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A New Algorithm of Iterative MIMO Detection and Decoding Using Linear Detector and Enhanced Turbo Procedure in Iterative Loop

Authors: Bakulin Mikhail; Kreyndelin Vitaly; Rog Andrey; Petrov Dmitry; Melnik Sergei;

A New Algorithm of Iterative MIMO Detection and Decoding Using Linear Detector and Enhanced Turbo Procedure in Iterative Loop

Abstract

In the paper we develop and evaluate a novel low complexity algorithm of iterative detection and decoding in multiple input multiple output (MIMO) system. It is based on a new enhanced Turbo procedure. Although the algorithm utilizes well-known components such as linear minimum mean square error (MMSE) detector and channel decoder with soft bits feedback, the new original procedure of getting extrinsic data essentially allows improving the receiver performance and reducing its complexity. Moreover, it is shown that proposed Turbo approach works even without channel decoder in the iteration loop. Thus, we ob-tain pure iterative MMSE detector with improved performance. Utilization of combined scheme with MMSE detector and channel decoder feedback demonstrates really outstanding performance. It is confirmed with simulations that the performance of proposed architecture exceeds traditional ML MIMO detector schemes that are designed with channel decoder but without iterative loop.

Keywords

Combined schemes, Linear detectors, Signal receivers, 621, Mean square error, Receiver performance, Channel coding, Low complexity algorithm, Iterative decoding, MIMO systems, 620, Computational complexity, Proposed architectures, Linear minimum mean square errors, Channel decoder, Iterative detection and decoding

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Top 10%
Top 10%
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