Hybrid channel estimation scheme for IEEE 802.11n-based STBC MIMO system

Author

Gogoi, Papori ; Sarma, Kandarpa Kumar

Author_Institution

Dept. of Electron. & Commun. Technol., Gauhati Univ., Guwahati, India

fYear

2012

fDate

28-29 Dec. 2012

Firstpage

49

Lastpage

52

Abstract

In this paper, we have proposed a Kalman Filter (KF) - Recurrent Neural Network (RNN) based channel estimator block for Multiple-Input Multiple-Output (MIMO) multipath fading channels based on the IEEE 802.11n channel models for indoor wireless local area networks (WLAN). Two transmit antennas and two receive antennas are used here. The estimator block has been simulated in STBC coded MIMO multipath fading channel scenario with and without CSI, and figure of merit in terms of Bit Error Rate (BER) has been obtained. The design criteria and performance curve shown in the paper clearly proves the effectiveness of the proposed hybrid estimator, both in terms of performance and hardware realizability.

Keywords

Kalman filters; MIMO communication; channel estimation; error statistics; fading channels; multipath channels; receiving antennas; recurrent neural nets; space-time block codes; transmitting antennas; wireless LAN; IEEE 802.11n; Kalman filter; MIMO multipath fading channels; STBC MIMO system; WLAN; bit error rate; channel estimator block; channel state information; hybrid channel estimation scheme; indoor wireless local area networks; multiple-input multiple-output multipath fading channels; recurrent neural network; space time block code; two receive antennas; two transmit antennas; Artificial neural networks; Channel estimation; Channel models; Fading; IEEE 802.11n Standard; MIMO; Training; ANN; Estimation; IEEE 802.11n; MIMO;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Devices and Intelligent Systems (CODIS), 2012 International Conference on

Conference_Location

Kolkata

Print_ISBN

978-1-4673-4699-3

Type

conf

DOI

10.1109/CODIS.2012.6422133

Filename

6422133