A low-complexity error-feedback lattice-equalizer with phase tracking for underwater acoustic communications.

Area of Science:

• Signal Processing
• Underwater Communications
• Adaptive Filtering

Background:

• Recursive least squares (RLS) equalizers in underwater acoustic (UWA) communications suffer from high computational complexity.
• Existing adaptive equalizers face challenges in handling time-varying UWA channels, impacting performance.

Purpose of the Study:

• To propose a novel adaptive equalizer, the error-feedback lattice-equalizer (EFLE), for UWA communication systems.
• To reduce the complexity of RLS-based equalizers while maintaining or improving performance.
• To enhance equalization performance in time-varying UWA channels through phase tracking.

Main Methods:

• Derivation of a recursive least squares algorithm for the EFLE utilizing a lattice structure with time and order updates.
• Implementation of an error-feedback mechanism for numerical stability in reflection coefficient computation.
• Integration of a phase tracking method to address rapid tap rotation in time-varying channels.

Main Results:

• The EFLE achieves complexity linearly related to its length, a significant reduction compared to RLS.
• Simulations and at-sea experiments demonstrate superior bit error rate (BER) performance of EFLE.
• EFLE outperforms linear complexity equalizers (LMS variants) and quadratic complexity RLS equalizers.

Conclusions:

• The proposed EFLE offers a computationally efficient and high-performance solution for UWA communication equalization.
• The phase tracking mechanism in EFLE is crucial for effective equalization in dynamic UWA environments.
• EFLE represents a significant advancement in adaptive equalization for challenging underwater acoustic channels.