No description available.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / The integrated Network-Enhanced Telemetry (iNET) project is transitioning from standards development to deployment of systems. In fielding a Telemetry Network System (TmNS) demonstration system, one must choose and integrate technological building blocks from the suite of standards to implement new test capabilities. This paper describes the operation of a TmNS and identifies the management, configuration, control, acquisition, and distribution of information and operational flows. These items are discussed utilizing a notional system to walk through the mechanisms identified by the iNET standards. Note that at the time of this paper the efforts discussed are only at the very beginning of the design process and will likely evolve throughout the design process.

Cloud-radio access network (CRAN) is expected to be the core network architecture for next generation mobile radio system. In CRANs, joint signal processing is performed at multiple cloud computing centers (clouds) that are connected to several base stations (BSs) via high capacity backhaul links. As a result, large-scale interference management and network power consumption reduction can be effectively achieved. Unlike recent works on CRANs which consider a single cloud processing and treat inter-cloud interference as background noise, the first part of this thesis focuses on the more practical scenario of the downlink of a multi-cloud radio access network where BSs are connected to each cloud through wireline backhaul links. Assume that each cloud serves a set of pre-known single-antenna mobile users (MUs). This part focuses on minimizing the network total power consumption subject to practical constraints. The problems are solved using sophisticated techniques from optimization theory (e.g. Dual Decomposition-based algorithm and the alternating direction method of multipliers (ADMM)-based algorithm). One highlight of this part is that the proposed solutions can be implemented in a distributed fashion by allowing a reasonable information exchange between the coupled clouds. Additionally, feasible solutions of the considered optimization problems can be estimated locally at each iteration. Simulation results show that the proposed distributed algorithms converge to the centralized algorithms in a reasonable number of iterations. To further account of the backhaul congestion due to densification in CRANs, the second part of this thesis considers the downlink of a cache-enabled CRAN where each BS is equipped with a local-cache with limited size used to store the popular files without the need for backhauling. Further, each cache-enabled BS is connected to the cloud via limited capacity backhaul link and can serve a set of pre-known single antenna MUs. This part assumes that only imperfect channel state information (CSI) is available at the cloud. This part focuses on jointly minimizing the network total power consumption as well as backhaul cost. It then suggests solving this optimization problem using the majorization-minimization (MM) approach. Simulation results show that the proposed algorithm converges in a reasonable number of iterations.

Passive and active devices are essential devices in mobile and base stations’ transceiver. Consequently, these devices dominated the large part of the PCB of the today’s transceiver. However, the tomorrow’s mobile terminals without circuit tunability would be extremely large in size to accommodate present and future radio access technologies (RATs). The stand-alone transceiver for one single RAT is comprised of single passive and active devices and adding two or more RATs for the same transceiver would require adding two or more devices, since all of these RATs standards work on different frequency bands. Apparently, without tunability approach, this will increase the complexity of the system design and will cover a large part of the circuit space leading to power consumptions, loss which results to the poor efficiency of the transceiver. In this work, a miniaturized RF MEMS tunable bandpass is developed to operate in the frequency range from 1.8 to 2.6 GHz.

Research Doctorate - Doctor of Philosophy (PhD) / The Radio Access Network (RAN) accounts for the major proportion of the UMTS system operating cost. Transmission from radio base station sites contributes a larger part of the RAN operating costs. Selection of suitable transport technologies and proper allocation of network resources are vital from an operator cost optimisation and the Quality of Experience (QoE) points of view. This thesis extensively investigated the performance of a RAN to support multimedia traffic on a HSDPA air interface. Transport network layer of a future RAN could be based on a number of transport protocols such as ATM, IP and Ethernet. With the increasing traffic volume and diversity the efficiencies of IP and Ethernet based RAN could increases significantly due to the use of larger payloads and simpler resource allocation techniques. Also, on IP and Ethernet based links relatively fewer overhead bits are transmitted compared to an ATM based link. Both the IP and Ethernet based links appear to perform better under heavy traffic load conditions. An IP based link could perform better than an Ethernet based link when an IP header compression technique is used. An Ethernet based link is an alternative transport technique for the UTRAN transport network due to its flexibility, economy and bandwidth efficiency. The HSDPA (High Speed Downlink Packet Access) is considered to be one of the initial evolutionary steps to enhance the data rate, and QoS of downlink data and multimedia services for the evolved UMTS network. It can provide high data rate up to 28.8 Mbps on the downlink shared channel using the packet access technique. A HSDPA network can dynamically adjust a connection data rate to match radio conditions to ensure the highest possible data rate for different type of traffic. Inappropriate RAN capacity allocation could lead to low radio resource or RAN resource utilizations. In this thesis, a Markov chain based analytical model has been developed to study the interaction between the air interface and the RAN for a HSDPA network. The analytical model was used to study interactions of RAN transport protocols, flow control techniques and the air interface transmission conditions. Further a simulation model was developed to investigate the relationship between the HSDPA air interface and its RAN parameters. Another important issue in the HSDPA network design is the scheduling algorithm used at the Node-B. A scheduling algorithm plays a key role in allocating a RAN’s network resources. Impacts of scheduling algorithms are studied in this work using a simulation model. Based on the study of the HSDPA air interface and its RAN parameter interactions this work has developed an adaptive resource management algorithm, which uses the measured air interface information to allocate the corresponding connection data rate on the Iub link. The developed algorithm reduces RAN resource requirements while increasing the air interface resource utilization and QoS of connections.

In the LTE access networks, the Radio Resource Management (RRM) is one of the most important modules which is responsible for handling the overall management of radio resources. The packet scheduler is a particular sub-module which assigns the existing radio resources to each user in order to deliver the requested services in the most efficient manner. Data packets are scheduled dynamically at every Transmission Time Interval (TTI), a time window used to take the user’s requests and to respond them accordingly. The scheduling procedure is conducted by using scheduling rules which select different users to be scheduled at each TTI based on some priority metrics. Various scheduling rules exist and they behave differently by balancing the scheduler performance in the direction imposed by one of the following objectives: increasing the system throughput, maintaining the user fairness, respecting the Guaranteed Bit Rate (GBR), Head of Line (HoL) packet delay, packet loss rate and queue stability requirements. Most of the static scheduling rules follow the sequential multi-objective optimization in the sense that when the first targeted objective is satisfied, then other objectives can be prioritized. When the targeted scheduling objective(s) can be satisfied at each TTI, the LTE scheduler is considered to be optimal or feasible. So, the scheduling performance depends on the exploited rule being focused on particular objectives. This study aims to increase the percentage of feasible TTIs for a given downlink transmission by applying a mixture of scheduling rules instead of using one discipline adopted across the entire scheduling session. Two types of optimization problems are proposed in this sense: Dynamic Scheduling Rule based Sequential Multi-Objective Optimization (DSR-SMOO) when the applied scheduling rules address the same objective and Dynamic Scheduling Rule based Concurrent Multi-Objective Optimization (DSR-CMOO) if the pool of rules addresses different scheduling objectives. The best way of solving such complex optimization problems is to adapt and to refine scheduling policies which are able to call different rules at each TTI based on the best matching scheduler conditions (states). The idea is to develop a set of non-linear functions which maps the scheduler state at each TTI in optimal distribution probabilities of selecting the best scheduling rule. Due to the multi-dimensional and continuous characteristics of the scheduler state space, the scheduling functions should be approximated. Moreover, the function approximations are learned through the interaction with the RRM environment. The Reinforcement Learning (RL) algorithms are used in this sense in order to evaluate and to refine the scheduling policies for the considered DSR-SMOO/CMOO optimization problems. The neural networks are used to train the non-linear mapping functions based on the interaction among the intelligent controller, the LTE packet scheduler and the RRM environment. In order to enhance the convergence in the feasible state and to reduce the scheduler state space dimension, meta-heuristic approaches are used for the channel statement aggregation. Simulation results show that the proposed aggregation scheme is able to outperform other heuristic methods. When the aggregation scheme of the channel statements is exploited, the proposed DSR-SMOO/CMOO problems focusing on different objectives which are solved by using various RL approaches are able to: increase the mean percentage of feasible TTIs, minimize the number of TTIs when the RL approaches punish the actions taken TTI-by-TTI, and minimize the variation of the performance indicators when different simulations are launched in parallel. This way, the obtained scheduling policies being focused on the multi-objective criteria are sustainable. Keywords: LTE, packet scheduling, scheduling rules, multi-objective optimization, reinforcement learning, channel, aggregation, scheduling policies, sustainable.

Optical fibre has become the dominant theme of transmission in long haul, high data rate communication systems due to its tremendous bandwidth and low loss. Radio over Fibre (RoF) technology facilitates the seamless integration between wireless and optical communication systems and found to be the most promising solution to meet the exponential bandwidth demands expected for the upcoming years. However, the main bit-rate/distance limitation in RoF systems is the chromatic dispersion. In this thesis, the two generations of RoF technologies, namely Analogue RoF (ARoF) and Digital RoF (DRoF) are investigated. The overall aim of this research is to optimise the optical bandwidth utilisation of these two approaches for a typical transmission of the fronthaul link proposed in the next generation Centralised Radio Access Network (C-RAN). Consequently, a number of physical layer design scenarios for the optimised transmission of the Radio Frequency (RF) signals over a Standards Single Mode Fibre (SSMF) are demonstrated. Firstly, for an ARoF transmission, where the analogue RF signals are transported over SSMF using an optical carrier, a bidirectional link transmitting four Downlink/Uplink channels in a chromatic dispersion limited scenario is designed. Simulation results have shown a clear constellation diagram of a 2.5 Gb/s RF signal transmission over 120 km fibre length. Secondly, a DRoF system with reduced optical bandwidth occupancy is proposed. This system employs an optical Duobinary transmission to the digitised RF signal at the transmitter side to reduce its spectrum and to address the chromatic dispersion effect, simultaneously. Simulation results demonstrate the capability of the proposed system to maintain high-quality transmission of the digitised signals over 70 km of fibre distance without dispersion compensation requirements. Finally, an advanced DRoF transmission link based on integrating digital Optical Single Sideband (OSSB) transmission with Duobinary encoding scheme is designed. Simulation results have clearly verified system's robustness against transmission impairments and have better performances in terms of the obtained BER and EVM with respect to the 3GPP standardised values. Moreover, the results show that both transmission distance and power budget are furtherly improved in comparison with two other digital transmission scenarios.

This thesis focuses on proposing a Software Defined Network (SDN) based programmable and capacity optimized backhaul and core network which is critical for 5G network design. Cloud Radio Access networks (CRAN) which is key enabler of 5G networks can address a number of challenges that mobile operators face while trying to support ever-growing end-users' needs towards 5th generation of mobile networks (5G). A novel layered and modular programmable CRAN architecture called Software Defined Virtualised Cloud Radio Access Network (SD-vCRAN) is introduced with Network Function Virtualization (NFV) and Software Defined Network (SDN) capabilities. The SDN-Base Band Unit (BBU) pool is shifted to the programmable core network site, where a centralised SDN controller manages the network servers and virtualised network function entities - Mobile Management Entity (MME), Serving/Packet Data Network Data plane (S/PGW-D), Serving/Packet Data Network Control plane (S/PGW-C), Software Network Defined Baseband Unit (SDN-BBU) and Local controllers (LC) via OpenFlow (OF) protocol. This approach simplifies network operations, improve traffic management, enable system-wide optimisation of Quality of Service (QoS) and network-aware application development. The control plane (excluding the preserved 3GPP standard interfaces: S1-MME, S6a, Gx) managed by the network servers provides load balancing, traffic management and optimisation tools for the data plane. The proposed work starts by reviewing the requirements of 5G networks, followed by discussion on 5G backhaul and core challenge. Then, an overview of CRAN, Evolved Programmable Core (EPC), SDN, NFV and related works. The simulation details of the proposed architecture are discussed along with the challenges faced by adopting SDN and NFV in mobile core. A thorough assessment of the interfaces and protocols that should be conserved or enhanced on both data and control plane is conducted. The result enables an architecture where the SDN-BBU pool shares a single cloud with the programmable EPC and the control plane is migrated from the network elements to a centralized controller, running on a virtual machine in the mobile core. The data and control plane separation removes overlaps and provides better signalling, as well as efficient network functioning to comply with latency demands. The proposed system performance is validated in terms of throughput, datagram loss, and packet delay variation under three scenarios: 1. single policy installation, 2. multiple policy installation and 3. load balancing. The load balancing performance of proposed system is validated comparing the performance of two different SDN controllers: Floodlight and OpenDaylight, where the later performs better in terms of throughput (no bandwidth restriction), packet loss (below 0.3%) and jitter (below 0.2ms). Furthermore, a detailed comparison of two SDN controller's - Floodlight and OpenDaylight performances is presented, which shows that OpenDaylight performs better only for less dense networks which needs less processing of messages without being blocked, and the Floodlight performs better in ultra-dense network. Some directions and preliminary thoughts for future work and necessary information to operators for building their roadmap to the upcoming technologies is presented.

In this thesis, components and parameters based power models (PMs) are produced to measure the power consumption (PC) of cloud radio access network (CRAN) architecture. In components PM, the power figure of each component within C-RAN is evaluated. After, this model is parametrised such that the computation complexity of each component is converted to a straightforward, but accurate method, called parameterised PM. This model compares cooling and total PC of traditional LTE architecture with C-RAN. This comparison considered different parameters such as, utilised bandwidth, number of antenna, base band units (BBUs) and remote radio heads (RRHs). This model draws about 33% reduction in power. Next, this PC model is updated to serve and exhibit the cost of integrating software defined networks (SDNs) with C-RAN. Alongside, modelling the power cost of the control plane units in the core network (CN), such as serving gateway (SGW), packet gateway (PGW) and mobility management entity (MME). Although there is power cost, the proposed model shows the directions to mitigate it. Consequently, a simplified PM is proposed for virtualisation based C-RAN. In this model, the power cost of server virtualisation by hosting several virtual machines (VMs) is shown, in a time and cost effective way. The total reduction in the PC was about 75%, due to short-cutting the number of active servers in the network. Alongside, the latency cost due to such technique is modelled. Finally, to enable efficient virtualisation technology, live migrating the VMs amongst the servers is vital. However, this advantageous situation is concurrent with VM's migration time and power cost. Therefore, a model is proposed to calculate the power cost of VM's live migration, and shows the effect of such decision upon the total PC of the network/C-RAN. The proposed work converts the complexity of other proposed PMs, to a simplified and costless method. Concurrently, the time cost is added to the imposed virtualisation's time cost to formulate the total delay expected prior to these techniques' execution.

Emerging 5G mobile networks are envisioned to become multi-service environments, enabling the dynamic deployment of services with a diverse set of performance requirements, accommodating the needs of mobile network operators, verticals and over-the-top service providers. The Radio Access Network (RAN) part of mobile networks is expected to play a very significant role towards this evolution. Unfortunately, such a vision cannot be efficiently supported by the conventional RAN architecture, which adopts a fixed and rigid design. For the network to evolve, flexibility in the creation, management and control of the RAN components is of paramount importance. The key elements that can allow us to attain this flexibility are the programmability and the virtualization of the network functions. While in the case of the mobile core, these issues have been extensively studied due to the advent of technologies like Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) and the similarities that the core shares with other wired networks like data centers, research in the domain of the RAN is still in its infancy. The contributions made in this thesis significantly advance the state of the art in the domain of RAN programmability and virtualization in three dimensions. First, we design and implement a software-defined RAN (SD-RAN) platform called FlexRAN, that provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. Second, we leverage the capabilities of the FlexRAN platform to design and implement Orion, which is a novel RAN slicing system that enables the dynamic on-the-fly virtualization of base stations, the flexible customization of slices to meet their respective service needs and which can be used in an end-to-end network slicing setting. Third, we focus on the use case of multi-tenancy in a neutral-host indoors small-cell environment, where we design Iris, a system that builds on the capabilities of FlexRAN and Orion and introduces a dynamic pricing mechanism for the efficient and flexible allocation of shared spectrum to the tenants. A number of additional use cases that highlight the benefits of the developed systems are also presented. The lessons learned through this research are summarized and a discussion is made on interesting topics for future work in this domain. The prototype systems presented in this thesis have been made publicly available and are being used by various research groups worldwide in the context of 5G research.