JOURNAL ARTICLE

A Simple Subspace-Based Semi-Blind Channel Estimator for Precoded OFDM Systems

Abstract

In this paper, a simple subspace based semi-blind channel estimator is developed for precoded OFDM systems. This channel estimator relies on redundant linear preceding. With this proposed channel estimator, the channel identifiability is guaranteed up to one scalar ambiguity, regardless of the channel zero locations and the underlying signal constellations. The ambiguity can be resolved with the known pilots inserted in the transmitted sequences. Computer simulations are conducted to support our analysis. The simulation results show that, compared with the well known LS estimator, the proposed estimator achieves higher estimation accuracy and is capable of tracking slow channel variations.

Keywords:
Estimator Identifiability Channel (broadcasting) Precoding Subspace topology Orthogonal frequency-division multiplexing Algorithm Computer science Ambiguity Signal subspace Mathematics Statistics Telecommunications Artificial intelligence MIMO Noise (video) Machine learning

Metrics

4
Cited By
0.00
FWCI (Field Weighted Citation Impact)
15
Refs
0.16
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Advanced Wireless Communication Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing
Wireless Communication Networks Research
Physical Sciences →  Computer Science →  Computer Networks and Communications

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