# sdr
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The `sdr` library is a Python 3 package for software-defined radio (SDR).
The goal of `sdr` is to provide tools to design, analyze, build, and test digital communication systems
in Python. The library relies on and is designed to be interoperable with NumPy, SciPy, and Matplotlib.
Performance is also very important. So, where possible, Numba is used to accelerate computationally-intensive
functions.
Additionally, the library aims to replicate relevant functionality from MATLAB's Communications and
DSP Toolboxes.
We are progressively adding functionality to the library. If there is something you'd like to see included
in `sdr`, please open an issue on GitHub.
> Enjoying the library? Give us a :star: on [GitHub](https://github.com/mhostetter/sdr)!
## Documentation
The documentation for `sdr` is located at <https://mhostetter.github.io/sdr/latest/>.
## Installation
The latest version of `sdr` can be installed from [PyPI](https://pypi.org/project/sdr/) using `pip`.
```console
python3 -m pip install sdr
```
## Features
View all available classes and functions in the [API Reference](https://mhostetter.github.io/sdr/latest/api/dsp/).
- **Digital signal processing**: Finite impulse response (FIR) filter, FIR filter design,
infinite impulse response (IIR) filter, polyphase interpolator, polyphase decimator, polyphase resampler,
polyphase channelizer, Farrow arbitrary resampler, fractional delay FIR filter, FIR moving average,
FIR differentiator, IIR integrator, IIR leaky integrator, complex mixing, real/complex conversion.
- **Sequences**: Barker, Hadamard, Walsh, Zadoff-Chu.
- **Modulation**: Phase-shift keying (PSK), $\pi/M$ PSK, offset QPSK, rectangular pulse shape, half-sine pulse shape,
raised cosine pulse shape, root raised cosine pulse shape, Gaussian pulse shape, binary and Gray symbol mapping,
differential encoding.
- **Synchronization**: Numerically-controlled oscillator (NCO), loop filter, closed-loop phase-locked loop (PLL)
analysis, automatic gain control (AGC), phase error detector (PEDs).
- **Measurement**: Energy, power, voltage, Euclidean distance, Hamming distance, bit/symbol error rate,
error vector magnitude (EVM).
- **Conversions**: Between linear units and decibels. Between $E_b/N_0$, $E_s/N_0$, and $S/N$.
- **Simulation**: Binary symmetric channel (BSC), binary erasure channel (BEC), discrete memoryless channel (DMC),
additive white Gaussian noise (AWGN), frequency offset, sample rate offset, IQ imbalance.
- **Link budgets**: Channel capacity, free-space path loss, antenna gain.
- **Data manipulation**: Packing and unpacking binary data, hexdump of binary data.
- **Plotting**: Time-domain, raster, periodogram, spectrogram, constellation, symbol map, eye diagram,
bit error rate (BER), symbol error rate (SER), impulse response, step response, magnitude response, phase response,
phase delay, group delay, and zeros/poles.
## Examples
There are detailed examples published at <https://mhostetter.github.io/sdr/latest/examples/pulse-shapes/>.
The Jupyter notebooks behind the examples are available for experimentation in `docs/examples/`.
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