Giter Site home page Giter Site logo

turbofec's Introduction

About TurboFEC

TurboFEC is an implementation of LTE forward error correction encoders and decoders. Included are convolutional codes, turbo codes, and associated rate matching units that handle block interleaving, bit selection, and pruning.

Using x86 SIMD instructions, the convolutional and turbo decoders are currently the fastest implementations openly available. If you believe the preceding statement to be false, please contact the author to discuss further optimizations.

Convolutional decoding uses Intel SSE3, SSE4, and AVX2 instructions if available.

Turbo decoding requires Intel SSE3 or higher.

LTE specification and sections:

3GPP TS 36.212 "LTE Multiplexing and channel coding"

5.1.3.1 "Tail biting convolutional code"

5.1.3.2 "Turbo encoding"

5.1.3.1 "Rate matching for turbo coded transport channels"

5.1.3.2 "Rate matching for convolutionally coded transport channels and control information"

Compile

$ autoreconf -i
$ ./configure
$ make

Test

$ make check

A collection of GSM, LTE, and other forward error correcting codes will be tested.

=================================================
[+] Testing: GSM TCH/AHS 5.15
[.] Specs: (N=3, K=5, recursive, flushed, punctured)

[.] BER test:
[..] Testing:
[..] Input BER.......................... 0.007450
[..] Output BER......................... 0.000000
[..] Output FER......................... 0.000000

=================================================
[+] Testing: LTE PBCH
[.] Specs: (N=3, K=7, non-recursive, tail-biting, non-punctured)

[.] BER test:
[..] Testing:
[..] Input BER.......................... 0.007478
[..] Output BER......................... 0.000000
[..] Output FER......................... 0.000000

PASS: conv_test

=================================================
[+] Testing: 3GPP LTE turbo
[.] Specs: (N=2, K=4), Length 6144

[.] BER test:
[..] Testing:
[..] Input BER.......................... 0.007479
[..] Output BER......................... 0.000000
[..] Output FER......................... 0.000000

PASS: turbo_test

Install

$ sudo make install

Benchmark

Various convolutional and turbo decoding tests are available.

$ tests/turbo_test -h
Options:
  -h    This text
  -p    Number of packets (per thread)
  -j    Number of threads for benchmark
  -i    Number of turbo iterations
  -a    Run all tests
  -b    Run benchmark tests
  -n    Run length checks
  -r    Specify SNR in dB (default 8.0 dB)
  -e    Run bit error rate tests
  -c    Test specific code
  -l    List supported codes

Benchmark LTE turbo codes with 8 threads, 4 iterations, and 10000 blocks per thread.

$ tests/turbo_test -b -j 8 -i 4 -p 10000

=================================================
[+] Testing: 3GPP LTE turbo
[.] Specs: (N=2, K=4), Length 6144

[.] Performance benchmark:
[..] Decoding 80000 bursts on 8 thread(s) with 4 iteration(s)
[..] Testing:
[..] Elapsed time....................... 5.925372 secs
[..] Rate............................... 83.043313 Mbps

turbofec's People

Contributors

openphy avatar ttsou avatar neofob avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.