# Clustering-Based Codebook Design for MIMO Communication System

## TL;DR

This paper introduces a K-means clustering-based codebook design for MIMO systems that improves performance in non-uniform channel conditions by utilizing clustering of channel state information.

## Contribution

It proposes a novel codebook design method using K-means clustering, addressing limitations of traditional uniform distribution assumptions.

## Key findings

- Outperforms conventional codebook schemes in simulations
- Achieves higher achievable rates in non-uniform channel scenarios
- Effectively utilizes clustering to represent channel statistics

## Abstract

Codebook design is one of the core technologies in limited feedback multi-input multi-output (MIMO) communication systems. However, the conventional codebook designs usually assume MIMO vectors are uniformly distributed or isotropic. Motivated by the excellent classfication and analysis ability of clustering algorithms, we propose a K-means clustering based codebook design. First, large amounts of channel state information (CSI) is stored as the input data of the clustering, and finally divided into N clusters according to the minimal distance. The clustering centroids are used as the statistic channel information of the codebook construction which the sum distance is minimal to the real channel information. Simulation results consist with theoretical analysis in terms of the achievable rate, and demonstrate that the proposed codebook design outperforms conventional schemes, especially in the non-uniform distribution of channel scenarios.