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Register a new userOFDM demodulation using virtual time reversal processing in underwater acoustic communication
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Yue Yang Dr
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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The extremely long underwater channel delay spread causes severe inter-symbol interference (ISI) for underwater acoustic communications. Passive time reversal processing (PTRP) can effectively reduce the channel time dispersion in a simple way via convolving the received packet with a time reversed probe signal. However the probe signal itself may introduce extra noise and interference (self-correlation of the probe signal). In this paper, we propose a virtual time reversal processing (VTRP) for single input single output (SISO) Orthogonal Frequency Division Multiplexing (OFDM) systems. It convolves the received packet with the reversed estimated channel, instead of the probe signal to reduce the interference. Two sparse channel estimation methods, matching pursuit (MP), and basis pursuit de-noising (BPDN), are adopted to estimate the channel impulse response (CIR). We compare the performance of VTRP with the PTRP and without any time reversal processing through MATLAB simulations and the pool experiments. The results reveal that VTRP has outstanding performance over time-invariant channels.
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Differential orthogonal frequency division multiplexing (OFDM) is practically attractive for underwater acoustic communications since it has the potential to obviate channel estimation. However, similar to coherent OFDM, it may suffer from severe inter-carrier interference over time-varying channels. To alleviate the induced performance degradation, we adopt the newly-emerging partial FFT demodulation technique in this paper and propose an eigendecomposition-based algorithm to compute the combining weights. Compared to existing adaptive methods, the new algorithm can avoid error propagation and eliminate the need for parameter tuning. Moreover, it guarantees global optimality under the narrowband Doppler assumption, with the optimal weight vector of partial FFT demodulation achieved by the eigenvector associated with the smallest eigenvalue of the pilot detection error matrix. Finally, the algorithm can also be extended straightforwardly to perform subband-wise computation to counteract wideband Doppler effects.
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