Abstract
Self-interference (SI) is usually generated by the simultaneous transmission and reception in the same system, and the variable SI channel and impulsive noise make it difficult to eliminate. Therefore, this paper proposes an adaptive digital SI cancellation algorithm, which is an improved normalized sub-band adaptive filtering (NSAF) algorithm based on the sparsity of the SI channel and the arctangent cost function. The weight vector is hardly updated when the impulsive noise occurs, and the iteration error resulting from impulsive noise is significantly reduced. Another major factor affecting the performance of SI cancellation is the variable SI channel. To solve this problem, the sparsity of the SI channel is estimated with the estimation of the weight vector at each iteration, and it is used to adjust the weight vector. Then, the convergence performance and calculation complexity are analyzed theoretically. Simulation results indicate that the proposed algorithm has better performance than the referenced algorithms.
Highlights
The integrated system of underwater detection and communication (ISUDC) [1] and in-band full-duplex (IBFD) underwater acoustic communication (UWC) [2] face the problem of SI, which is caused by the near-end transmission [3]
An improved improved PNSAF (IPNSAF) algorithm based on the sparsity of the SI channel and the arctangent function has been proposed for the impulsive noise with the variable SI channel, and its application has been considered in ISUDC
An improved IPNSAF algorithm is proposed for the SI channel with varying sparsity in impulsive noise, and it is called the Sc-Arc-IPNSAF algorithm
Summary
The integrated system of underwater detection and communication (ISUDC) [1] and in-band full-duplex (IBFD) underwater acoustic communication (UWC) [2] face the problem of SI, which is caused by the near-end transmission [3]. There is some non-Gaussian impulsive noise in the practical application environment [8], and the performance of the traditional adaptive filtering algorithms deteriorates severely with the non-Gaussian impulsive noise [9]. The sub-band adaptive filter (SAF) and the normalized SAF (NSAF) [15] algorithms have been proposed to address this problem. The input signal is decomposed into sub-band signals and processed by the adaptive filter, respectively. The general zero attraction proportionate normalized maximum correntropy criterion algorithm was proposed in [20], and it has a superior performance for a sparse system in a non-Gaussian noise environment. An improved IPNSAF algorithm based on the sparsity of the SI channel and the arctangent function has been proposed for the impulsive noise with the variable SI channel, and its application has been considered in ISUDC. Where μ is the step-size, · indicates the norm of a vector, and the term δ is the regularization parameter
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