sparsenc

KO | EN

gitlite — search

#javascript #python #react #go #reactjs #nextjs #firebase #typescript #android #machine-learning #ios #html

★ 31 Open GitHub ↗

A library for encoding and decoding sparse network codes

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

<h1>IMPORTANT NOTICE</h1>

Due to personal reasons, the source codes **have been taken down** from this public repository.

If you are interesed in using sparsenc, please send request to <ins>yeli[AT]ntu.edu.cn</ins> from an **institutional email** with your name.

Please note that public domain emails (such as qq.com, gmail.com, hotmail.com etc.) will **NOT** get a reply.

Introduction
============
This project provides a C implementation (and a Python wrapper) for encoding/recoding/decoding of network coding. Random linear network coding (RLNC) [1] and several of its sparse variants are implemented. The library supports three catagories of sparse network codes (SNC): random codes, band codes and BATS-like codes [2].

The following decoders are implemented:

- (sub)generation-by-(sub)generation (GG) decoder has a linear-time complexity but exhibits higher decoding-induced overhead.

- overlap-aware (OA) decoder has optimized code overhead but exhibits higher complexity.

- band (BD) and compact band (CBD) decoders that apply to band code only.

- PP(perpetual) decoder applies to decode the window-wrapped codes only.

The library had been used for performance evaluation and comparison when authoring the following papers. If you find the lib useful, please cite the papers when appropriate.

- Ye Li, J. Zhu and Z. Bao, "Sparse Random Linear Network Coding With Precoded Band Codes," in IEEE Communications Letters, vol. 21, no. 3, pp. 480-483, March 2017.

- Ye Li, W.-Y. Chan, S. Blostein, "On Design and Efficient Decoding of Sparse Random Linear Network," in IEEE Access, 5: 17031~17044, 2017.

- Ye Li, S. Zhang, J. Wang, X. Ji, H. Wu and Z. Bao, "A Low-Complexity Coded Transmission Scheme over Finite-Buffer Relay Links," in IEEE Transactions on Communications, vol. 66, no. 7, pp. 2873 - 2887, July. 2018.

- Y. Li, J. Wang, S. Zhang, Z. Bao and J. Wang, "Efficient Coastal Communications with Sparse Network Coding," in IEEE Network, vol. 32, no. 4, pp. 122-128, July/August 2018.

- Y. Li, J. Zhou, J. Wang, Z. Bao, T. Q. S. Quek and J. Wang, "On Data Dissemination Enhanced by Network Coded Device-to-Device Communications," in IEEE Transactions on Wireless Communications, vol. 19, no. 6, pp. 3963-3976, June 2020, doi: 10.1109/TWC.2020.2979145.

- Y. Li, B. Tang, J. Wang and Z. Bao, "On Multi-Hop Short-Packet Communications: Recoding or End-to-End Fountain Coding?," in IEEE Transactions on Vehicular Technology, vol. 69, no. 8, pp. 9229-9233, Aug. 2020, doi: 10.1109/TVT.2020.3005409.

Limitation
============
The library only supports coding against a given block of source packets, i.e., a *generation* of packets as termed in the network coding literature. Sliding-window mode is not supported.

A sliding-window implementation, also known as streaming coding, is available as a separate project at: https://github.com/yeliqseu/streamc, which implementes coding schemes proposed in

- M. Karzand, D. J. Leith, J. Cloud and M. Medard, "Design of FEC for Low Delay in 5G," in IEEE Journal on Selected Areas in Communications, vol. 35, no. 8, pp. 1783-1793, Aug. 2017.
- Y. Li, F. Zhang, J. Wang, T. Q. S. Quek and J. Wang, "On Streaming Coding for Low-Latency Packet Transmissions over Highly Lossy Links," in IEEE Communications Letters, 2020 (Early Access: https://ieeexplore.ieee.org/document/9075270).

Other References
============
[1] T. Ho, M. Medard, R. Koetter, and D. R. Karger, "A Random Linear Network Coding Approach to Multicast", in IEEE Transactions on Information Theory, Vol 52, No. 10, pp. 4413-4430, 2006.

[2] S. Yang and R. W. Yeung, "Batched Sparse Codes," in IEEE Transactions on Information Theory, vol. 60, no. 9, pp. 5322-5346, Sept. 2014.

sparsenc

Explore Similar Repositories

Was this content helpful?

Recent Feedback

Download README