# Security Vulnerability of FDD Massive MIMO Systems in Downlink Training Phase

## TL;DR

This paper analyzes how a multi-antenna jammer can significantly disrupt downlink channel training in FDD massive MIMO systems by exploiting channel statistics, leading to increased estimation errors even with optimal training.

## Contribution

It introduces a novel jamming attack based on second-order channel statistics and derives conditions for maximizing the mean square error in downlink training.

## Key findings

- Jamming can substantially increase channel estimation MSE.
- Optimal training signals are vulnerable to targeted jamming.
- The attack remains effective even with many pilot symbols.

## Abstract

We consider downlink channel training of a frequency division duplex (FDD) massive multiple-input-multiple-output (MIMO) system when a multi-antenna jammer is present in the network. The jammer intends to degrade mean square error (MSE) of the downlink channel training by designing an attack based on second-order statistics of its channel. The channels are assumed to be spatially correlated. First, a closed-form expression for the channel estimation MSE is derived and then the jammer determines the conditions under which the MSE is maximized. Numerical results demonstrate that the proposed jamming can severely increase the estimation MSE even if the optimal training signals with a large number of pilot symbols are used by the legitimate system.