Abstract
Orthogonal frequency division multiplexing (OFDM) is a promising technique in the current broadband wireless communication system due to the high data rate transmission capability and the ability to combat frequency selective fading of the channel. Channel estimation is mainly implemented by sending pilot symbols in the transmitted bit streams. In this paper, channel estimation based on block type pilot arrangements is analyzed using Least Square (LS) and Minimum Mean Square Error (MMSE) channel estimators. Performance is analyzed in terms of Bit Error Rate and Mean Square Error by varying pilot energy levels and by varying channel length. It is gathered that performance gets affected considerably with change in pilot energy levels implying there exist an optimum value for pilot energy for getting better performance.
Highlights
The information data in binary form are first grouped and mapped into mutiamplitude multi-phase signals according to the type of modulation used in the signal modulator
The channel estimation has been performed by inserting pilot tones into each Orthogonal frequency division multiplexing (OFDM) symbol
The estimation can be based on least square (LS) and minimum mean square error (MMSE) estimators
Summary
In figure 1, the information data in binary form are first grouped and mapped into mutiamplitude multi-phase signals according to the type of modulation used in the signal modulator. After inserting pilots uniformly between the information data sequence, IFFT block is used to transform and multiplex the complex data sequence into time domain signal. The transmitted signal is sent to a frequency selective multi-path time varying slow fading channel. The guard insertion is removed first and the received samples are sent to the FFT block for de-multiplexing the multi-carrier signal. Following FFT block, the pilot signals are extracted from the demultiplexed samples. The transmitted data samples can be recovered from the knowledge of the channel responses by dividing the received signal by the channel response. 3⁄4 MMSE The MMSE estimator employs the second order statistics of the channel conditions to minimize the MSE. Assume the channel vector and the noise are uncorrelated, it is derived that:
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