Difference between revisions of "GSOC2022Channel"

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(Weekly Progress Reports)
(Weekly Progress Reports)
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** Implementation of the first test, i.e., MimoFtrAverageTest, which compares the empirical mean obtained using the GetFtrFastFading function with the expected theoretical one. The test is repeated for different combinations of the FTR model input parameters.
 
** Implementation of the first test, i.e., MimoFtrAverageTest, which compares the empirical mean obtained using the GetFtrFastFading function with the expected theoretical one. The test is repeated for different combinations of the FTR model input parameters.
 
** First study on how to extend the above test by checking also the Emprirical CDF. The open issue is that while other statistical tests can rely on the GNU Scientific Library to compute the CDF of the distribution and then compare it with the ECDF, the FTR model is not implemented in the GSL. Therefore, the most promising approach at the moment is to generate a set of ECDFs in MATLAB, export them and then compare them to the ECDF computed in ns-3.
 
** First study on how to extend the above test by checking also the Emprirical CDF. The open issue is that while other statistical tests can rely on the GNU Scientific Library to compute the CDF of the distribution and then compare it with the ECDF, the FTR model is not implemented in the GSL. Therefore, the most promising approach at the moment is to generate a set of ECDFs in MATLAB, export them and then compare them to the ECDF computed in ns-3.
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* '''Week 3'''
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** Further study of ECDF test for the FTR fading model. Consistency checks with the original paper led to finding typos in the closed form CDF and PDF equations. Currently exchanging mails with the authors to fix them and have a correct reference.
 +
** Definition and implementation of the computation of the combined array and beamforming gains in the MimoSpectrumPropagationLossModel class, by defining the CalcBeamformingGain.

Revision as of 09:31, 6 July 2022

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Project Overview

  • Project Name: A simplified channel and beamforming model for ns-3
  • Student: Matteo Pagin
  • Mentors: Sandra Lagen, Biljana Bojovic, Michele Polese
  • Google page: https://summerofcode.withgoogle.com/programs/2022/projects/uxXqy83g
  • Project Goals: Currently, ns-3 provides the TR 38.901 channel model as the default option for sampling MIMO wireless channels which take into account the presence of (possibly directional) multiple antenna elements at both transmitter and receiver. However, this model represents a major performance bottleneck for most end-to-end simulations, especially whenever they involve upwards of hundreds of nodes. Accordingly, the goal of my proposal is twofold:
    • to provide ns-3 with a simplified statistical channel model, to be used for analyses which are focused on the upper layers of the protocol stack only, and
    • to improve the performance of the TR 38.901-based framework which is currently available in ns-3, for the remainder of the use cases.
  • Repository: GitLab
  • About Me: I am a first year PhD student at the University of Padova, working with the SIGNET group under the supervision of professor Michele Zorzi. Previously, I have been a research engineer in the same group, and I have obtained both my master and bachelor degree from the University of Padova, in Information Engineering and ICT for Internet and Multimedia, respectively. During these first years of my research career I have been working quite extensively with ns-3, primarily by working on the mmwave module for simulating 5G cellular networks. However, with this project I aim to contribute in a more direct manner to the ns-3 project! I spend most of my free time having "aperitivo"s with friends, training at the gym, hiking and learning to play the guitar.
  • Project proposal: GDrive link

Milestones and Deliverables

Project plan, which will be periodically updated during the whole GSoC: GDoc.

The project objectives will be achieved through three incremental updates of the spectrum and antenna modules, representing the project deliverables and each providing additional features with respect to the previous one. Specifically, the following deliverables are planned:

  • D1, which will comprise the addition of the simplified channel and beamforming models and which will be completed by the end of Week 5.
  • D2, which will include the port of the spectrum and antenna modules to the Eigen linear algebra library and the aforementioned optimizations. It will be completed by the end of Week 9.
  • D3, which will comprise the validation campaign for the 3GPP model and the calibration of the simplified model, based on the former. This deliverable will be completed by the end of Week 12.

Weekly Progress Reports

  • Week 1
    • Discussion with the mentors and the ns-3 maintainers regarding the level of integration of Eigen in ns-3. Optional, external installation is the chosen approach.
    • Study of the FTR fading model, draft implementation in MATLAB and consistency checks among such implementation and the related paper.
    • Further definition of the calibration steps. Identification of the 3GPP calibration campaigns which can be used to such end. Since most of the latter make use of older versions of the 38.901 SCM (v14.0.0), only selected scenarios will be calibrated, i.e., the ones which are consistent among the v.14.0.0 and the one currently implemented in ns-3. The full SCM will be calibrated first, using the 3GPP campaigns as a reference. Then, the simplified channel model will be calibrated using the latter.
  • Week 2
    • Definition of the APIs of the new SpectrumPropagationLossModel, i.e., MimoSpectrumPropagationLossModel, which extends the PhasedArraySpectrumPropagationLossModel class and implements the performance-oriented channel model.
    • Implementation of the GetFtrFastFading function, which samples the squared norm of a fading sample distributed as per the Two-Ray Fluctuating (FTR) Model fast-fading model.
    • Implementation of the first test, i.e., MimoFtrAverageTest, which compares the empirical mean obtained using the GetFtrFastFading function with the expected theoretical one. The test is repeated for different combinations of the FTR model input parameters.
    • First study on how to extend the above test by checking also the Emprirical CDF. The open issue is that while other statistical tests can rely on the GNU Scientific Library to compute the CDF of the distribution and then compare it with the ECDF, the FTR model is not implemented in the GSL. Therefore, the most promising approach at the moment is to generate a set of ECDFs in MATLAB, export them and then compare them to the ECDF computed in ns-3.
  • Week 3
    • Further study of ECDF test for the FTR fading model. Consistency checks with the original paper led to finding typos in the closed form CDF and PDF equations. Currently exchanging mails with the authors to fix them and have a correct reference.
    • Definition and implementation of the computation of the combined array and beamforming gains in the MimoSpectrumPropagationLossModel class, by defining the CalcBeamformingGain.