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Effective Aperture Distribution Function

Project description

Python 3.6 Python 3.7 Python 3.8 Build Status Documentation Status codecov Codacy Badge Black PyPI license PyPI format PyPI implementation PyPI version fury.io

Motivation

Geometry-based MIMO channel modelling and a high-resolution parameter estimation are applications in which a precise description of the radiation pattern of the antenna arrays is required. In this package we implement an efficient representation of the polarimetric antenna response, which we refer to as the Effective Aperture Distribution Function (EADF). High-resolution parameter estimation are applications in which this reduced description permits us to efficiently interpolate the beam pattern to gather the antenna response for an arbitrary direction in azimuth and elevation. Moreover, the EADF provides a continuous description of the array manifold and its derivatives with respect to azimuth and elevation. The latter is valuable for the performance evaluation of an antenna array as well as for gradient-based parameter estimation techniques.

Instructions

Installation

Currently we simply have a source only distribution setup. To install the latest tagged release just use pip install eadf. Otherwise you can simply run pip install -e . --user in your local git clone to get a development setup running.

Documentation

We also have recent documentation on readthedocs. Locally you can build it your git clone via python setup.py build_sphinx -E.

Contributing

We are always happy about unhapppy users, who run into problems, report bugs, file pull requests or cheer for our nice package. If you want something merged, please create a pull request against master and we are happy to review them.

References

Full 3D Antenna Pattern Interpolation Using Fourier Transform Based Wavefield Modelling; S. Haefner, R. Mueller, R. S. Thomae; WSA 2016; 20th International ITG Workshop on Smart Antennas; Munich, Germany; pp. 1-8

Impact of Incomplete and Inaccurate Data Models on High Resolution Parameter Estimation in Multidimensional Channel Sounding, M. Landmann, M. Käske and R.S. Thomä; IEEE Trans. on Antennas and Propagation, vol. 60, no 2, February 2012, pp. 557-573

Efficient antenna description for MIMO channel modelling and estimation, M. Landmann, G. Del Galdo; 7th European Conference on Wireless Technology; Amsterdam; 2004; IEEE Link

Geometry-based Channel Modeling for Multi-User MIMO Systems and Applications, G. Del Galdo; Dissertation, Research Reports from the Communications Research Laboratory at TU Ilmenau; Ilmenau; 2007; Download

Limitations of Experimental Channel Characterisation, M. Landmann; Dissertation; Ilmenau; 2008; Download

Project details


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