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Chapter 10, in contrast to all the previous chapters that focused on the performance of the downlink, analyzes the performance of the uplink of an ultra-dense network. Importantly, this chapter shows that the phenomena presented in – and the conclusions derived from – all the previous chapters also apply to the uplink, despite its different features, e.g. uplink transmit power control, inter-cell interference source distribution. System-level simulations are used in this chapter to conduct the study.
Chapter 9, using the new capacity scaling law presented in the previous chapter, explores three relevant network optimization problems: i) the small cell base station deployment/activation problem, ii) the network-wide user equipment admission/scheduling problem, and iii) the spatial spectrum reuse problem. These problems are formally presented, and exemplary solutions are provided, with the corresponding discussion on the intuition behind the proposed solutions.
Chapter 11 shows the benefits of dynamic time division duplexing with respect to a more static time division duplexing assignment of time resources in an ultra-dense network. As studied in previous chapters, the amount of user equipment per small cell reduces significantly in a denser network. As a result, a dynamic assignment of time resources to the downlink and the uplink according to the load in each small cell can avoid resource waste, and significantly enhance its capacity. The dynamic time division duplexing protocol is modelled and analyzed through system-level simulations in this chapter too, and its performance carefully examined.
Chapter 3 summarizes the modelling, derivations and main findings of probably one of the most important works on small cell theoretical performance analysis, which concluded that the fears of an inter-cell interference overload in small cell networks were not well-grounded, and that the network capacity – or in more technical words, the area spectral efficiency – linearly grows with the number of deployed small cells. This research was the cornerstone of much of the research that followed on small cells performance analysis.
Chapter 6 brings attention to another important feature of ultra-dense networks, i.e. the surplus of the number of small cell base stations with respect to the amount of user equipment. Building on this fact and looking ahead at next generation small cell base stations, the ability to go into idle mode, transmit no signalling meanwhile, and thus mitigate inter-cell interference is presented in this chapter, as a key tool to enhance ultra-dense network performance and combat the previously presented caveats. Special attention is paid to the upgraded modelling and analysis of the idle mode capability at the small cell base stations.
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 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.
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