Full MIMO Channel Estimation Using A Simple Adaptive Partial Feedback Method

TL;DR

This paper introduces an adaptive partial feedback method for MIMO channel estimation that uses a simple least squares algorithm and time-varying step-size feedback to improve channel state information accuracy with reduced complexity.

Contribution

It proposes a novel adaptive partial feedback scheme employing a least squares algorithm and variable step-size feedback, independent of space-time coding, to enhance MIMO channel estimation.

Findings

Improved channel estimation accuracy demonstrated through simulations

Reduced computational complexity compared to traditional methods

Effective in severely limited feedback scenarios

Abstract

Partial feedback in multiple-input multiple-output (MIMO) communication systems provides tremendous capacity gain and enables the transmitter to exploit channel condition and to eliminate channel interference. In the case of severely limited feedback, constructing a quantized partial feedback is an important issue. To reduce the computational complexity of the feedback system, in this paper we introduce an adaptive partial method in which at the transmitter, an easy to implement least square adaptive algorithm is engaged to compute the channel state information. In this scheme at the receiver, the time varying step-size is replied to the transmitter via a reliable feedback channel. The transmitter iteratively employs this feedback information to estimate the channel weights. This method is independent of the employed space-time coding schemes and gives all channel components. Simulation examples are given to evaluate the performance of the proposed method.