Decoding Method Based on Complex ICA for a Multicell Massive MIMO Uplink System

doi:10.1109/LSP.2016.2545105

Return

Decoding Method Based on Complex ICA for a Multicell Massive MIMO Uplink System

2016-05-01

PRE

DOI：10.1109/LSP.2016.2545105

Original

Original request for help

Save

Abstract

En 中文

Pilot signal reuse in neighboring cells causes the pilot contamination, and performance will be degraded significantly in a multicell, massive multiple-input, multiple-output (MIMO) uplink system. In this letter, a new decoding method is proposed to alleviate the degradation. In the proposed method, the principal component analysis (PCA) is used to reduce the dimension of the received signals from both intercell and intracell. Then, the complex independent component analysis (ICA) is implemented to estimate the channels, and the mean minimum square error (MMSE) decoder is employed to decode the transmitted signals. At last, few pilot signals are used to overcome the ambiguity caused by the complex ICA. In our method, orthogonality or asymptotic orthogonality of the channels is not required. Moreover, the path-loss and shadowing factors can be unknown. Simulation results show that the performance of our decoder is better than the MMSE channel estimation-based MMSE decoder. Moreover, error floor does not appear even when signal-to-noise ratio (SNR) is high, while it occurs if the MMSE decoder is used.

Keywords:

Independent component analysis (ICA)

multicell massive multiple-input

multiple-output (MIMO) system

pilot contamination

pilot signals

principal component analysis (PCA)

semi-blind decoding

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.