaly processing framework strengthens the analysis and diagnosis for network system administrators through synthesized fault detection and root cause localization. The learning-based traffic engineering stimulates networking flow management via experienced data and further shows a promising direction of flexible traffic adjustment for ever-changing environments

An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)

With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications

Hybrid Radio Resource Management for Heterogeneous Wireless Access Network

Heterogeneous wireless access network (HWAN) is composed of fifth-generation (5G) and fourth-generation (4G) cellular systems and IEEE 802.11-based wireless local area networks (WLANs). These diverse and dense wireless networks have different data rates, coverage, capacity, cost, and QoS. Furthermore, user devices are multi-modal devices that allow users to connect to more than one network simultaneously. This thesis presents radio resource management for RAT selection, radio resource allocation, load balancing, congestion control mechanism, and user device (UD) energy management that can effectively utilize the available resources in the heterogeneous wireless networks and enhance the quality-of-service (QoS) and user quality-of-experience (QoE). Recent studies on radio resource management in HWAN lead to two broad categories, 1) centralized architecture and 2) distributed model. In the centralized model, all the decision making power confines to a centralized controller and user devices are assumed as passive transceivers. In contrast, user devices actively participate in radio resource management in the distributed model, resulting in poor resource utilization and maximum call blocking and call dropping probabilities. In this thesis, we present a novel hybrid radio resource management model for HWAN that is composed of OFDMA based system and WLAN. In this model, both the centralized controller and the user device take part in resource management. Our hybrid mechanism considers attributes related to both user and network. However, these attributes are conflicting in nature. Moreover, a single RAT selection is performed based on user location and available networks, whereas UD with a multi-homing call receives the radio resource share from each network to fulfil its minimum data rate requirement. A novel approach is proposed for load balancing where an equal load ratio is maintained across all the available networks in HWAN. Performance evaluation through call blocking probability and network utilization will reveal the effectiveness of the proposed scheme. The demand for more data rates is on the rise. The 5G heterogeneous wireless access network is a potential solution to tackle the high data rate demand. The 5GHWAN is composed of 5G new radio (NR) and 4G long-term evolution (LTE) base stations (BSs). In a practical system, the channel conditions fluctuate due to user mobility. We, therefore, investigate radio resource allocation and congestion control mechanism along with network-assisted distributive RAT selection in a time-varying 5GHWAN. This joint problem of radio resource allocation and congestion control management has signalling overhead and computational complexity limitations. Therefore, we use the Lyapunov optimization to convert the offline problem into an online optimization problem based on channel state information (CSI) and queue state information (QSI). The theoretical and simulation results evaluate the performance of our proposed approach under the assumption of network stability. In addition, simulation results are presented to depict our proposed scheme’s effectiveness. Furthermore, our proposed RAT selection scheme performs better than the traditional centralized and distributive mechanisms. Recently an increase in the usage of video applications has been observed. Therefore, we explore hybrid radio resource management video streaming over time-varying HWAN. Using the Lyapunov optimization technique, we decompose our two-time scale stochastic optimization problem into two main sub-problems. One of the sub-problems is related to radio resource allocation that operates at a scheduling time interval. The radio resource allocation policy is implemented at a centralized control node responsible for allocating radio resources from the available wireless networks using Lagrange dual method. The other sub-problem is related to the quality rate adaptation policy that works at a chunk time scale. Each user selects the appropriate quality level of the video chunks adaptively in a distributive way based on buffer state and channel state information. We analyze and compare the QoE of our proposed approach over an arbitrary sample path of channel state information with an optimal T-slot algorithm. Finally, we evaluate the performance analysis of our proposed scheme for video streaming over a time-varying heterogeneous wireless access network through simulation results