Publications – Details
Improved Decoding of Analog Modulo Block Codes for Noise Mitigation
- Authors:
- Tim Schmitz, Peter Jax, and Peter Vary
- Book Title:
- Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
- Venue:
- Shanghai, China
- Event Date:
- 20.-25.3.2016
- Organization:
- IEEE
- Date:
- Mar. 2016
- Pages:
- 3861–3865
- URL:
- 10.1109/ICASSP.2016.7472400
- Language:
- English
Abstract
A drawback of digital transmission of analog signals is the unavoidable quantization error which leads to a limited quality even for good channel conditions.
This saturation can be avoided by using analog transmission systems with discrete-time and quasi-continuous-amplitude encoding and decoding, e.g., Analog Modulo Block codes (AMB codes). The AMB code vectors are produced by multiplying a real-valued information vector with a real-valued generator matrix using a modulo arithmetic.
Here, algorithms for improving the decoding performance are presented. The Lattice Maximum Likelihood (LML) decoder, a variant of the Discrete Maximum Likelihood (DML) decoder, is derived and analyzed. It refines the Zero Forcing (ZF) result if necessary, thus achieving near-ML signal quality with a reduced decoding complexity. A reduced complexity is essential for decoding high-dimensional code words. Additionally, pre- and post-processing methods are presented and analyzed, which increase the signal-to-distortion ratio (SDR) of the received symbols.
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