SNR estimation algorithm based on the preamble for OFDM systems in frequency selective channels

• Published in: IEEE transactions on communications Vol. 57; no. 8; pp. 2230 - 2234
• Main Authors: Ren, Guangliang, Zhang, Huining, Chang, Yilin
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Additive white noise; Algorithms; Applied sciences; AWGN; Channels; Computer simulation; Estimates; Exact sciences and technology; Frequency division multiplexing; Frequency domain analysis; Frequency domains; Frequency estimation; frequency selective channel; Gaussian noise; Information, signal and communications theory; Maximum likelihood estimation; Multiplexing; Noise; Noise robustness; OFDM; Orthogonal Frequency Division Multiplexing; Orthogonal frequency division multiplexing (OFDM); preamble; Signal and communications theory; Signal to noise ratio; SNR estimation; Symbols; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Training; Transmission and modulation (techniques and equipments); Fading channels; Performance evaluation; Second order; preamble; Wireless telecommunication; Frequency domain method; Algorithm; Orthogonal frequency division multiplexing (OFDM); Learning; Frequency selection; Simulation; Telecommunication channels; Orthogonal frequency division multiplexing; frequency selective channel; SNR estimation; Signal to noise ratio
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2008.08.060406

We propose a new SNR estimation method based on the preamble for OFDM systems in frequency selective channels. The OFDM training symbols in the preamble are equalized by the known data in frequency domain and employed to estimate the noise variance. The second order moments of the received symbols are used to estimate the signal plus noise power in the OFDM packets. The SNRs on the subchannels and the average SNR of the packets can all be estimated. Simulation results show that the proposed method is robust to frequency selectivity in wireless channels, and its performance is considerably improved compared with the available methods.