For low-power wide-area networks (LPWANs) operating in license-exempt spectrum, a major advantage is low network costs. However, given the exponential growth of IoT devices, shared limited radio resources are becoming increasingly crowded. In order to improve quality of service (QoS) and network scalability, ensuring immunity to interference in LPWAN is a major task.
Understanding interference in unlicensed spectrum
Interference is when two radio signals conflict unnecessarily on the same frequency, resulting in data loss. Interference with license-free LPWANs falls into two broad categories:
1. Intra-system interference, or self-interference, refers to interference caused by devices operating within the same network, such as within the MIOTY network or within the LoRa network. Self-interference is mainly attributed to asynchronous communication using the ALOHA scheme in many LPWAN systems. Although power consumption is greatly reduced, purely ALOHA-based networks will produce significant self-interference due to uncoordinated random data transmission between end devices.
2. Inter-system interference refers to interference caused by radio signals from other systems. Since license-free spectrum is available to everyone, multiple technologies coexist and access the same frequency resources. For example, most LPWAN technologies, including MIOTY, LoRa, and Sigfox, typically use sub-gigahertz industrial, scientific, and medical (ISM) radio bands. Similarly, Ingenu, another LPWAN player, shares the crowded 2.4GHz band with Wi-Fi, Bluetooth, Zigbee, and more.
Intra- and inter-system interference can degrade network performance and hinder scalability.
LPWAN anti-interference technical methods
Among these challenges, robust system design is key to ensuring high interference immunity of LPWAN. Below we describe four technical approaches to controlling and mitigating intra- and inter-system interference.
1. Exploiting (ultra)narrow bandwidth
Compared to spread spectrum-based broadband approaches, (ultra)narrowband technologies mitigate intra-system interference issues. Each narrowband message uses a very small bandwidth, resulting in high spectral efficiency. As a result, more messages can be put into a designated frequency band without overlapping each other, allowing more devices to operate efficiently at the same time without interfering with each other. This increases overall network capacity and system scalability. Minimal bandwidth usage also reduces the noise level of each signal.
Think of narrowband messaging as a motorcycle and broadband messaging as a truck. We can carry many more motorcycles than trucks on the highway without causing an accident.
2. Reduce broadcast time
In many LPWAN systems, the signal’s transmission time, or broadcast time, can be as long as 2 seconds. This is problematic because the longer a message takes to “broadcast”, the more likely it is to conflict with another message sent at the same time, which can result in data loss. Longer transmission times also increase the chances of malicious and sophisticated attacks, such as selective jamming.
3. Frequency hopping
Frequency hopping increases resistance to inter-system interference by quickly switching messages between different channels during transmission. Constant frequency variation helps avoid channel congestion and makes signals difficult to intercept. The downside is that frequency hopping is very spectrally inefficient because it requires the use of a larger bandwidth. Broadband signals transmitted at low rates can easily overlap, causing self-interference and data loss.
4. Forward Error Correction (FEC)
Applying channel coding or forward error correction allows detection and correction of transmission errors due to noise, interference and fading. In unreliable or noisy channels, FEC helps reduce the bit error rate of digital signals, improves the reliability of signal transmission, and avoids costly data retransmissions.
To date, no traditional LPWAN system has successfully leveraged all of these approaches in its system design. LPWAN using a (ultra)narrowband approach offers high spectral efficiency but suffers from extended broadcast times due to very slow data rates. Spread spectrum systems take advantage of frequency hopping but suffer from self-interference and scalability issues due to the wide bandwidth used.
Telegram splitting applies the advantages of the above 4 methods into one system by splitting ultra-narrowband messages into multiple smaller sub-packets and distributing them in a pseudo-random time and frequency pattern. Due to its much smaller size, each sub-packet has an extremely short broadcast time of only 15 milliseconds. Therefore, the chance of conflicts with other inter- and intra-system signals is greatly reduced. Additionally, built-in forward error correction (FEC) enables successful message retrieval even if up to 50% of sub-packets are lost in the process.
As device density and communication traffic continue to grow in the IoT era, anti-interference capabilities in low-power wide area networks will continue to be a top priority. Also, choosing robust technologies without compromising on cost and energy efficiency.
Palabras clave: lora communication technology