Low-Complexity Maximum-Likelihood Detector for IoT BLE Devices

Autor: Jose Valencia-Velasco, Luis Pizano-Escalante, O. Longoria-Gandara, Rodrigo Aldana-López
Rok vydání: 2020
Předmět:
Zdroj: IEEE Internet of Things Journal. 7:4737-4745
ISSN: 2372-2541
Popis: Internet of Things (IoT) is a technology that has overgrown and whose interest lies in the connection of diverse kinds of devices to collect and exchange data. Since most IoT devices are mobile, the hardware resources are hard limited; thus, complexity reduction becomes a relevant concern in this context. Bluetooth low energy (BLE) communication standard has an important position in IoT due to its Gaussian frequency-shift keying (GFSK) modulation scheme employed in the physical layer, which provides both attractive spectral and power efficiency. Typically, GFSK requires a maximum-likelihood sequence estimator (MLSE) implemented through the Viterbi algorithm (VA) at the receiver. This article provides a GFSK receiver based on a new paradigm that transforms the I-Q baseband signal and uses the VA with a reduced-complexity proposed metrics. Comparisons of theoretical and simulated results are presented, and they show that the proposed metrics for the GFSK receiver are compliant with the Bluetooth standard. Henceforth, the proposed receiver is an attractive scheme for IoT BLE devices.
Databáze: OpenAIRE