Hardware Acceleration for RLNC: A Case Study Based on the Xtensa Processor with the Tensilica Instruction-Set Extension
Random linear network coding (RLNC) can greatly aid data transmission in lossy wireless networks. However, RLNC requires computationally complex matrix multiplications and inversions in finite fields (Galois fields). These computations are highly demanding for energy-constrained mobile devices. The...
Main Authors: | Javier Acevedo, Robert Scheffel, Simon Wunderlich, Mattis Hasler, Sreekrishna Pandi, Juan Cabrera, Frank H. P. Fitzek, Gerhard Fettweis, Martin Reisslein |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-09-01
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Series: | Electronics |
Subjects: | |
Online Access: | http://www.mdpi.com/2079-9292/7/9/180 |
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