Abstract
In this paper, a novel normalized least mean squares (NLMS) algorithm that jointly updates the efficient of the linear equalizer and soft interference canceller (SIC) in an adaptive turbo equalizer for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. To exploit the sparsity of MIMO UWA channels and enhance the convergence speed of adaptive equalization, improved proportionate fast self-optimized NLMS algorithm (IPFONLMS), is proposed to well adapt to sparse channel with the similar complexity as improve proportionate NLMS (IPNLMS) algorithm. Then we extend the proposed algorithm to the adaptive turbo equalization for MIMO UWA communications. The performance of the proposed adaptive algorithm is evaluated by numerical results. Simulation results show that the improved data efficiency and bit error ratio (BER) performance of the proposed receiver is achieved over adaptive turbo equalizer based on the IPNLMS algorithm.
Highlights
In recent years, due to the competition for marine resources, every country has strengthened the research on underwater acoustic (UWA) communications
UWA communications using multiple-input multiple-output (MIMO) technique shown effective in exploiting the time and spatial diversity characteristics of UWA channel
In order to solve the above issues, in this paper, we present a new adaptive algorithm IPFONLMS to update the coefficients of turbo equalization (TEQ) for MIMO UWA communications
Summary
Due to the competition for marine resources, every country has strengthened the research on UWA communications. UWA communications using MIMO technique shown effective in exploiting the time and spatial diversity characteristics of UWA channel. The turbo equalization (TEQ) techniques for UWA communication is commonly used in large applications[2,3]. The PNLMS algorithm converges much slower than NLMS algorithm when the impulse response is dispersive To resolve this problem, a new and simple rule was derived in [7]. The existing algorithms do not strike a balance between utilize the sparsity of UWA channels and adaptive varying step-size. In order to solve the above issues, in this paper, we present a new adaptive algorithm IPFONLMS to update the coefficients of TEQ for MIMO UWA communications. The superscripts ( )∗ , ( )T and ( )H represent, respectively, the conjugate, the matrix transpose, and the matrix Hermitian
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