May 24, 2018

Designing Low Power IoT Applications? Ask the Experts Part 2: LPWA Technology Features and Data Management

Did you read our first blog, summarizing the questions and answers around Low Power IoT applications?

In the second installment, we summarize additional answers from Altair’s Director of Product Management Dima Feldman, together with Bryan O’Flaherty Wills and Gus Vos from Sierra Wireless, who answered your questions on LPWA technology features and data management in this webinar.

How does proprietary LPWA differ from LTE-M and NB-IoT?

The main difference is that proprietary LPWA technologies, such as LoRa and Sigfox, operate on unlicensed spectrum – the primary benefits being it is free. However, this also entails significant drawbacks, namely that unlicensed spectrum is used by multiple users, leading to increased interference over time. Therefore, there is no guarantee of quality of service – such as data rates, latency, battery life and coverage – and so the performance five years on may be significantly different to that at time of deployment. Due to regulatory issues on unlicensed bands, proprietary base stations have very limited duty cycles and cannot support large firmware downloads, IP messaging and robust security protocols. Proprietary LPWA networks are also deployed differently, requiring new base station installations, while LTE-M and NB-IoT can be rolled out via software upgrades to the existing infrastructure. Finally, proprietary LPWA IoT networks generally target very low-end applications, even simpler than NB-IoT. Having only limited support, they don’t carry IP data and provide little more than an SMS-type messaging interface.

What are the maximum throughput and latency capabilities of LTE-M and NB-IoT?

This is best illustrated in the following table, showing the sustained peak data rates:

Peak Data Rates and Latency

DL Speed (kbps) UL Speed (kbps) Latency Ping (ms)
LTE-M Rel 13 300 375 20
Rel 14 590 1100 20
NB-IOT Rel 13 20 60 50
Rel 14 85 150 50

It should be noted that, in the interest of accuracy, these figures include scheduling delays, as LTE-M and NB-IoT are all scheduled. If you don’t include scheduling, the NB-IoT data rate would be closer to 225 kbps, as opposed to the 20 kbps shown here for Release 13. There will also be a substantial increase when it comes to Release 14, especially for NB-IoT.

Is NB-IoT suitable for mobile applications?

Unlike LTE-M, NB-IoT does not support connected mode (i.e. when the device is sending data) mobility but does support idle mode (i.e. when it is not sending data). So once the device starts sending data, it can no longer track neighboring cells and so cannot hand over to other base stations when mobile. The result is that coverage can becomes worse as the device move and so these devices use considerably more network resources and more device power. In extreme cases, the connection can be lost completely and the whole transaction must start again, consuming even more power and resources. Therefore, NB-IoT only works for “slow mobility” – such as pedestrian and bicycle, but won’t be feasible for highly mobile applications, such as vehicle telematics or applications that send streaming data.

What communication protocols do LTE-M and NB-IoT support?

Cellular LPWA, being IP-based, comes with a suite of protocols which we are used to seeing with IP networking. When it comes to LPWA, we tend to think of low bandwidth and efficient messaging, and so lightweight M2M and MQTT (Message Queuing Telemetry Transport) are increasingly seen as standards for communicating on these networks. LTE-M also supports SMS.

How does data orchestration complement LPWAN to improve battery life?

Data orchestration provides knowledge of the context of the data, so it can be utilized with different variables to understand how to send the necessary data at the right time and with the required priority. Take, for example, a medical tote transporting blood samples for testing. These are extremely sensitive to changes in temperature and are at risk of expiring before being processed. They may go from clinic to vehicle, cross town, and then enter a hospital or research center where they deeply embedded in the building. Throughout this process, the signal strength will fluctuate dramatically – as will the power necessary to transmit the data. Data orchestration can optimize power while tracking these samples to make the right decision about when to send different events based on signal strength. This may include withholding a temperature reading when signal strength is poor, in favor of an anti-tampering alert which should be sent immediately.

For those who missed it, the full recording of our webinar, LPWA Expert Panel: Answering Your Questions on Designing Low Power IoT Applications, can be accessed here.