Constructing Knowledge Map for MIMO-OFDM Clustered Channel Estimation

TL;DR

This paper introduces ClusterCKM, a knowledge map that leverages environmental information to improve channel estimation accuracy and reduce pilot overhead in clustered MIMO-OFDM channels.

Contribution

The paper proposes ClusterCKM, a novel environment-aware knowledge map specifically designed for clustered channels, enhancing estimation accuracy and efficiency.

Findings

ClusterCKM accurately estimates multipath parameters.

Using ClusterCKM reduces pilot overhead.

Channel estimation accuracy improves with ClusterCKM.

Abstract

Channel knowledge map (CKM) exploits environ-ment information to assist channel estimation during communi-cation. For clustered channels, which represent a typical type ofwireless propagation environment, there has been no researchdevoted to designing an appropriate CKM to enhance theirestimation. To exploit environment information for clusteredchannel, improve channel estimation accuracy and reduce pilotoverhead, we propose ClusterCKM, a CKM providing the rangeof clustered multipath parameters for any pair of transmitter-receiver links in the region of interest. Firstly, we construct Clus-terCKM through estimating the spatial range of scatterer clustersfrom historical channel information. From these spatial range ofscatterer clusters, ClusterCKM infers the range of multipathparameters for the target link. Furthermore, a ClusterCKM-based channel estimation algorithm is developed to utilize theparameter range provided by ClusterCKM. Simulation resultsshow that, more accurate channel estimation can be achievedand pilot overhead can also be reduced by ClusterCKM and theClusterCKM-based estimation algorithm.