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Improved Decoding of Analog Modulo Block Codes for Noise Mitigation

Citation Author(s):
Tim Schmitz, Peter Jax, Peter Vary
Submitted by:
Tim Schmitz
Last updated:
16 June 2016 - 3:14am
Document Type:
Poster
Document Year:
2016
Event:
Presenters:
Tim Schmitz

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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