Design and analysis of ultra-low latency fronthaul and backhaul networks for 5G

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Conventional communications between human mobile users are not the only type of activities envisioned for post-5G and future 6G networks. Traditional Human-to- Human (H2H) communications are now joined by Human-to-Machine (H2M), and Machine-to-Machine (M2M) communications, in a Tactile Internet world. 6G is expected to put an end to smartphone-centric era, introducing new system paradigms. New services and applications such as telepresence, remote control of haptic machines, online schools/working, remote surgery, Multi-access Edge Computing (MEC) are envisioned to be part of the future daily life. Cloud-based services (including the cloud-based signal processing of radio waveforms), video traffic, enterprise applications, and virtualization have led to a rise of the traffic demand in metropolitan areas. Traditional cellular architectures are becoming exhausted and unable to cope with the requested performance and new approaches such as the Cloud Radio Access Networks (C-RAN) appear as natural replacements. This technology suggests the separation between the radio and the processing equipment that now will be located at different places of the network. However, all the implementation details about how to meet the bandwidth, latency, jitter or even how to measure these parameters remain open. In this thesis, we firstly assess real world traditional deployments for C-RAN like ring-star topologies implemented with Ethernet switching equipment. We derive the theoretical expressions for the propagation and queueing delays, assuming G/G/1 queueing models. Furthermore, the properties of the fronthaul streams are examined, particularly regarding the aggregation of functional Split B flows in the same fronthaul network. Additionally, the G/G/1 queueing model is further extended with the Kingman’s Exponential Law of Congestion, paying special attention to the percentile values of the queueing delay. High queueing delay percentiles are proposed as the key metric for the fronthaul network dimensioning. Namely, the aggregation of eCPRI flows (Splits IU and IID) in a packet aggregator is explored for different values of the radio channel’s bandwidth. The use of extreme latency percentiles is later explored as a useful tool for the design of fronthaul networks. The G/G/1 and N*D/D/1 queueing models are tested as modeling tools and compared with simulation to assess the tightness of their predictions in the extreme latency percentiles scenarios. The results support that the N*D/D/1 queue is able to model the behavior of a packet-switch fronthaul aggregator using the eCPRI standard for 5G New Radio (NR) fronthaul streams in a more accurate way and can be used as a tool to dimension the length of the links. This better modeling of the fronthaul translates into a finer implementation of C-RAN. By interpreting the gap betweenthis estimation and maximum worst-case delay as an extra delay budget, the fronthaul links’ lengths can be increased by 60% and 10% for 50 MHz and 100 MHz NR channels, respectively, while keeping the latency budget and frame loss ratio within the IEEE 802.1CM limits. Recent research efforts focus on the development of new photonic technologies, enabling capacities of Tb/s for the metropolitan area network. Sliceable Bandwidth Variable Transceivers (S-BVTs) appear as a promising technology to achieve this goal. The newadvancements in S-BVTs suggest that it is a cost-effective, flexible, and highperformance technology to improve metropolitan networks. In this thesis, we show their advantages over fixed transceivers in edge computing and content delivery network scenarios. Particularly, this work studies the dimensioning of edge data center resources from the perspective of achieving the blocking probabilities as low as 10[elevado a -6]. Two different scenarios are analyzed: the overflow over a paired samelevel data centers and the overflow over a centralized site. The results show that a proper distribution of computing resources in the centralized overflow approach can outperform the costs of a distributed strategy, requiring fewer processors and much smaller data centers at the central office. Moreover, different strategies to implement cost-effective CDN caching are presented. Fixed and bandwidth variable solutions are proposed and compared against each other in three different topologies, from the perspective of availability. Those solutions that make us of S-BVTs show many advantages in terms of scalability, low wavelength occupancy, and the reduced number of IT resources needed to support the same availability. Finally, this thesis addresses the characterization of the fronthaul traffic so that we may support its coexistence with other types of traffic and services. A Heterogeneous Cloud Radio Access Network (H-CRAN) serves as the reference network comprising all the envisioned traffic types, services, and data rates. A network simulator and its building blocks are described and presented as the tool to assess the performance of the proposed solution. This description includes the basics and the building blocks of the simulator (channel and interference models) as well as the definition of many concepts such as the heterogeneous networks, the construction of the coverage maps, the uplink and downlink decoupling, etc. A global optimization problem is proposed for the entire network, supporting three access technologies: LTE-A, WiFi, and C-RAN. A distributed and scalable operation method is proposed to orchestrate all the above components and to enable a seamless and flexible operation. The distributed algorithm is computationally simple as it only requires broadcasting the Lagrange multipliers that arise while solving the optimization problem. These, work as a sort of price indicator, transmitting information about the state and needs of base stations and users at any particular time. This solution is able to organize the user association and network resources in the appropriate way so as to comply with the delay requirements of each traffic type. As a desirable side effect, the energy consumption of the mobile nodes is also optimized.
Mención Internacional en el título de doctor
5G mobile communication, Delay estimation, Fronthaul traffic flows, C-RAN transport network, G/G/1 queueing models, Telecommunication network topology, Multiplexing
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