Eigendecomposition-Based Partial FFT Demodulation for Differential OFDM in Underwater Acoustic Communications

TL;DR

This paper introduces an eigendecomposition-based partial FFT demodulation method for differential OFDM in underwater acoustic communications, effectively mitigating inter-carrier interference caused by time-varying channels without error propagation or parameter tuning.

Contribution

It proposes a novel eigendecomposition algorithm for partial FFT demodulation that guarantees global optimality and can be extended to handle wideband Doppler effects.

Findings

Avoids error propagation in demodulation

Eliminates need for parameter tuning

Achieves optimal weights via eigenvector analysis

Abstract

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.