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.