Manchester Metropolitan University's Research Repository

Low-Power Wide Area Network Technologies for Internet-of-Things: A Comparative Review

Ikpehai, Augustine and Adebisi, Bamidele and Rabie, Khaled and Anoh, Kelvin and Ande, Ruth and Hammoudeh, Mohammad and Gacanin, Haris and Mbanaso, Uche (2018) Low-Power Wide Area Network Technologies for Internet-of-Things: A Comparative Review. IEEE Internet of Things. ISSN 2327-4662


Download (718kB) | Preview


The rapid growth of Internet-of-Things (IoT) in the current decade has led to the the development of a multitude of new access technologies targeted at lowpower, wide area networks (LP-WANs). However, this has also created another challenge pertaining to technology selection. This paper reviews the performance of LP-WAN technologies for IoT, including design choices and their implications. We consider Sigfox, LoRaWAN, WavIoT, random phase multiple access (RPMA), narrow band IoT (NB-IoT) as well as LTE-M and assess their performance in terms of signal propagation, coverage and energy conservation. The comparative analyses presented in this paper are based on available data sheets and simulation results. A sensitivity analysis is also conducted to evaluate network performance in response to variations in system design parameters. Results show that each of RPMA, NB-IoT and LTE-M incurs at least 9 dB additional path loss relative to Sigfox and LoRaWAN. This study further reveals that with a 10% improvement in receiver sensitivity, NB-IoT 882 MHz and LoRaWAN can increase coverage by up to 398% and 142% respectively, without adverse effects on the energy requirements. Finally, extreme weather conditions can significantly reduce the active network life of LP-WANs. In particular, the results indicate that operating an IoT device in a temperature of -20 degree C can shorten its life by about half; 53% (WavIoT, LoRaWAN, Sigfox, NB-IoT, RPMA) and 48% in LTE-M compared with environmental temperature of 40 degree C.

Impact and Reach


Activity Overview

Additional statistics for this dataset are available via IRStats2.


Actions (login required)

View Item View Item