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ns-3 module for simulating mmWave-based cellular systems. See https://ieeexplore.ieee.org/document/8344116/ (open access) as a reference.
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# mmWave ns-3 module # This is an [ns-3](https://www.nsnam.org "ns-3 Website") module for the simulation of 5G cellular networks operating at mmWaves. A description of this module can be found in [this paper](https://ieeexplore.ieee.org/document/8344116/ "mmwave paper"). Main features: * Support of a wide range of channel models, including the model based on 3GPP TR 38.901 for frequencies between 0.5 and 100 GHz. Ray tracing and measured traces can also be used. * Custom PHY and MAC classes supporting the 3GPP NR frame structure and numerologies. * Custom schedulers for supporting dynamic TDD formats * Carrier Aggregation at the MAC layer * Enhancements to the RLC layer with re-segmentation of packets for retransmissions * Dual Connectivity with LTE base stations, with fast secondary cell handover and channel tracking * Simulation of core network elements (with also the MME as a real node) ## Installation This repository contains a complete ns-3 installation with the addition of the mmwave module. Use these commands to download and build `ns3-mmwave`: ``` git clone https://github.com/nyuwireless-unipd/ns3-mmwave.git cd ns3-mmwave ./ns3 configure --disable-python --enable-examples && ./ns3 build ``` ## Usage example You can use the following command to run the `mmwave-simple-epc` example. ``` ./ns3 run mmwave-simple-epc ``` Other examples are included in `src/mmwave/examples/` ## Documentation The documentation of this module is available at [this link](./src/mmwave/doc/mmwave-doc.md). ## Related modules - MilliCar is an ns-3 module for the simulation of mmWave NR V2X networks. Check [this repo](https://github.com/signetlabdei/millicar) for further details. - A seperate module is being developed for [mmWave UE Energy Consumption](https://github.com/arghasen10/mmwave-energy "mmwave-energy"). You can use this module for analyzing Energy Consumption behaviour of mmwave UE. Check this repository for further details. - `ns3-mmwave-iab` is an extended version of `ns3-mmWave` adding wireless relaying capabilities to an ns-3 NetDevice, and the possibility of simulating in-band relaying at mmWave frequencies. Check [this repo](https://github.com/signetlabdei/ns3-mmwave-iab) for further details. ## References The following papers describe in detail the features implemented in the mmWave module: - [End-to-End Simulation of 5G mmWave Networks](https://ieeexplore.ieee.org/document/8344116/ "comst paper") is a comprehensive tutorial with a detailed description of the whole module. We advise the researchers interested in this module to start reading from this paper; - [Integration of Carrier Aggregation and Dual Connectivity for the ns-3 mmWave Module](https://arxiv.org/abs/1802.06706 "wns3 2018") describes the Carrier Aggregation implementation; - [Implementation of A Spatial Channel Model for ns-3](https://arxiv.org/abs/2002.09341 "wns3 2020") describes the integration of the spatial channel model based on the 3GPP specifications TR 38.901 V15.0.0; - [Performance Comparison of Dual Connectivity and Hard Handover for LTE-5G Tight Integration](https://arxiv.org/abs/1607.05425 "simutools paper") describes the Dual Connectivity feature. These other papers describe features that were implemented in older releases: - [ns-3 Implementation of the 3GPP MIMO Channel Model for Frequency Spectrum above 6 GHz](https://dl.acm.org/citation.cfm?id=3067678 "wns3 2017") describes the implementation of the 3GPP channel model based on TR 38.900; - [Multi-Sector and Multi-Panel Performance in 5G mmWave Cellular Networks](https://arxiv.org/abs/1808.04905 "globecom2018") describes the multi-sector addition to the 3GPP channel model; If you use this module in your research, please cite: M. Mezzavilla, M. Zhang, M. Polese, R. Ford, S. Dutta, S. Rangan, M. Zorzi, _"End-to-End Simulation of 5G mmWave Networks,"_ in IEEE Communications Surveys & Tutorials, vol. 20, no. 3, pp. 2237-2263, thirdquarter 2018. [bibtex available here](https://ieeexplo
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
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