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CAIM: Cooperative Angle of Arrival Estimation using the Ising Model

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