The Internet reached an important milestone a little over 10 years ago. Around 2004/5, according to Cisco, we reached a point where there were as many devices (“things”) as people on the planet connected to the Internet. In fact, today this global network is called the “Internet of Things” (“Internet of Things”, IoT). It is estimated that there are currently between three and four Internet-connected devices per person and this number will almost double over the next three years, which is equivalent to 26.000 billion IoT devices by 2020 (according to Gartner). Although many organizations are investing a lot of resources, it is difficult to predict the size of the total IoT market. Early forecasts indicated more than 50.000 billion devices, but a more realistic and recent forecast from ABI points to a total of 36.000 billion IoT-connected devices by 2020. ABI's forecast anticipates a figure of 19.000 billion IoT nodes, 11.000 billion of gateways and 6.000 million mobile devices. The revenue potential for IoT in the future is even more difficult to estimate due to the newness and rapid growth of the sector. The McKinsey Global Institute estimates a figure between $4 trillion and $11 trillion in 2025.
Whatever the actual number of devices and associated billing, it is clear that IoT is set to be a significant part of the future. When comparing IoT and the Internet “normal”, it becomes clear that a much larger proportion of their IoT activity is from machine-to-machine (M2M) communications. The information that circulates through this network is generated, interpreted, stored and works mainly through the direct intervention of a person. Each of these uniquely identifiable embedded devices exists within the existing infrastructure of the Internet and, when interconnected, will facilitate automation in virtually every aspect of daily life, as well as enable advanced applications in the future. Very soon, in fact, already in 2020, it is estimated that household devices such as household appliances and air conditioning systems will exceed the number of computers on the Internet. The rapid growth of applications is due to the combination of new product concepts (such as wearable fitness devices) and smart factories that can be controlled and monitored remotely, as well as the evolution of established technologies, for example, applications in smart homes (such as automated lighting and heating controls). Innovators will continue to push IoT forward to create new applications, some of which we already know about, and certainly some that we haven't even thought of yet. However, by definition, IoT relies on communication for its very existence, and due to the remote location of numerous devices, such as sensors, wireless communication technologies allow the promising world of IoT to exist.
IoT ecosystem
With the strong trend of applications moving from fixed to wireless networks, the entire radio spectrum is a widely used valuable asset. The availability of spectrum bandwidth is most crucial for the evolution of wireless sensor networks (WSNs) in IoT. In the IoT environment, each connected device is an intelligent mode that detects information and performs some kind of signal processing and conditioning, whether digital or analog. An example of this would be the filtering of valuable signals from noise in order to reduce the spectral bandwidth required for data communications. In commonly used configurations, IoT sensor devices communicate with a gateway (or data collector) from which data can be routed to the Internet and a centralized, centralized data storage that securely protects, stores, and processes the information. . Fig. 1 offers a possible representation of an IoT ecosystem in which sensor data is managed remotely via the Internet. Melexis wireless sensors and products can be used in various applications, both on the IoT sensor devices themselves and as a gateway connecting to the Internet in general.
Below 1 GHz: greater distances
There is an industry-wide debate about whether to use radio below 1 GHz or 2,4 GHz as the preferred carrier for all types of wireless data communications and sensing applications. Within the IoT infrastructure, 2,4 GHz often means Bluetooth-based technologies (such as Bluetooth Low Energy, BLE) or Wi-Fi. Below 1 GHz are mainly the ISM bands, for example at 433,92 MHz or 868,3 MHz. A system based on 2,4 GHz offers a relatively high data rate, generally on the order of several megabits per second (Mbps) for Wi-Fi and substantially lower at about 260 kbps for BLE. Naturally, Wi-Fi is compatible with WLAN infrastructure such as routers, and can therefore be directly connected to the IoT. Various versions of Bluetooth can connect directly to a mobile device, which in turn provide a connection to the IoT/Internet. One drawback of a 2,4 GHz wireless link is its relatively short range (<10 m) due to high propagation losses compared to sub-1 GHz systems. Below 1 GHz is ideal if The long range (up to 1 km outdoors) is important for the application or installation as it provides high levels of robustness as well as excellent immunity to disturbing signals through the use of narrow band radio channels (often on the order of 25kHz). In addition, devices that operate below 1 GHz usually use their own protocols, their optimization is relatively simple in terms of efficient consumption and battery autonomy, two fundamental factors for remote sensors in IoT powered by batteries or dedicated to energy harvesting. . Fig. 2 shows various IoT applications that stand out for taking advantage of technology below 1 GHz.
Carrier frequency acceptance is important
An important element when using wireless links for any application, but especially IoT applications, is the ability for receiving nodes to track carrier frequency deviations from transmitting nodes. Modern embedded RF receivers and transceivers use quartz crystal technology to generate a local reference frequency in each device. Cheaper crystals typically offer frequency stability of approximately ±10 ppm to ±50 ppm. Less integrated RF products, often based on devices like SAW resonators, tend to be less stable with tolerances of ±100 ppm. Classic analog RF transceivers and receivers usually incorporate demodulators with the same phase. They generally use an external discriminator circuit or an integrated FSK demodulator. As a result of the analog demodulation principle, these products offer a carrier frequency acceptance range of up to ±100 kHz. If we analyze the carrier frequency of an 868,3 MHz IoT transmitter node based on a low-cost crystal reference with a tolerance of ±50 ppm, the center frequency of the node can have a spread of ±43 kHz. This value may exceed the FSK offset, which is a fundamental modulation parameter. Typically allowable FSK offset values for IoT sensor node applications are between ±10 kHz and ±50 kHz. However, RF products with analog demodulators can accept carrier frequency spread greater than the FSK deviation due to their broad carrier frequency acceptance. Modern highly integrated RF products perform demodulation and many other necessary signal conditioning operations in the digital domain. This is possible thanks to modern semiconductor processes based on reduced geometries that allow very compact IC designs. However, due to their digital nature, most modern RF transceivers are characterized by relatively small carrier frequency acceptance ranges when compared to their existing analog counterparts. Therefore, receiving a signal from an IoT sensor node can be difficult for a digital RF receiver if the sensor node offers poor frequency accuracy due to large crystal tolerance.
Melexis High Integration RF Transceivers
Melexis' modern MLX73290-M RF transceiver provides a solution that works well with the wide tolerances of the carrier frequency. Fig. 3 shows the block diagram of the MLX73290-M. As you can see, a significant part of the device is based on digital technology, shown in the gray box. The MLX73290-M is a multi-channel RF transceiver IC that takes advantage of Melexis' long experience in low power wireless devices. The product, which works in ISM bands below 1 GHz between 300 MHz and 960 MHz, offers two RF channels, each with a programmable RF power transmitter (with power detectors) and an RF receiver of high sensitivity. It is fully programmable through its SPI interface (serial peripheral interface). This IC is well suited for wireless applications below 1 GHz such as home/building automation, tire pressure monitoring (TPMS), automatic meter reading (AMR), alarm systems, systems passive keyless entry (PKE), medical diagnosis and telemetry. Its output power level is -20 dBm to 13 dBm in 64 steps, while its receiver sensitivity can go as low as -120 dBm in a 15 kHz bandwidth. With a maximum data rate of 250 kbps, the transceiver is also capable of handling faster data processing. Due to its high degree of programmability, engineers using this IC have many possibilities for configuring and implementing an RF input stage. A wide variety of RF parameters (number of channels, frequency resolution, output, frequency deviation, etc.) can be adjusted to meet certain application criteria. In addition, it supports OOK (onoff keying), FSK (binary frequency shift keying), MSK (minimum shift keying), GMSK (Gaussian minimum shift keying) and GFSK (Gaussian frequency shift keying) modulation techniques. Two RF power detectors allow the radiated power to be increased during transmission and thanks to an energy capture interface it can be powered without a battery by means of a solar cell and a supercapacitor.
This enhances the value of the transceiver in remote locations with no power supply. Report cards and software tools are also available. The MLX73290-M is supplied in a 32-pin, 5mm x 5mm QFN package. Its working temperature range is from -40°C to 105°C and its supply voltage range is from 2,1 to 3,6V DC. The device incorporates a PLL synthesizer with a resolution of 60 Hz, a FIFO of 256 bytes that can be divided into 128/128 for reception/transmission and a total of 4 programmable GPIO ports for connection to other elements of the system. Due to its carrier recovery function, the MLX73290-M transceiver is able to tolerate a carrier frequency deviation of up to twice the Raw Data Rate (DR), which is usually expressed as ±2 x DR. The Carrier Frequency Acceptance Range (CFAR) does not depend on the AFC setting. AFC simply allows bearer recovery to converge to a certain value after each packet, in turn reducing the preamble length if the application can tolerate losing a few packets at startup. Fig. 4 illustrates the Packet Error Rate (PER) relative to CFAR. The example shown is for a DR of 55,6 kbps with an FSK offset of ±50 kHz. As can be seen, there is an interrelationship between the preamble length (the part of the packet during which bearer recovery tries to converge) and the PER.
Conclusion
There is no doubt that as the demand for IoT devices grows substantially, consumers and users will increase the pressure on the manufacturers of these devices, requiring them to reduce costs with each generation of products. This will inevitably lead to increased use of low cost crystals with higher frequency tolerances in sensor nodes to achieve this goal. As designers search for elegant solutions to this trade-off between cost and performance, the MLX73290-M RF transceiver, with its wide carrier frequency acceptance range, will become a popular solution for data collection in IoT, as well as for bidirectional network nodes.
