LoRa wireless module targets M2M, IoT applications

2nd November 2016

Avnet Abacus

Mick Elliott

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A new and highly compact module that is compliant with the LoRaWAN specification for narrowband wireless connectivity is in stock at Avnet Abacus. Measuring only 12.5 x 11.6 x 1.76mm in a metal-shielded LGA package, the low-cost module from Murata is one of the world’s smallest solutions for adding LoRa based wireless connectivity for a range of products and applications including Machine-to-Machine (M2M) communications and the Internet of Things (IoT).

Murata’s CMWX1ZZABZ-078 LoRa wireless module is designed to be a fully stand-alone solution. It can be deployed in a wide range of applications including smart metering such as gas and water meters, wearables, the tracking of livestock or other assets, M2M communications and sensor-based end nodes in IoT networks.

The module also has pre-certified radio regulatory approvals for operating in the 868 and 915MHz ISM spectrum. This makes it suitable for most geographical regions, thereby removing the requirement for developers to deliver separate solutions for different regions worldwide.

The module integrates the SX1276 RF transceiver from Semtech, along with the low-power STM32L Cortex M0+ based microcontroller from STMicroelectronics.

The STM32L includes 192-kbytes of flash memory and 20-kbytes of RAM, providing enough memory for customer applications and to host other modulation protocol stacks.

An integrated TCXO crystal oscillator has robust low drift thermal characteristics and provides an accurate clock source for the RF transceiver. 

Other specifications of the module include UART, SPI or I2C peripheral interfaces and integration of an ADC and up to 16 GPIOs, which provides plenty of flexibility for connecting sensors, switches and status LEDs.

The module operates from a 2.2 to 3.6VDC input voltage range and has an operating temperature range of –40 to +85°C, making it suitable for LoRaWAN networks that require the placing of sensor nodes in remote and unpredictable environments.