CAIM: Cooperative Angle of Arrival Estimation using the Ising Method

TL;DR

This paper introduces CAIM, a cooperative AoA estimation method leveraging compressive sensing and Ising energy formulation, achieving improved accuracy through MCMC optimization with multiple access points.

Contribution

It presents a novel cooperative AoA estimation approach using the Ising method and MCMC, enhancing accuracy over existing techniques.

Findings

Outperforms existing AoA estimation methods in simulations

Utilizes compressive sensing for sparse signal processing

Reformulates AoA estimation as an Ising energy problem

Abstract

This paper proposes a cooperative angle-of-arrival(AoA) estimation, taking advantage of co-processing channel state information (CSI) from a group of access points that receive signals of the same source. Since received signals are sparse, we use Compressive Sensing (CS) to address the AoA estimation problem. We formulate this problem as a penalized l0-norm minimization, reformulate it as an Ising energy problem, and solve it using Markov Chain Monte Carlo (MCMC). Simulation results show that our proposed method outperforms the existing methods in the literature.