On the Achievable Error Rate Performance of Pilot-Aided Simultaneous Communication and Localization With a Ground-to-Air Model

This paper investigates the symbol error rate (SER) performance of the pilot-aided simultaneous communication and localisation (PASCAL) system with a ground-to-air model. A scenario where multiple drones transmit communication signals to a base station (BS), which needs to simultaneously decode the signals and continuously locate the drones’ positions during the communication session, is considered. The BS operates in two stages: first, it estimates the drones’ location parameters using pilot signals; second, it performs data detection by reconstructing the channel response based on the estimated location parameters. The theoretical analysis presented in this paper demonstrates that the distributions of the estimated location parameters follow Gaussian distributions of which the mean values are equal to the actual values of the locations, and their variances are determined by the achievable mean square error of the estimator. Using these distributions, the average SER is derived to quantify the impact of localisation errors on decoding performance. This analysis highlights the synergy between communication and localisation, providing valuable insights into the influence of localisation inaccuracies on the performance of location-aware communication systems. Simulations are conducted to validate the theoretical derivations.