Fast Iterative Adaptive Approach for Indoor Localization With Distributed 5G Small Cells

This letter addresses Time-Of-Arrival estimation for an indoor positioning system (IPS) made up of distributed 5G small cells by focusing on the Iterative Adaptive Approach (IAA) with Orthogonal Frequency Division Multiplexing (OFDM) signals. While IAA has been successfully applied to many other areas, its application to 5G IPS is not straightforward. In fact, even the current fast implementation of IAA is hardly compatible with 5G chips having limited computational capability, due to large number of sub-carriers of OFDM signals. To address this problem, we pursue the idea of averaging over a number of successive sub-carriers sequentially. Since our analysis shows that the direct Sub-carrier Average (SA) operation exhibits the asinc modulation effect on channel response, possibly leading to miss-detection of Direct Path (DP), we further propose a channel compensation-based SA method and provide a quantitative analysis of the signal-to-noise ratio of the DP to demonstrate its robustness. The resulting SA-based fast IAA (SA-FIAA) algorithm can achieve comparable performance as the standard IAA, while reducing computational cost by over 2 − 3 orders of magnitude, making it practically tractable in 5G IPSs. The effectiveness and computational efficiency of the proposed approach are well demonstrated through real-world experiments.