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A Framework for End-to-End Evaluation of 5G mmWave Cellular Networks in ns-3

Published:15 June 2016Publication History

ABSTRACT

The growing demand for ubiquitous mobile data services along with the scarcity of spectrum in the sub-6 GHz bands has given rise to the recent interest in developing wireless systems that can exploit the large amount of spectrum available in the millimeter wave (mmWave) frequency range. Due to its potential for multi-gigabit and ultra-low latency links, mmWave technology is expected to play a central role in 5th Generation (5G) cellular networks. Overcoming the poor radio propagation and sensitivity to blockages at higher frequencies presents major challenges, which is why much of the current research is focused at the physical layer. However, innovations will be required at all layers of the protocol stack to effectively utilize the large air link capacity and provide the end-to-end performance required by future networks.

Discrete-event network simulation will be an invaluable tool for researchers to evaluate novel 5G protocols and systems from an end-to-end perspective. In this work, we present the first-of-its-kind, open-source framework for modeling mmWave cellular networks in the ns-3 simulator. Channel models are provided along with a configurable physical and MAC-layer implementation, which can be interfaced with the higher-layer protocols and core network model from the ns-3 LTE module to simulate end-to-end connectivity. The framework is demonstrated through several example simulations showing the performance of our custo mmmWave stack.

References

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  1. A Framework for End-to-End Evaluation of 5G mmWave Cellular Networks in ns-3

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      • Published in

        cover image ACM Other conferences
        WNS3 '16: Proceedings of the 2016 Workshop on ns-3
        June 2016
        148 pages
        ISBN:9781450342162
        DOI:10.1145/2915371

        Copyright © 2016 ACM

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        Publication History

        • Published: 15 June 2016

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        WNS3 '16 Paper Acceptance Rate18of28submissions,64%Overall Acceptance Rate54of82submissions,66%

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