DFT-based low-complexity optimal cell ID estimation in NB-IoT

Vincent Savaux

doi:10.1186/s13634-020-00677-4

Abstract

This paper deals with cell identifier (ID) estimation for narrowband-Internet of things (NB-IoT) system. It is suggested to transform the usual maximum likelihood (ML) estimator expression in order to highlight a discrete Fourier transform (DFT), which can be computed with fast algorithms. Therefore, the proposed method is a DFT-based low-complexity cell ID estimator that can be qualified as optimal in the ML sense. The principle is extended to the practical case where the channel is unknown and must be estimated. In this scenario, the concentrated likelihood function needs to be maximized, in which the ML channel estimate is a function of the unknown cell ID parameter. This operation only involves a few additional multiplications. Simulation results reveal that the performance of the proposed method actually matches the optimal one of the ML cell ID estimator. Furthermore, the technique is robust to residual frequency offset up to several hundreds of Hertz. We also show that the mean square error of channel estimation reaches its Cramér-Rao bound (CRB).

Highlights

The Internet of things (IoT) market is growing rapidly as the number of applications increases in various domains such as industry, smart home, smart cities, and agriculture
Among the low-power wide area (LPWA) technologies allowing for long-range applications [1–3], narrowband-IoT (NB-IoT) is a promising solution as it is inherited from long-term evolution (LTE) [4–7]
The synchronization process is carried out according to two main steps: the devices physically synchronize with the evolved node B (eNB) using the narrowband primary synchronization signal (NPSS) [8–11] and seek the cell identifier (ID) of the neighboring eNBs through the narrowband secondary synchronization signal (NSSS)

Summary

Introduction

The Internet of things (IoT) market is growing rapidly as the number of applications increases in various domains such as industry, smart home, smart cities, and agriculture. Among the low-power wide area (LPWA) technologies allowing for long-range applications [1–3], narrowband-IoT (NB-IoT) is a promising solution as it is inherited from long-term evolution (LTE) [4–7]. Similar to LTE, NB-IoT devices work in licensed frequency bands, occupying one resource block of the LTE system. The synchronization process is carried out according to two main steps: the devices physically synchronize with the eNBs using the narrowband primary synchronization signal (NPSS) [8–11] and seek the cell identifier (ID) of the neighboring eNBs through the narrowband secondary synchronization signal (NSSS). We focus on the cell ID estimation process

Objectives

Methods

Discussion

Conclusion