Getting to Grips With IoT Network Technologies

There are many different ways to connect your sensors to the web, but how to know which are best for your project?

How sensors communicate with the internet is a fundamental consideration when conceiving of a connected project. There are many different ways to connect your sensors to the web, but how to know which are best for your project?

Having just spent the better part of a week researching these new network technologies, this brief guide outlines the key aspects to focus on for an optimal IoT deployment:

Advanced radio technology

  • Deep indoor performance – networks utilising sub-GHz ISM (industrial-scientific-medical) frequency bands such as LoRaWAN, NWave and Sigfox are able to penetrate the core of large structures and even subsurface deployments.
  • Location aware networking – a variety of networks are able to track remote sensors even without the use of embedded GPS modules. Supporting sensors moving between hubs – with advanced handoff procedures and innovative network topologies mobile sensors can move around an area and remain in contact with core infrastructure without disrupting data transmission. Intelligent node handoff is also crucial for reducing packet loss, if the connection to one hub is hampered by passing through particularly chatty radiowaves, the node can switch to a better placed hub to relay it’s crucial payload.
  • Interference resistance – the capability of a network to cleave through radio traffic and interference that would ordinarily risk data loss.

Low energy profiling

  • Device modes – LoRaWAN is a great case and point with three classes of edge node: the first, Class A, allows a brief downlink window after each uplink upload i.e after having sent a message, the sensor listens in for new instructions; a Class A node appoints a scheduled downlink slot, the device checks in at a certain point; and the last, Class C type nodes, listen for downlink messages from LoRaWAN hubs at all times. The latter burns considerably more power.
  • Asynchronous communication – this enables sensors to communicate data in dribs and drabs where possible, services do not need to wait for eachother thereby reducing power consumption.
  • Adaptive data rates (ADR) – depending on the quality of signal and attenuation, modern networks are able to dynamically allocate data rate depending on interference, distance to hub etc. This delivers real scalability benefits, frees up space on the radio spectrum (spectrum optimisation) and improves overall network reliability.


  • Authentication – maintains data integrity by ensuring the sensor which is publishing that mission critical data really is that sensor and not an impostor node. Ensures information privacy.
  • End to end encryption (E2E) – prevents tampering and maintains system integrity.
  • Integrated security – good network security avoids potential breaches and doesn’t place the onus on costly, heavily encrypted message payloads.
  • Secure management of security keys – either written remotely on the initial install or embedded at manufacture, security keys are fundamental to system security. ZigBee’s recent security issue shows how not to manage security keys, by sending them unencrypted over-the-air to devices on an initial install.
  • Receipt acknowledgement – ensures mission critical data is confirmed received by network or device.

Advanced network design

  • Full bidirectional comms – enables over the air (OTA) updates, enabling operators to push new firmware or system updates to thousands of remotely deployed sparse sensors at the push of a button. This is critical to a dynamic and responsive network. As with device modes mentioned previously, bidirectionality allows deployed devices to function as actuators and take action (close a gate, set off a fire alarm etc) rather than just one-way sensors publishing to a server.
  • Embedded scalability and consistent QoS – as load increases on a network so too does the capacity of the network. This takes the form of adaptive data rates, prevention of packet loss by interference and channel-blocking, the ability to deploy over-the-air updates and ensuring the capability to add nodes, hubs and maintain existing assets without impacting on overall network service, perhaps through automatic adaptation.

There are also a number of legal, cost, market and power focused aspects worth considering that I shall not cover here. But, critically, it’s worth mentioning that the majority of these technologies operate on ISM (industrial – scientific – medical) frequency bands, and as a result are unlicensed. These bands are regulated and there are rules, however anyone operating on these bands can do so without purchasing a license. Notably, you don’t have sole ownership of a slice of the spectrum, you don’t get exclusive access. Therefore, with a variety of other vendors blasting away across the radio waves, these technologies encounter significantly more interference than the licensed spectrum. However, the new networks, LoRa, Sigfox, NWave etc are based on protocols and technologies designed to better sort through this noisy environment, grab a channel and send a message.

Understanding that the airwaves are a chaotic mess underlines the importance placed on features such as adaptive data rates, node handoff and power saving methods such as asynchronous communication. Wired networks do not have to consider such things. But for most it’s not just a case of who shouts loudest wins. The majority of wireless protocols ‘play nice’ opting for a polite “listen, then talk” approach, waiting for a free slot in the airwaves before sending their message.

Some protocols such as Sigfox forego such niceties and adopt a shout loud, shout longer approach, broadcasting without listening. A typical LoRaWAN payload takes a fraction of a second to transmit, Sigfox by comparison sends messages 3-4 seconds in length. However, if you just broadcast without listening, Sigfox must therefore operate with severe cycle duty limitations, which translate into a limited number of messages sent per device per day and severe data rate limitations.

These choices also translate into varying costs, and critically, into battery life limitations and gains, the crux of any remote deployment.

See this link for a matrix of the major technologies currently vying for network domination.

What Is LoRaWAN?

Confused about why it’s better than Zigbee? Let us help…

What is LoRaWAN and why is it “better” than Zigbee?

Even long-time IoT enthusiasts struggle with the wealth of technologies that are on offer these days. One of the most confusing phenomena for someone who isn’t a RF engineer is the scale and range of LoRaWAN. If you’ve been in the game for a while, you may have used a ZigBee radio module for wireless data transmission in your own projects. ZigBee-compliant modules had become a gold standard for many industrial applications in the 2000s, featuring >10m range (it was said to be 100m, but that was hardly ever achieved), up to hundreds of kbit/second transfer rate (depending on the model and radio band used) and message encryption by default. Over most cheap proprietary RFM22 transceivers, ZigBee also offered an industry standard following the IEEE 802.15.4 specification for mesh networking. This allowed ZigBee devices to forward messages from one to another, extending the effective range of the network. Despite their rich features, ZigBee devices are limited in range and limiting when it comes to their power consumption and the potential use in IoT application. And this is where LoRaWAN comes into play: It’s a Low-Power Wide Area Network (LPWAN) standard promising a reach of tens of kilometres for line-of-sight connections and aiming to provide battery lives of up to ten years. How can this work?

First, let’s contrast short-range radio standards like the ZigBee with the LPWAN standards like LoRaWAN. RFM22, ZigBee and LPWAN all use radio frequencies in the ultra high frequency (UHF) range. Following the ITU 9 classification, these are devices that use a carrier frequency of 300 MHz to 3 GHz. That is, the radio waves have a peak-to-peak distance of 10-100 cm — a tiny proportion of the electromagnetic spectrum. Here, we find television broadcasts, mobile phone communication, 2.4 GHz WiFi, Bluetooth, and various proprietary radio standards. We all know that television broadcasting transmitters have a significant range, but clearly that’s because they can pack some punch behind the signal. There must be another reason that LoRaWAN does better than the other radio standards. The carrier frequency itself can therefore not explain the range of LPWAN standards.

There is all sorts of hardware trickery that can be applied to radio signals. Rather than allowing those electromagnetic waves orientate randomly on their way to the receiver, various polarisation strategies can increase range. A circular-polarised wave that drills itself forward can often more easily penetrate obstacles, whereas linear-polarised signals stay in one plane when progressing towards the receiver, concentrating the signal rather than dispersing it in different directions of the beam. However, these methods require effort and preparation on both the sender and receiver side, and wouldn’t really lend themselves to IoT field deployment…

The secret sauce of LPWAN is the modulation of the signal. Modulation describes how information is encoded in a signal. From radio broadcasting stations you may remember ‘AM’ or ‘FM’, amplitude or frequency modulation. That’s how the carrier signal is changed in order to express certain sounds. AM/FM are analog modulation techniques and digital modulation interprets changes like phase shifts in the signal as binary toggle. LPWAN standards are using a third set of methods, spectrum modulation, all of which get away with very low, noisy input signals. So as the key function of LPWAN chipsets is the demodulation and interpretation of very faint signals, one could think of a LoRaWAN radio as a pimped ZigBee module. That’s crazy, isn’t it? To understand a little more in detail how one of the LPWAN standards works, in the following we are going to focus on LoRaWAN as it is really ‘the network of the people’ and because The Things Network -a world-wide movement of idealists who install and run LoRaWAN gateways- supports our idea of open data.

LoRaWAN uses a modulation method called Chirp Spread Spectrum (CSS). Spread spectrum methods contrast narrow band radio as ‘they do not put all of their eggs into the same basket’. Consider a radio station that transmits its frequency-modulated programme with high power at one particular frequency, e.g. 89.9 MHz (the carrier is 89.9 MHz with modulations of about 50 kHz to encode the music). If you get to receive that signal, that’s good, but if there is a concurrent station sending their programme over the same frequency, your favourite station may get jammed. With spread spectrum, the message gets sent over a wide frequency range, but even if that signal is just above background noise, it is difficult to deliberately or accidentally destroy the message in its entirety. The ‘chirp’ refers to a particular technique that continuously increases or decreases the frequency while a particular payload is being sent.

The enormous sensitivity and therefore reach of LoRaWAN end devices and gateways has a price: throughput. While the effective range of LoRaWAN is significantly higher than ZigBee, the transmitted data rate of 0.25 to 12.5 kbit/s (depending on the local frequency standard and so-called spreading factor) is a minute fraction of it – but, hey, your connected dishwasher doesn’t have to watch Netflix, and a payload of 11-242 bytes (again, depending on your local frequency standard etc) is ample for occasional status updates. Here is where the so-called spreading factor comes into play. If your signal-to-noise ratio is great (close proximity, no concurrent signals, etc), you can send your ‘chirp’ within a small frequency range. If you need to compensate for a bad signal-to-noise ratio, it’s better to stretch that ‘chirp’ over a larger range of frequencies. However, that requires smaller payloads per ‘chirp’ and a drop in data rate.

Power consumption, reach and throughput are all linked. To burst out a narrow transmission consumes more power than to emit a spread signal. Hence, LoRaWAN implements an adaptable data rate that can take into account the signal-to-noise ratio as well as the power status of a device.