Toward Fine-Grained Indoor Localization Based on Massive MIMO-OFDM System: Experiment and Analysis

Abstract

Fine-grained indoor localization has attracted attention recently because of the rapidly growing demand for indoor location-based services (ILBS). Specifically, massive (largescale) multiple-input and multiple-output (MIMO) systems have received increasing attention due to high angular resolution. This paper presents an indoor localization testbed based on a massive MIMO orthogonal frequency-division multiplexing (OFDM) system, which supports physical-layer channel measurements. Instead of exploiting channel state information (CSI) directly for localization, we focus on positioning from the perspective of multipath components (MPCs), which are extracted from the CSI through the space-alternating generalized expectationmaximization (SAGE) algorithm. On top of the available MPCs, we propose a generalized fingerprinting system based on different single-metric and hybrid-metric schemes. We evaluate the impact of varying antenna topologies, feeding metrics, sizes of the training set, and fingerprinting methods. The experimental results show that the proposed fingerprinting method can achieve centimeter-level positioning accuracy with a relatively small training set. Specifically, the distributed uniform linear array obtains the highest accuracy with about 1.63-2.5-cm mean absolute errors resulting from the high spatial resolution.

Pairwise Node Localization From Differences in Their UWB Channels to Observer Nodes

“…We believe that the mathematical structure in (12) to ( 14) is fundamentally responsible for successes in wideband MIMO location fingerprinting, e.g. reported in [43], [44]. In this paper we will utilize these properties systematically to formulate estimators.…”

“…The proposal has the potential to supplement or replace machine-learning-based technology for wireless location fingerprinting as presented in [18], [43], [44].…”

Machine Learning-Based Fingerprint Positioning for Massive MIMO Systems

“…In [23], the authors proposed an amplitude-plus-AoA constructed fingerprint of the massive MIMO system for indoor localization. In [24], the authors presented a massive MIMO-OFDM fingerprinting system based on the extracted multi-path components of direct links for indoor localization. However, the fingerprints above are too rough to characterize the complex multi-path information for outdoor urban positioning fully.…”

Secure Transmission Strategy of Power Communication Based on Sensor-to-Computation Linkage

“…In recent years, many scholars have studied the impact of antenna correlation on physical layer security technology in wireless communications. In Reference [2], the author modeled the channel gain between the multiple antennas at the base station as a spatially arbitrary correlated Rayleigh random variable, and studied the relationship between the security performance of the system and the correlation coefficient when the base station transmits signals using Maximum Ratio Transmission (MRT) technology. The pros and cons of the correlation pair system are related to the SNR of the main channel.…”