Abstract
Applying the orthogonal matching pursuit (OMP) to estimate the underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) channels is attractive because of its high estimation accuracy and low computational cost. However, most existing OMP-based algorithms suffer the limited estimation accuracy in impulsive noise (IN) cases. Through the studies can be found, only part of channels’ estimation is affected due to the random IN which appears transient and intermittent in time and frequency. Based on this observation, joint time-frequency OMP (JTF-OMP) method is proposed, where the estimation of the affected channels benefits adaptively from that of adjacent channels in time or frequency. It is well known that preliminary Doppler scale estimation is key to the subsequent OMP algorithm, which is difficult to deal with due to the IN. To solve this problem, an adaptive Doppler scale estimation (ADSE) method is proposed. It involves generating two shorter identical cyclic prefixes (CPs) for each OFDM symbol, placed before two adjacent OFDM symbols. The repetition pattern can adaptively defend the IN which appears randomly and shortly in time. Simulation results show that the proposed algorithms integrating JTF-OMP with ADSE can achieve much higher estimation accuracy and better system reliability than the OMP in the IN environment.
Highlights
The increasing marine service requirements urgently need to enhance the data rate of underwater acoustic (UWA) communication [1, 2]
Joint time-frequency orthogonal matching pursuit (OMP) (JTF-OMP) method is proposed in this paper; the pilot subcarriers are divided into groups at the same interval and estimated separately
The results show that the joint time-frequency OMP (JTF-OMP) and the adaptive Doppler scale estimation (ADSE) can be
Summary
The increasing marine service requirements urgently need to enhance the data rate of underwater acoustic (UWA) communication [1, 2]. A recursive CS algorithm incorporating Kalman filter and Smoother (KFS) is developed in [21], which adopts the sparse Bayesian learning (SBL) to construct the CS framework These methods either require extra bandwidth for null subcarriers or use the statistical feature of the IN as the basis for instantaneous estimation. On the premise of maintaining the same spectral and energy efficiency as traditional single CP structure, two shorter CPs with reasonable distance can ensure the self-correlation of the received signal in the IN cases, which is key to the Doppler scale estimation (iii) The proposed algorithms do not require null subcarriers for channel estimation; channel resource is saved. AT , AH, and A−1 denote the transpose, conjugate transpose, and inverse of A, respectively
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