Next Article in Journal
Maxwell’s Demon—A Historical Review
Next Article in Special Issue
On the Energy-Distortion Tradeoff of Gaussian Broadcast Channels with Feedback
Previous Article in Journal
Lyapunov Spectra of Coulombic and Gravitational Periodic Systems
Previous Article in Special Issue
Leveraging Receiver Message Side Information in Two-Receiver Broadcast Channels: A General Approach †
Article

On Linear Coding over Finite Rings and Applications to Computing

Communication Theory Lab, School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm 10044, Sweden
*
Author to whom correspondence should be addressed.
Academic Editor: Raúl Alcaraz Martínez
Entropy 2017, 19(5), 233; https://doi.org/10.3390/e19050233
Received: 6 January 2017 / Revised: 24 April 2017 / Accepted: 15 May 2017 / Published: 20 May 2017
(This article belongs to the Special Issue Network Information Theory)
This paper presents a coding theorem for linear coding over finite rings, in the setting of the Slepian–Wolf source coding problem. This theorem covers corresponding achievability theorems of Elias (IRE Conv. Rec. 1955, 3, 37–46) and Csiszár (IEEE Trans. Inf. Theory 1982, 28, 585–592) for linear coding over finite fields as special cases. In addition, it is shown that, for any set of finite correlated discrete memoryless sources, there always exists a sequence of linear encoders over some finite non-field rings which achieves the data compression limit, the Slepian–Wolf region. Hence, the optimality problem regarding linear coding over finite non-field rings for data compression is closed with positive confirmation with respect to existence. For application, we address the problem of source coding for computing, where the decoder is interested in recovering a discrete function of the data generated and independently encoded by several correlated i.i.d. random sources. We propose linear coding over finite rings as an alternative solution to this problem. Results in Körner–Marton (IEEE Trans. Inf. Theory 1979, 25, 219–221) and Ahlswede–Han (IEEE Trans. Inf. Theory 1983, 29, 396–411, Theorem 10) are generalized to cases for encoding (pseudo) nomographic functions (over rings). Since a discrete function with a finite domain always admits a nomographic presentation, we conclude that both generalizations universally apply for encoding all discrete functions of finite domains. Based on these, we demonstrate that linear coding over finite rings strictly outperforms its field counterpart in terms of achieving better coding rates and reducing the required alphabet sizes of the encoders for encoding infinitely many discrete functions. View Full-Text
Keywords: linear coding; source coding; ring; field; source coding for computing linear coding; source coding; ring; field; source coding for computing
Show Figures

Figure 1

MDPI and ACS Style

Huang, S.; Skoglund, M. On Linear Coding over Finite Rings and Applications to Computing. Entropy 2017, 19, 233. https://doi.org/10.3390/e19050233

AMA Style

Huang S, Skoglund M. On Linear Coding over Finite Rings and Applications to Computing. Entropy. 2017; 19(5):233. https://doi.org/10.3390/e19050233

Chicago/Turabian Style

Huang, Sheng, and Mikael Skoglund. 2017. "On Linear Coding over Finite Rings and Applications to Computing" Entropy 19, no. 5: 233. https://doi.org/10.3390/e19050233

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop