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CommPy is an open source toolkit implementing digital communications algorithms in Python using SciPy, NumPy and Cython.

• To provide readable and useable implementations of algorithms used in the research, design and implementation of digital communication systems.

• Encoder for Convolutional Codes (Polynomial, Recursive Systematic). Supports all rates and puncture matrices.
• Viterbi Decoder for Convolutional Codes (Hard Decision Output).
• MAP Decoder for Convolutional Codes (Based on the BCJR algorithm).
• Encoder for a rate-1/3 systematic parallel concatenated Turbo Code.
• Turbo Decoder for a rate-1/3 systematic parallel concatenated turbo code (Based on the MAP decoder/BCJR algorithm).
• Binary Galois Field GF(2^m) with minimal polynomials and cyclotomic cosets.
• Create all possible generator polynomials for a (n,k) cyclic code.
• Random Interleavers and De-interleavers.

• Binary Erasure Channel (BEC)
• Binary Symmetric Channel (BSC)
• Binary AWGN Channel (BAWGNC)

• Rectangular
• Raised Cosine (RC), Root Raised Cosine (RRC)
• Gaussian

• Carrier Frequency Offset (CFO)

• Phase Shift Keying (PSK)
• Quadrature Amplitude Modulation (QAM)
• OFDM Tx/Rx signal processing

• PN Sequence
• Zadoff-Chu (ZC) Sequence

• Decimal to bit-array, bit-array to decimal.
• Hamming distance, Euclidean distance.
• Upsample

During my coursework in communication theory and systems at UCSD, I realized that the best way to actually learn and understand the theory is to try and implement ''the Math'' in practice :). Having used Scipy before, I thought there should be a similar package for Digital Communications in Python. This is a start!

CommPy uses Python as its base programming language and python packages like NumPy, SciPy and Matplotlib. Some algorithms which are too slow in a pure Python implementation are implemented using Cython.

Implement any feature you want and send me a pull request :). If you want to suggest new features or discuss anything related to CommPy, please get in touch with me (veeresht@gmail.com).

• Python 2.7 or above
• NumPy 1.6 or above
• SciPy 0.10 or above
• Matplotlib 1.1 or above
• Cython 0.15 or above

• Clone from github and install as follows (recommended):

  $ git clone https://github.com/veeresht/CommPy.git
  $ cd CommPy
  $ sudo python setup.py build_ext --inplace
  $ sudo python setup.py install 

• To install using pip or easy_install use the following commands:

  $ sudo pip install scikit-commpy
  $ sudo easy_install scikit-commpy 

I would greatly appreciate your feedback if you have found CommPy useful. Just send me a mail: veeresht@gmail.com

For more details on CommPy, please visit http://veeresht.github.com/CommPy