A full explanation of precoding technology

Table of contents

1. Linear precoding

1.1 Basic linear precoding

1.1.1 Maximum Ratio Transmission Algorithm (MRT)

1.1.2 ZF

1.1.3 MMSE

1.2 Approximate matrix inversion precoding

1.2.1 Truncated Polynomial Expansion Algorithm (TPE)

1.2.2 Approximate Newman Series Algorithm (NSA)

1.2.3 Newton iteration method (NI)

1.2.4 Chebyshev iteration method (CI)

1.3 Based on fixed point iterative algorithm

1.3.1 Gauss-Scheid algorithm (GS)

1.3.2 Successive over-relaxation method (SOR)

1.3.3 Conjugate gradient method (CG)

1.3.4 Jacobi iteration method (JI)

1.4 Precoding based on matrix decomposition

1.4.1 QR decomposition method

1.4.2 Cholesky Decomposition (CD)

2. Nonlinear precoding

2.1 Dirty Paper Code (DPC)

2.2 Tomlinson-Harashima Algorithm (TH)

2.3 Vector Perturbation Algorithm (VP)

2.4 Lattice Reduction Auxiliary Algorithm (LR)

3. Peak-to-average power ratio precoding (PAPR)

3.1 Constant Envelope Algorithm (CE)

3.2 Approximate Message Passing Algorithm (AMP)

3.3 Quantization Precoding (QP)

4. Machine Learning Precoding

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This article will be continuously supplemented and updated

1. Linear precoding

1.1 Basic linear precoding

1.1.1 Maximum Ratio Transmission Algorithm (MRT)

1.1.2 ZF

The essence of the zero-forcing algorithm (ZF) is channel inversion (pseudo-inversion). The zero-forcing algorithm makes the signal space of other users in the zero space by directing the signal beam to the target user, thereby reducing the interference caused by other users.

1.1.3 MMSE

1.2 Approximate matrix inversion precoding

1.2.1 Truncated Polynomial Expansion Algorithm (TPE)

1.2.2 Approximate Newman Series Algorithm (NSA)

1.2.3 Newton iteration method (NI)

1.2.4 Chebyshev iteration method (CI)

1.3 Based on fixed point iterative algorithm

1.3.1 Gauss-Scheid algorithm (GS)

1.3.2 Successive over-relaxation method (SOR)

1.3.3 Conjugate gradient method (CG)

1.3.4 Jacobi iteration method (JI)

1.4 Precoding based on matrix decomposition

1.4.1 QR decomposition method

1.4.2 Cholesky Decomposition (CD)

2. Nonlinear precoding

2.1 Dirty Paper Code (DPC)

2.2 Tomlinson-Harashima Algorithm (TH)

2.3 Vector Perturbation Algorithm (VP)

2.4 Lattice Reduction Auxiliary Algorithm (LR)

3. Peak-to-average power ratio precoding (PAPR)

3.1 Constant Envelope Algorithm (CE)

3.2 Approximate Message Passing Algorithm (AMP)

3.3 Quantization Precoding (QP)

4. Machine Learning Precoding

at last

This section supplements some of the terms that appear above (continuously updated.....)

Equal Gain Transmission: It can be combined with zero-forcing algorithm to design hybrid precoding.

DL:down link downlink

UL: up link uplink

IUI: inter-user interference Interference between users