A New Adaptive Channel Estimation for Frequency Selective Time Varying Fading OFDM Channels

TL;DR

This paper introduces an adaptive channel estimation algorithm for OFDM systems that dynamically selects training patterns based on channel stationarity and error rates, improving data throughput.

Contribution

It presents a novel adaptive algorithm that enhances OFDM channel estimation by using a logic controller to optimize training pattern selection, increasing data rate without sacrificing error performance.

Findings

Improved data rate in OFDM systems with adaptive estimation.

Maintained error probability comparable to traditional methods.

Effective in frequency selective, time-varying fading channels.

Abstract

In this paper a new algorithm for adaptive dynamic channel estimation for frequency selective time varying fading OFDM channels is proposed. The new algorithm adopts a new strategy that successfully increases OFDM symbol rate. Instead of using a fixed training pilot sequence, the proposed algorithm uses a logic controller to choose among several available training patterns. The controller choice is based on the cross-correlation between pilot symbols over two consecutive time instants (which is considered to be a suitable measure of channel stationarity) as well as the deviation from the desired BER. Simulation results of the system performance confirm the effectiveness of this new channel estimation technique over traditional non-adaptive estimation methods in increasing the data rate of OFDM symbols while maintaining the same probability of error.