Happy together: solving the coexistence challenge for IoT devices
2018-09-07 | 8 min read
No one likes working in an overcrowded environment: it’s noisy, distracting, and interferes with what you’re trying to do. The same also applies to IoT devices. Ensuring reliable wireless performance in areas where there are many smart devices, all using different protocols on crowded radio bands, is challenging. These conditions often cause unexplained communications failures, even when the signal strength is sufficient for good operation.
These dropouts are often attributed to issues with coexistence, which is the ability of wireless equipment to operate in the presence of other devices using different communication protocols. The only way to ensure that devices deliver reliable wireless network performance, especially in mission-critical environments such as healthcare which demand uninterrupted connectivity, is to conduct rigorous coexistence testing. However, this is often easier said than done.
There are three main techniques which are commonly used to improve coexistence of devices and networks, but each has unique challenges that need to be overcome:
Physical separation: this aims to improve network operations by reducing the relative signal strength of two radio networks. By placing the two networks in different locations, each network experiences a weaker signal from the other, reducing the risk of interference. This can work well for some modulation types, but not all. For example, a hospital using the 2.4 GHz Industrial, Scientific and Medical (ISM) band may have thousands of wireless IoT devices using this band in operation, which makes physical separation impractical.
Frequency separation: this technique involves one network operating on a different frequency from another to reduce interference between the two, regardless of physical proximity. However, it is not always effective when it comes to the 2.4-GHz ISM band, which is occupied by overlapping Bluetooth, ZigBee, and 802.11 channels.
Time separation: here, transmissions are sent and received at different times to avoid collisions. However, as the volume of data transmitted on a network increases (which happens frequently in dynamic IoT ecosystems), simultaneous transmissions and collisions will occur more frequently. Additionally, most radio standards are not designed to detect other network transmissions and cooperatively share channels. This increases the chance of colliding transmissions that can cause errors and the need to retransmit data.
Designing your coexistence test
Despite these challenges, using one or more of these techniques is essential to enable reliable wireless performance for devices. This in turn requires an effective coexistence testing plan, which should include these four key stages:
- Characterize the expected RF environment
First, you need to accurately model the environment for the device under test. This involves taking field measurements of the frequency band of interest, usually with a Real-Time Spectrum Analyzer, as it allows spectrum to be continually and accurately sampled with a high-speed analog to digital converter. A real-time fast Fourier transform can then be performed to convert the data into a spectral view and identify the types of signals present. Traditional swept-spectrum analyzers are often ineffective for this stage, as digital transmissions can come and go from the device before the sweep even reaches the frequency in use, which means it will not be detected.
- Pick your test signals
After identifying the signals that are present, the type and number of signals needed to generate or model the coexistence test must be selected. This may mean choosing three different tiers of test signals, for example, one single Wi-Fi network passing data at the lowest tier, two Wi-Fi and one single Bluetooth signals at higher data rates, and then at the highest level, three Wi-Fi and five Bluetooth signals.
- Define functional wireless performance
The next stage is to define the functional wireless performance of the device, by listing out its required functions. These may include device startup and connection to the wireless network (for example, in the healthcare facility), successful sending of status reports, regular data exchanges per minute while roaming between access points, and so on.
- Choose the test’s physical format
There are four possible ways to configure test equipment for coexistence testing. Each configuration uses similar components: the device under test (DUT), the device that connects or pairs with it, competing network devices, and a spectrum analyzer. The configuration to use depends on practical considerations, such as access to external antenna connections on the DUT, and whether the device has directional antennas. The options are:
- Conducted test method: this is done entirely with coaxial cables connecting the test equipment and the DUT. It is the most quantitatively accurate test, but the least realistic at simulating the operating environment, so is best suited for initial tuning the DUT hardware and firmware.
- Multiple chamber test method: this uses multiple non-reflective chambers to provide a calibrated field at the location of the DUT. It allows the device’s antennas to be included in the test and radiated path loss to be controlled.
- Radiated-anechoic chamber test method: This uses a single, large anechoic test chamber to ensure that the environment does not decrease the repeatability of results. It provides additional information about how the DUT fails, and makes it possible to determine which part of the DUT is susceptible to interference.
- Radiated Open Environment test method: here, all equipment is placed in an open area. It is the least quantitative and repeatable test, but it is the most realistic.
When running coexistence tests and applying the results to your IoT environment, remember that these tests do not result in a simple ‘pass’ or ‘fail’. Rather, they focus on the probability that the device can meet its functional performance parameters in the test conditions. By varying those test conditions, device designers can chart the device’s coexistence behavior in detail, and mitigate the risk of interference affecting its performance in mission critical, real-world usage.