BayesAoA: A Bayesian method for Computation Efficient Angle of Arrival Estimation
This addresses the need for efficient and robust AoA estimation in communication systems, though it appears incremental as it builds on existing Bayesian and optimization approaches.
The paper tackles the problem of Angle of Arrival (AoA) estimation in communication systems by proposing a Bayesian method that is insensitive to initialization and computationally efficient, achieving 92% accuracy with 19.3% of the brute-force method's computation.
The angle of Arrival (AoA) estimation is of great interest in modern communication systems. Traditional maximum likelihood-based iterative algorithms are sensitive to initialization and cannot be used online. We propose a Bayesian method to find AoA that is insensitive towards initialization. The proposed method is less complex and needs fewer computing resources than traditional deep learning-based methods. It has a faster convergence than the brute-force methods. Further, a Hedge type solution is proposed that helps to deploy the method online to handle the situations where the channel noise and antenna configuration in the receiver change over time. The proposed method achieves $92\%$ accuracy in a channel of noise variance $10^{-6}$ with $19.3\%$ of the brute-force method's computation.