Low-complexity sub-optimal cell ID estimation in NB-IoT system
Résumé
The cell identity (ID) estimation is one of the essential steps performed by the narrowband-internet of things (NB-IoT) user equipment (UE) during its initial access to the network. The cell ID value is carried by the narrowband secondary synchronisation signal (NSSS) that is periodically transmitted in even radio frames. In this study, the authors proposed a novel technique of cell ID estimation for the NB-IoT UE. The proposed technique is based on a sub-optimal estimator that applies auto-correlation over the received observations and which is 30 times less complex than the optimal maximum likelihood (ML) estimator based on cross-correlation. In addition, they presented three methods that allow the receiver to take advantage of the periodicity of the NSSS. Finally, the advantages and the drawbacks of the presented methods are discussed with a performance analysis through simulation results. Results show that these methods reach the performance of ML with lower overall complexity.