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A package for polar codes in Python.

Project description

Polar Codes in Python

A library written in Python3 for Polar Codes, a capacity-achieving channel coding technique used in 5G. The library includes functions for construction, encoding, decoding, and simulation of polar codes. In addition, it supports puncturing and shortening.

It provides:

  • non-systemic encoder and Successive Cancellation Decoder (SCD) for polar codes.
  • mothercode construction of polar codes using Bhattacharyya Bounds or Gaussian Approximation
  • support for puncturing and shortening.
  • Bit-Reversal Shortening (BRS), Wang-Liu Shortening (WLS), and Bioglio-Gabry-Land (BGL) shortening constructions.
  • an AWGN channel with BPSK modulation.


A YouTube video with an introduction to polar codes, shortening, and the library: IMAGE ALT TEXT

Getting Started

  1. Install the package with pip install py-polar-codes (
  2. Install matplotlib from
  3. Install numpy from
  4. Run using a Python3 compiler. If the program runs successfully, the library is ready to use. Make sure the compiler has writing access to directory "root/data", where simulation data will be saved by default.
  5. Run to start the GUI.


Mothercode Encoding & Decoding

An example of encoding and decoding over an AWGN channel for a (256,100) mothercode, using Bhattacharyya Bounds and SCD.

   import numpy as np
   from polarcodes import *

    # initialise polar code
    myPC = PolarCode(256, 100)
    myPC.construction_type = 'bb'
    # mothercode construction
    design_SNR  = 5.0
    Construct(myPC, design_SNR)
    print(myPC, "\n\n")
    # set message
    my_message = np.random.randint(2, size=myPC.K)
    print("The message is:", my_message)
    # encode message
    print("The coded message is:", myPC.x)
    # transmit the codeword
    AWGN(myPC, design_SNR)
    print("The log-likelihoods are:", myPC.likelihoods)
    # decode the received codeword
    print("The decoded message is:", myPC.message_received)

Shortened Code Construction

An example of constructing a shortened polar code with Bit-Reversal Shortening (BRS) algorithm.

   import numpy as np
   from polarcodes import *

    # initialise shortened polar code
    shorten_params = ('shorten', 'brs', None, None, False)
    myPC = PolarCode(200, 100, shorten_params)
    # construction
    design_SNR  = 5.0
    Shorten(myPC, design_SNR)
    print(myPC, "\n\n")

Simulation & Plotting

A script to simulate a defined polar code, save the data to a JSON file in directory "/data", and then display the result in a matplotlib figure.

    # simulate polar code 
    myPC.simulate(save_to='data/pc_sim', Eb_No_vec=np.arange(1,5), design_SNR=5.0, manual_const_flag=True)
    # plot the frame error rate
    myPC.plot(['pc_sim'], 'data/')

The simulation will save your Polar Code object in a JSON file, for example:

    "N": 64,
    "n": 6,
    "K": 32,
    "frozen": [
        22, 38, 49, 26, 42, 3, 28, 50, 5,44,9, 52, 6, 17, 10, 33, 56, 18, 12, 34, 20, 36, 1, 24, 40, 48, 2, 4, 8, 16, 32, 0
    "construction_type": "bb",
    "punct_flag": false,
    "punct_type": "",
    "punct_set": [],
    "source_set": [],
    "punct_algorithm": "",
    "update_frozen_flag": [],
    "BER": [
    "FER": [
    "SNR": [

This is a final year project created by Brendon McBain under the supervision of Dr Harish Vangala at Monash University.

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