Chapter 5 studies in detail – and also from a theoretical perspective – yet another and more important caveat towards a satisfactory network performance in the ultra-dense regime, i.e. that of the impact of the antenna height difference between the user equipment and the small cell base stations. Similarly as in the previous chapter, such antenna-related modelling upgrades, the new derivations in a three-dimensional space and the new obtained results are carefully presented and discussed in this book chapter for the better understanding of the readers. Moreover, several small cell deployment and configuration guidelines are provided to improve the network performance.

Chapter 2 introduces the need for wireless network performance analysis tools to drive optimal network deployments and set optimal parameter values and describes the main building blocks and models of any wireless network performance analysis tool. In more details, it focuses on i) the system-level simulation and ii) the theoretical performance analysis concepts used in this book, paying particular attention to stochastic geometry frameworks.

Chapter 7 investigates the impact of ultra-dense networks on multi-user diversity. A denser network reduces the number of user equipment per small cell in a significant manner, and thus can significantly reduce – and potentially neglect – the gains of channel-dependent scheduling techniques. These performance gain degradations are theoretically analyzed in this chapter, and the performance of a proportional fair scheduler is compared to that of a round robin one.

Chapter 8, standing on the shoulders of all previous chapters, presents a new capacity scaling law for ultra-dense networks. Interestingly, the signal and the inter-cell interference powers become bounded in the ultra-dense regime. The former is due to the antenna height difference between the user equipment and the small cell base stations, and the latter is due to the finite user equipment density as well as the idle mode capability at the small cell base stations. This leads to a constant signal-to-interference-plus-noise ratio at the user equipment, and thus to an asymptotic capacity behaviour in such a regime. From this new capacity scaling law, it can be concluded that, for a given user equipment density, the network densification should not be abused indefinitely, and instead, it should be stopped at a certain level. Network densification beyond such a point is a waste of both invested money and energy consumption.

Chapter 4 analyzes in detail – from a theoretical perspective – the first practical caveat towards such linear growth of capacity in the ultra-dense regime, i.e. that of the impact of the transition of a large number of interfering links from non-line-of-sight to line-of-sight. Importantly, this chapter shows that the theoretical tools used until then to analyze traditional sparse or dense small cell networks, such as that presented in the previous chapter, do not directly apply to ultra-dense ones, and neither do their conclusions. In this chapter, we detail the path loss modelling upgrades necessary for a more realistic and accurate modelling of ultra-dense networks, present the subsequent and new theoretical derivations, and analyze the obtained results for the better understanding of the readers.

We overview the main characteristics of the power-line channel, such as noise, attenuation, and its broadcast nature. We identify the key factors that affect end-to-end performance of single links. We discuss the PHY layer functions and the evolution of PLC technologies. We present a typical PLC transceiver, its signal modulation and coding techniques, and their parameters. We discuss the new features of HomePlug AV2 compared to IEEE 1901 and the differences between Wi-Fi and PLC PHY layers.

We discusse PLC efficiency when multiple users contend for the medium. To resolve contention conflicts, PLC uses carrier sense multi- ple access with collision avoidance (CSMA/CA) on the MAC layer. The stations have to sense the medium before they transmit, and to wait for a random interval of idle-medium time slots before they transmit. The PLC CSMA/CA protocol is similar but more complex than that of Wi-Fi. We present the IEEE 1901 CSMA/CA protocol and certain MAC-layer processes, such as the priority resolution for QoS classes, inter-frame spaces, and frame aggregation. We discuss the new features of HomePlug AV2 compared to IEEE 1901 and the differences between Wi-Fi and PLC MAC layers.

We introduce an experimental framework for PLC.We explain how to configure PLC devices and how to measure certain statistics, such as the capacity of the links, packet errors, modulation information, and collision statistics. We rely on PLC management messages and on open-source tools. We give examples of these messages and guidelines on employing the tools. We also explain how to develop new custom PLC tools.