Abstract

Long-term evolution (LTE) femtocells represent a very promising answer to the ever growing bandwidth demand of mobile applications. They can be easily deployed without requiring a centralized planning, to provide high data rate connectivity with a limited coverage. In this way, the overall capacity of the cellular network can be greatly improved. At the same time, the uncoordinated setup of femtocells poses new issues that require a deep and thorough analysis before spreading this technology worldwide. Unfortunately, to the best of our knowledge, no accurate simulation tools are freely available for enabling this kind of investigation. Thus, we present in this study a simulation tool for LTE femtocells, implemented as a module of the emerging open source LTE-sim framework. It encompasses heterogeneous scenarios with both macro and femtocells, spectrum allocation techniques, user mobility, femtocell access policies, and several other features related to this promising technology. After reviewing the status of the art on LTE femtocells, we detail the description of the module that we propose with a major emphasis on the newly devised loss models for indoor scenarios, the new network topology objects, and the most significant enhancements to the simulator protocol stack. Furthermore, to provide a clear understanding of the practical utility of this new simulator, we investigate two indoor and urban scenarios. A scalability test is also presented to demonstrate the efficiency of the proposed tool in terms of processing requirements. All presented results suggest that this new module can be very interesting for the research community, due to its great flexibility and limited computational cost.

Highlights

  • The capillary diffusion of smartphones and tablets and the integration of connectivity capabilities in common life objects are generating a very fast growth of bandwidth demand for mobile applications [1]

  • This aspect becomes very critical for femtocells due to the limited computational capabilities of home evolved NodeB (HeNB): for instance, there are no guarantees that sophisticated scheduling strategies, such as those proposed in [26-28], could be straightly adopted in Long-term evolution (LTE) femtocells

  • We compared the distribution of signalto-interference plus noise ratio (SINR) provided by the WinnerII channel model inside a 5 × 5 apartment grid, supposing to assign the spectrum by means of the reuse-1 and the reuse-1/2 scheme

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Summary

Introduction

The capillary diffusion of smartphones and tablets and the integration of connectivity capabilities in common life objects (such as TVs, domestic appliances, and vehicles) are generating a very fast growth of bandwidth demand for mobile applications [1]. Despite it provides standard compliant definition of the LTE network architecture as well as several propagation loss models for indoor scenarios, at the current status it cannot be sufficient in helping researchers during the study of femtocell related issues It does not implement any handover strategies for HetNet, it does not allow the application of different access policies to the HeNB, it offers only a weak support for the quality of service (QoS) management [17] (e.g., only simple scheduling strategies, such as Maximum Throughput and Proportional Fair, have been developed at the MAC layer). In [20], the 3GPP introduced a new low-power and small-range radio based station, i.e., the HeNB, for providing broadband services in indoor and outdoor environments Such a device is connected to the operator network through a DSL line available at consumers’ houses or offices, like a common Wi-Fi access point. There are several interesting problems that could arise with a wide deployment of LTE femtocells, which have to be carefully accounted for in order to exploit all the potential of this new promising technology

How to cope with uncoordinated femtocell deployment?
New topology objects Three new network topology objects have been introduced:
Studying the impact of co-layer interference in an indoor environment
40 UEs 80 UEs 120 UEs
Conclusions
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