Are D2D and RIS in the same league? Cooperative RSSI-based localization model and performance comparison

Abstract

The next generation of high-accuracy positioning services is required to satisfy the sub-meter accuracy level for more than 95% of the network area, including indoor, outdoor, and urban deployments. In this vein, inter-agent measurements appear to provide additional position information and, hence, have the capacity to boost localization accuracy. This paper researches cooperative positioning techniques by means of device-to-device (D2D) and reconfigurable intelligent surfaces (RIS) technologies leveraging received signal strength (RSS) based ranging. We estimate the maximum capacities of the positioning systems in terms of accuracy through the Gaussian noise model, proposed universal theoretical distance-dependent noise model, and empirical noise model. We also evaluate the positioning error achieved by combining two or more technologies. Numerical results reveal the use cases advantageous for RIS- and D2D-aided localization. Then, based on the results, valuable guidelines are derived on the optimal sensor fusion metric – median – that minimizes the mean error of the cooperative localization.