Virtual Space-Time DiversityTurbo Equalization Using Cluster Sparse Proportional Recursive Least Squares Algorithm for Underwater Acoustic Communications

Abstract

The oceanic positioning, navigation and timing (PNT) network requires high-quality underwater acoustic message transmission. Turbo equalization technology has exhibited superior performance for underwater acoustic (UWA) communications compared with conventional channel equalizers. To overcome the performance reduction caused by severe doubly selective UWA channels, the virtual space-time diversity soft direct-adaptation turbo equalization is proposed for UWA communications. The proposed scheme improves the ability of the typical turbo equalizer to deal with both Doppler and multipath effects for time varying channels. We utilize a fractionally spaced soft interference cancellation equalizer (FS-SE) instead of a hard decision to constitute the soft-input soft-output (SISO) equalizer. Combined with another virtual time-reversal mirror equalizer component, we can obtain virtual space and time diversity with only a single receiving transducer and mitigate the error propagation phenomenon of the feedback filter. To satisfy the sparse UWA channel, the ℓp,q-PRLS algorithm is applied to adaptive updates for FS-SE. In the proposed scheme, an adjustable interpolator and digital phase-locked loop are embedded into the equalizer to overcome the residual Doppler frequency shift and recover the timing distortion. Results of simulations and field lake trial show that the proposed scheme achieves better performance than existing ones under the same equalizer order.

Advances and Trends in Channel Codes for Underwater Acoustic Communications

“…It can be seen from Figure 3 that the underwater acoustic channel multi-path structure exhibits pronounced time-varying characteristics and multi-paths with long delays, moreover, there are differences in the time-varying characteristics and degree of fading between each data frame [26]. In addition, as shown in Figure 4, the Doppler effect of the multi-path structure with different time delays is extremely time varying and unevenly distributed, which makes it challenging to obtain a unified and concise model for an accurate parameter description of the UWA channel [27]. With the increase in maritime activities in recent years, the kinematic state of the communication equipment carriers has become more complex and diverse, making it more challenging to reduce the Doppler effect, especially for multi-carrier UWAC.…”

“…structure with different time delays is extremely time varying and unevenly distributed, which makes it challenging to obtain a unified and concise model for an accurate parameter description of the UWA channel [27]. With the increase in maritime activities in recent years, the kinematic state of the communication equipment carriers has become more complex and diverse, making it more challenging to reduce the Doppler effect, especially for multi-carrier UWAC.…”

“…It consists of various noise sources superimposed on the integrated effect, including natural background noise, such as air bubbles, earthquakes, wind and waves, marine organisms, etc., and manufactured noise, such as underwater vehicles, the shorebased industry, etc. As described in the literature [5], SNR are calculated from signal attenuation and the noise power spectrum, as shown in Equation ( 6), where t P is the signal structure with different time delays is extremely time varying and unevenly distributed, which makes it challenging to obtain a unified and concise model for an accurate parameter description of the UWA channel [27]. With the increase in maritime activities in recent years, the kinematic state of the communication equipment carriers has become more complex and diverse, making it more challenging to reduce the Doppler effect, especially for multi-carrier UWAC.…”