Preamble-based SNR Estimation in Frequency Selective Channels for Wireless OFDM Systems

The two main categories of SNR estimators is the data-aided (DA) estimator and the in-service estimator where the data aided estimator are based on estimated knowledge of transmitted data, but a some portion of data is been needed for estimation process which has the tendency to reduce the bandwidth efficiency.

The in – service estimator or the blind estimator derives SNR from a unknown bearing portion of the signal been received preserving efficiency at cost of decreased performance.In packet based data transfer or communicationthe block of information is preceded in several training symbols of the data known used equalization process and synchronization.

So that the data – aided SNR estimation can be utilized without additional throughput reduction. In the background the OFDM is multi carrier modulation that can provide strong robustness against ISI, i.e. inter symbol interface by dividing broad band signal to number of narrowband sub – channels where the attention towards each sub channels stays as flat. The Orthogonalizationof the sub channel is done with less complexity using fast Fourier transform (FFT). Serial high-rate data stream are been converted into multiple parallel low-rate streams, where each modulated are on a different subcarrier.

This paper proposes an efficient algorithm for SNR estimation in wireless OFDM. The SNR sub carrier can be additional estimation by use of channel estimation and the estimated average SNR. The proposed estimator in this paper makes use of preamble structure which allows synchronization over a wide frequency offset range, which helps in reducing the training symbol overhead.  Hear the proposed estimator algorithm depends on the signal samples at the output of fast Fourier transform, where the performance depends on the given preamble structure.

The performance of the algorithm is been compared with the MMSE algorithm and other two preamble-based algorithms and it is proved that the algorithm which has been discussed in this paper is robust against the frequency selectivity and can be used for sub channel SNR.

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