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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

4. Nonlinear Massive MIMO Signal Detection Algorithm

verfasst von : Leibo Liu, Guiqiang Peng, Shaojun Wei

Erschienen in: Massive MIMO Detection Algorithm and VLSI Architecture

Verlag: Springer Singapore

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Abstract

This chapter first introduces several conventional nonlinear MIMO signal detection algorithms in Sect. 4.1. The optimal nonlinear ML signal detection algorithm is introduced first, and then the SD signal detection algorithm and the K-Best signal detection algorithm evolved from the nonlinear ML signal detection algorithm are introduced. Section 4.2 presents a K-best signal detection and preprocessing algorithm in high-order MIMO systems, combining the Cholesky sorted QR decomposition and partial iterative lattice reduction (CHOSLAR). At the same time, the algorithm uses the partial iterative lattice reduction (PILR) algorithm to acquire more asymptotically orthogonal matrix R. After the preprocessing, the K-Best signal detector combined with ordering reduction and branch expansion can achieve the detection accuracy similar to that of ML signal detection algorithm. Section 4.3 presents another new signal detection algorithm, TASER algorithm. Based on semi-definite relaxation, the TASER algorithm can achieve the signal detection performance of approximate ML within the computational complexity of the polynomial (with the number of transmitting antennas or time slots as independent variables) in the system with low bit rate and fixed modulation scheme.

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Vorheriges Kapitel Architecture of Linear Massive MIMO Detection
Nächstes Kapitel Architecture for Nonlinear Massive MIMO Detection
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Metadaten
Titel
Nonlinear Massive MIMO Signal Detection Algorithm
verfasst von
Leibo Liu
Guiqiang Peng
Shaojun Wei
Copyright-Jahr
2019
Verlag
Springer Singapore
Buch
Massive MIMO Detection Algorithm and VLSI Architecture

Print ISBN: 978-981-13-6361-0

Electronic ISBN: 978-981-13-6362-7

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-981-13-6362-7_4

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