No abstract

Network densification has been identified as one key enabling technology to address the 1000x mobile data challenge. This article analyzes network densification from the different deployment options perspective by looking into three mainstream technologies; Macrocells, Microcells, and Femtocells. The technologies are evaluated in a suburban neighborhood with modern residential houses. As majority of the data traffic in the network is believed to be generated by indoor users, we make a techno-economic analysis and comparison of the different deployment strategies from the indoor local area service provisioning viewpoint. Results show superior performance of low power indoor femtocell based deployment solutions in terms of coverage, capacity, energy and cost efficiency as compared to the outdoor solutions. Densifying the traditional pure Macro or Micro layers does provide improvement in the indoor coverage levels, however, due to the closer proximity of the co-channel interfering sites, the achievable capacity in the indoor environment deteriorates, which in turn also affects the energy and cost efficiency. These findings strongly motivate towards ultra dense deployments, based on indoor femtocell solutions, for addressing the local area capacity needs of the emerging future 5G networks.

ABSTRACT

In this article, we study and analyze the impact of modern buildings, with increased building penetration losses (BPLs), on different cellular deployment strategies based on tra ditional outdoor (macro) and dedicated indoor (femto) solutions in a suburban environment. The analysis covers both indoor and outdoor use cases, and the performance of the deployment strategies is evaluated in terms of network coverage, spectral and energy efficiency. The obtained results indicate that the indoor performance of pure macrocellular network in terms of coverage, capacity and energy efficiency is highly degraded with increasing wall penetration losses of modern buildings. Hence, the best strategy to overcome this problem is by deploying indoor femtocells, whose indoor performance is shown to actually benefit from increased BPLs. However, the outdoor performance of pure femtocell deployment is shown to degrade due to increased BPLs. Stemming from this, a heterogeneous Macro-Femto co channel deployment solution is also analyzed and shown to deliver a balanced performance for both outdoor and indoor environments in terms of coverage, capacity and energy efficiency.These findings strongly motivate towards heterogeneous network deployments in the future, where indoor network elements play an increasingly important role.

Ultradense deployment of small cells is being considered as one of the key flavors of the emerging 5G cellular networks to address the future data capacity challenges. A large share of these deployments will be indoor, as this is the arena where the majority of the data traffic is believed to originate from in the future. Indoor small cell solutions (e.g., femtocell or WiFi) are well positioned for delivering superior indoor coverage and capacity. However, due to relatively smaller coverage footprint compared to traditional macrocells, a very dense deployment of small cells will be needed in order to have a ubiquitous indoor coverage. Such dense deployment triggers cost and energy efficiency concerns for mobile operators. In this paper, we analyze and compare the technoeconomic performance of two deployment strategies: homogeneous macrocellular densification and heterogeneous macro-femto deployment strategy, from an indoor service provisioning perspective. Particularly, we analyze and contrast the performance of macro-femto based deployment, with varying femtocell market penetration rate and under different femtocell backhaul connectivity constraints, with that of homogeneous macrocellular densification. The results indicate superior performance of indoor femtocell based deployment as compared to macrocellular-only densification, due to better indoor coverage, radio channel conditions, and high degree of spatial reuse.