Channel state information-based multi-dimensional parameter estimation for massive RF data in smart environments

Abstract Smart environment sensing and other applications play a more important role along with the rapid growth of device-free sensing-based services, extracting parameters contained in channel state information (CSI) accurately is basis these applications. However, antenna arrays wireless devices are all planar whose spacing does not meet spatial sampling theorem while existing parameter estimation methods almost based on array satisfying theorem. In this paper, we propose algorithm to estimate signal angle arrival (AoA), time flight (ToF), Doppler frequency shift (DFS) service array, which satisfy Firstly, mapped virtual linear manifold calculated. Secondly, applied multi-dimensional signal. Finally, by calculating geometric relationship between incident can be obtained. Therefore, only use communication for communication, but also sense surrounding provide related remote application services. Simulation results show that proposed when Compared TWPalo, AoA within 3 ∘ , error ToF DFS 1 ns m/s.