The traffic volume in wireless communication has grown dramatically in the last decade and is predicted to keep increasing in the future. In this thesis, we focus on the densification dimension for capacity improvement, which has been proved to be the most effective in the past. The current gain of network densification mainly comes from cell splitting, thereby serving more user equipments (UEs) simultaneously. This trend will decelerate as base station (BS) density gets closer to or even surpass UE density which forms an ultra-dense network (UDN). Thus, it is crucial to understand the behavior of ultra-densification for future network provisioning.

We start from comparing the effectiveness of densification with spectrum expansion and multi-antenna systems. Our findings show that deploying more BSs provides a substantial gain in sparse network but the gain decreases progressively in a UDN. The diminishing gain appears in a UDN make us curious to know if there exists a terminal on the way of densification. Such uncertainty leads to the study on the asymptotic behavior of densification. We incorporate a sophisticated bounded dual-slope path loss model and practical UE densities in our analysis. By using stochastic geometry, we derive the expressions and prove the convergence of the coverage probability of a typical UE and network area spectral efficiency (ASE). Considering the large portion of dormant BSs in a UDN, it is an interesting question whether we can utilize these dormant BSs to improve system performance is an interesting question. To this end, we employ joint transmission (JT) techniques into a UDN. Two types of cooperation schemes are investigated: non-coherent JT and coherent JT depending on the availability of channel state information (CSI). Our results reveal that non-coherent JT is not beneficial in a UDN while coherent JT are able to increase UE spectral efficiency (SE) depending on the environmental parameters.

The traffic volume in wireless communication has grown dramatically in the lastdecade. Recent predictions indicate such data storm will be even more violent in theshort run. Potential solutions for accommodating the rapid traffic growth can besummed up into three categories: broadening the available bandwidth, improvingthe spectral efficiency, and densifying the infrastructure. In this thesis, we focuson the densification dimension which has been proven to be the most effectiveone in the past. The current gain of network densification mainly comes from cellsplitting, thereby serving more user equipment (UE) simultaneously. This trendwill decelerate as the base station (BS) density gets closer to or even surpassesthe UE density which forms an ultra-dense network (UDN). Thus, it is crucialto understand the behavior and design operations of ultra-densification in futurenetworks.

An important question for future system design and operating strategy is whichelement is more effective than others. To this end, we start from comparing the effectivenessof densification with spectrum expansion and multi-antenna systems interms of meeting certain traffic demand. Our findings show that deploying more BSsprovides a substantial gain in sparse network but the gain decreases progressively ina UDN. Meanwhile, even with the same area throughput, different combinations ofindividual throughput and UE density lead to different requirements for resources.The diminishing gain appearing in UDNs makes us curious to know if there existsa terminal on the way of densification. Such uncertainty leads to the study onthe asymptotic behavior of densification. By incorporating a sophisticated boundeddual-slope path loss model and practical UE densities in our analysis, we present theasymptotic behavior of ultra-densification: the coverage probability and area spectralefficiency (ASE) have non-zero convergences in asymptotic regions unless theUE density goes to infinity (full load). Our results suggest that network densificationcannot always improve the UE performance or boost the network throughput.

Next, we shift our focus to the operations of UDNs. We first study BS cooperationsin two UDN scenarios: homogeneous and heterogeneous UDNs which aredistinguished by BS types. In both cases, the cooperation rules become more complicatedthan those in traditional networks. Either channel state information (CSI) orextra delay information needs to be acquired in order to obtain cooperation gains.At last, we investigate the feasibility of applying random beamforming to initialaccess in millimeter-wave (mmWave) UDNs. To our surprise, the simple methodcan provide sufficient performance in both control and data plane, comparing withthe existing schemes. Therefore, it may be unnecessary to develop complex algorithmsfor initial access in future dense mmWave networks. The findings indicatethat UDN may complicate network operations while it may also facilitate the use ofsimple schemes. Our work provides insights into the understanding of the networkdensification and thus paves the way for the operational design of future UDNs.