Enabling Optical Wired and Wireless Technologies for 5G and Beyond Networks

The emerging fifth-generation mobile communications are envisaged to support massive number of deployment scenarios based on the respective use case requirements. The requirements can be efficiently attended with ultradense small-cell cloud radio access network (C-RAN) approach. However, the C-RAN architecture imposes stringent requirements on the transport networks. This book chapter presents high-capacity and low-latency optical wired and wireless networking solutions that are capable of attending to the network demands. Meanwhile, with optical communication evolutions, there has been advent of enhanced photonic integrated circuits (PICs). The PICs are capable of offering advantages such as low-power consumption, high-mechanical stability, low footprint, small dimension, enhanced functionalities, and ease of complex system architectures. Consequently, we exploit the PICs capabilities in designing and developing the physical layer architecture of the second standard of the next-generation passive optical network (NG-PON2) system. Apart from being capable of alleviating the associated losses of the transceiver, the proposed architectures aid in increasing the system power budget. Moreover, its implementation can significantly help in reducing the optical-electrical-optical conversions issue and the required number of optical connections, which are part of the main problems being faced in the miniaturization of network elements. Additionally, we present simulation results for the model validation

WiBACK: A back-haul network architecture for 5G networks

Recently both academic and industry worlds has started to define the successor of Long Term Evolution (LTE), so-called 5G networks, which will most likely appear by the end of the decade. It is widely accepted that those 5G networks will have to deal with significantly more challenging requirements in terms of provided bandwidth, latency and supported services. This will lead to not only modifications in access and parts of core networks, but will trigger changes throughout the whole network, including the Back-haul segment. In this work we present our vision of a 5G Back-haul network and identify the associated challenges. We then describe our Wireless Backhaul (WiBACK) architecture, which implements Software Defined Network (SDN) concepts and further extends them into the wireless domain. Finally we present a brief overview of our pilot installations before we conclude.This work has been supported by the BATS research project which is funded by the European Union Seventh Framework Programme under contract n317533

Addressing the 5G cell switch-off problem with a multi-objective cellular genetic algorithm

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The power consumption foreseen for 5G networks is expected to be substantially greater than that of 4G systems, mainly because of the ultra-dense deployments required to meet the upcoming traffic demands. This paper deals with a multi- objective formulation of the Cell Switch-Off (CSO) problem, a well-known and effective approach to save energy in such dense scenarios, which is addressed with an accurate, yet rather unknown multi-objective metaheuristic called MOCell (multi- objective cellular genetic algorithm). It has been evaluated over a different set of networks of increasing densification levels. The results have shown that MOCell is able to reach major energy savings when compared to a widely used multi-objective algorithm.TIN2016-75097-P Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Probabilistic small-cell caching: performance analysis and optimization

Small-cell caching utilizes the embedded storage of small-cell base stations (SBSs) to store popular contents, for the sake of reducing duplicated content transmissions in networks and for offloading the data traffic from macro-cell base stations to SBSs. In this paper, we study a probabilistic small-cell caching strategy, where each SBS caches a subset of contents with a specific caching probability. We consider two kinds of network architectures: 1) the SBSs are always active, which is referred to as the always-on architecture, 2) the SBSs are activated on demand by mobile users (MUs), referred to as the dynamic on-off architecture. We focus our attention on the probability that MUs can successfully download contents from the storage of SBSs. First, we derive theoretical results of this successful download probability (SDP) using stochastic geometry theory. Then, we investigate the impact of the SBS parameters, such as the transmission power and deployment intensity on the SDP. Furthermore, we optimize the caching probabilities by maximizing the SDP based on our stochastic geometry analysis. The intrinsic amalgamation of optimization theory and stochastic geometry based analysis leads to our optimal caching strategy characterized by the resultant closed-form expressions. Our results show that in the always-on architecture, the optimal caching probabilities solely depend on the content request probabilities, while in the dynamic on-off architecture, they also relate to the MU-to-SBS intensity ratio. Interestingly, in both architectures, the optimal caching probabilities are linear functions of the square root of the content request probabilities. Monte-Carlo simulations validate our theoretical analysis and show that the proposed schemes relying on the optimal caching probabilities are capable of achieving substantial SDP improvement compared to the benchmark schemes

5G Backhaul: Requirements, Challenges, and Emerging Technologies

5G is the next generation cellular networks which is expected to quench the ever-ending thirst of data rates and interconnect billions of smart devices to support not only human centric traffic, but also machine centric traffic. Recent research and standardization work have been addressing requirements and challenges from radio perspective (e.g., new spectrum allocation, network densification, massive multiple-input-multiple-output antenna, carrier aggregation, inter-cell interference mitigation techniques, and coordinated multi-point processing). In addition, a new network bottleneck has emerged: the backhaul network which will allow to interconnect and support billions of devices from the core network. Up to 4G cellular networks, the major challenges to meet the backhaul requirements were capacity, availability, deployment cost, and long-distance reach. However, as 5G network capabilities and services added to 4G cellular networks, the backhaul network would face two additional challenges that include ultralow latency (i.e., 1 ms) requirements and ultradense nature of the network. Due to the dense small cell deployment and heavy traffic cells in 5G, 5G backhaul network will need to support hundreds of gigabits of traffic from the core network and today’s cellular backhaul networks are infeasible to meet these requirements in terms of capacity, availability, latency, energy, and cost efficiency. This book chapter first introduce the mobile backhaul network perspective for 2G, 3G, and 4G networks. Then, outlines the backhaul requirements of 5G networks, and describes the impact on current mobile backhaul networks