The sdr package

[Tags:benchmark, bsd3, test]

Write software defined radio applications in Haskell.

Features:

See https://github.com/adamwalker/sdr for more features and screenshots.

A collection of simple apps that use this library can be found here. These include an FM radio receiver, an OpenGL waterfall plotter and an AM radio receiver.


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Properties

Versions 0.1.0.0, 0.1.0.1, 0.1.0.2, 0.1.0.3, 0.1.0.4, 0.1.0.5, 0.1.0.6, 0.1.0.8, 0.1.0.9
Dependencies array (>=0.4 && <0.6), base (>=4.7 && <4.9), bytestring (==0.10.*), cairo (==0.13.*), cereal (==0.4.*), Chart (>=1.3 && <1.5), Chart-cairo (>=1.3 && <1.5), colour (==2.3.*), containers (==0.5.*), Decimal (==0.4.*), dynamic-graph (==0.1.0.8), either (>=4.1 && <4.4), fftwRaw (==0.1.*), GLFW-b (==1.4.7.*), OpenGL (>=2.11 && <2.13), optparse-applicative (==0.11.*), pango (==0.13.*), pipes (==4.1.*), pipes-bytestring (>=2.0 && <2.2), pipes-concurrency (==2.0.*), primitive (>=0.5 && <0.7), pulse-simple (==0.1.*), rtlsdr (==0.1.*), storable-complex (==0.2.*), time (>=1.4 && <1.6), tuple (>=0.2 && <0.4), vector (==0.10.*) [details]
License BSD3
Copyright 2015 Adam Walker
Author Adam Walker
Maintainer adamwalker10@gmail.com
Category Software Defined Radio
Home page https://github.com/adamwalker/sdr
Bug tracker https://github.com/adamwalker/sdr/issues
Source repository head: git clone https://github.com/adamwalker/sdr
Uploaded Thu Jun 4 12:52:14 UTC 2015 by adamwalker
Distributions NixOS:0.1.0.9
Downloads 604 total (4 in the last 30 days)
Votes
0 []
Status Docs uploaded by user
Build status unknown [no reports yet]

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Maintainer's Corner

For package maintainers and hackage trustees

Readme for sdr

Readme for sdr-0.1.0.3

SDR

A Software Defined Radio library written in Haskell

Features

  • Write software defined radio applications in Haskell
  • Signal processing blocks can be chained together using the Pipes library
  • Zero copy design
  • Signal processing functions are implemented in both Haskell and C:
    • Optimised C implementations of signal processing functions that utilise SIMD instructions
    • Performance of Haskell signal processing functions within a factor of 2 of C (without SIMD) thanks to the vector library, stream fusion and ghc's LLVM backend
  • Can filter, decimate and resample
  • Helper functions for FIR filter design using window functions and plotting of the frequency response
  • FFTs using FFTW
  • Line and waterfall plots using OpenGL
  • FM demodulation
  • PulseAudio sound sink
  • rtl-sdr based radio source supported and other sources are easily added
  • Extensive benchmark and test suites of signal processing functions

See https://github.com/adamwalker/sdr-apps for a collection of simple apps built on the library and https://github.com/adamwalker/sdr-demo for a demo application.

Screenshot

A chunk of the FM broadcast spectrum. Captured with an RTLSDR device and drawn as a waterfall using the Plot module.

Screenshot

Getting Started

Installation

You can install it from Hackage:

cabal install sdr

Or, you can build it with cabal sandboxes:

cabal sandbox init
git clone https://github.com/adamwalker/dynamic-graph
git clone https://github.com/adamwalker/haskell-fftw-simple
git clone https://github.com/adamwalker/sdr
cabal sandbox add-source dynamic-graph haskell-fftw-simple sdr
cabal install sdr

Example Applications

A collection of simple apps can be found here. These include an FM radio receiver, an OpenGL waterfall plotter and an AM radio receiver that can be used to listen to Airband.

Clone and build:

git clone https://github.com/adamwalker/sdr-apps  
cabal sandbox add-source sdr-apps
cabal install sdr-apps

To run the FM receiver:

.cabal-sandbox/bin/fm -f <your favourite station, e.g. 90.2M>  

To run the waterfall plot:

.cabal-sandbox/bin/waterfall -f <center frequency, e.g. 90.2M> -r <sample rate, e.g. 1280M>

To run the AM receiver:

.cabal-sandbox/bin/am -f <center frequency, e.g. 124.4M> 

Usage

Documentation is available on Hackage.

An FM receiver:

import           Control.Monad.Trans.Either
import           Data.Vector.Generic        as VG 
import           Pipes
import qualified Pipes.Prelude              as P
import           Foreign.Storable.Complex

import SDR.Filter 
import SDR.RTLSDRStream
import SDR.Util
import SDR.Demod
import SDR.Pulse
import SDR.CPUID

--The filter coefficients are stored in another module
import Coeffs

samples    = 8192
frequency  = 105700000

main = eitherT putStrLn return $ do

    info <- lift getCPUInfo

    str  <- sdrStream frequency 1280000 1 (fromIntegral samples * 2)

    lift $ do

        sink <- pulseAudioSink

        deci <- fastDecimatorC info 8 coeffsRFDecim 
        resp <- fastResamplerR info 3 10 coeffsAudioResampler
        filt <- fastFilterSymR info coeffsAudioFilter

        runEffect $   str
                  >-> P.map convertCAVX 
                  >-> firDecimator deci samples 
                  >-> fmDemod
                  >-> firResampler resp samples 
                  >-> firFilter filt samples
                  >-> P.map (VG.map (* 0.2)) 
                  >-> sink

Disclaimer

I started this project to learn about signal processing. I still have no idea what I'm doing.

Only tested on Arch Linux.

If you actually use this library for anything, let me know: adamwalker10@gmail.com