Channel Estimation in Massive MIMO Systems
arXiv:1503.08691
Abstract
We introduce novel blind and semi-blind channel estimation methods for cellular time-division duplexing systems with a large number of antennas at each base station. The methods are based on the maximum a-posteriori principle given a prior for the distribution of the channel vectors and the received signals from the uplink training and data phases. Contrary to the state-of-the-art massive MIMO channel estimators which either perform linear estimation based on the pilot symbols or rely on a blind principle, the proposed semi-blind method efficiently suppresses most of the interference caused by pilot-contamination. The simulative analysis illustrates that the semi-blind estimator outperforms state- of-the-art linear and non-linear approaches to the massive MIMO channel estimation problem.
References in corpus (8)
- A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems
- Distributed Compressive CSIT Estimation and Feedback for FDD Multi-user Massive MIMO Systems
- Blind pilot decontamination
- Downlink Training Techniques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training with Memory
- Efficient Coordinated Recovery of Sparse Channels in Massive MIMO
- Dealing with Interference in Distributed Large-scale MIMO Systems: A Statistical Approach
- Optimal Channel Training in Uplink Network MIMO Systems
- Hierarchical Interference Mitigation for Massive MIMO Cellular Networks
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- Pilot Power Allocation Through User Grouping in Multi-Cell Massive MIMO Systems
- Blind Estimation of Sparse Broadband Massive MIMO Channels with Ideal and One-bit ADCs
- Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO with One-Dimensional Antenna Array
- Asymptotic Rate Analysis for Impairments-Aware Multi-Carrier FD Massive MIMO Relay Networks utilizing MRT/MRC Strategy