Eric Hsu | Keysight Technologies, Inc.
The demand for wireless communications now challenges the physical limitations of today’s wireless communications systems. Interference can easily arise when systems operate in a crowded wireless environment using a shared spectrum. Signal congestion makes the process of designing, testing, and isolating system problems more complex.
In the next few years, billions of devices will connect through many different and emerging wireless technologies. Each device may integrate with two or more wireless standards. With many wireless standards using the same unlicensed bands, device manufacturers must verify that neither co-channel nor adjacent-channel interference will degrade their designs. This situation presents challenges to device designers as design and verification testing becomes more complex, time-consuming, and expensive.
For example, consider the most commonly used 2.4-GHz industrial, scientific, and medical (ISM) band, which includes wireless standards such as Bluetooth, WI-Fi, and ZigBee. These longtime standards enjoy broad support in both the integrated circuits (ICs) and integrated modules that are built into IoT devices.
Co-existence in the unlicensed band comes with a price. Bluetooth uses the frequency-hopping spread spectrum (FHSS) technique, and Wi-Fi uses direct sequence spread spectrum (DSSS) and orthogonal frequency-division multiplexing (OFDM) as a way to increase resistance to interference. Furthermore, Bluetooth enhanced the FHSS with the adaptive frequency hopping (AFH) to resist interference in the 2.4-GHz ISM band. Wi-Fi added the dynamic frequency selection (DFS) to avoid interference with radar signals in the 5-GHz band. Designers must take various interfering signals into account when evaluating the receiver performance of wireless IoT devices.
Consider a digital radio receiver. First, the receiver must extract the RF signal in the presence of potential interference. A preselecting filter, the first component of the receiver, attenuates out-of-band signals received from the antenna. A low-noise amplifier (LNA) then boosts the desired signal level while minimally adding to the noise of the radio signal. Next, a mixer down-converts the RF signal to a lower intermediate frequency (IF) by mixing the RF signal with a local oscillator (LO) signal. Finally, the IF filter attenuates the unwanted frequency components that the mixer generates along with signals from adjacent frequency channels. The variations in the receiver’s design manifest after they pass through the IF filter.
Receiver design is challenging because the wireless device manages a wide variety of input signal conditions, and they are difficult to predict. Also, you need to inject noise and interfering signals to characterize the receiver’s performance.
Quantifying receiver performance
Several parameters serve to help quantify how receivers behave. The most common measurement parameters include receiver dynamic range, signal-to-noise ratios, channel selectivity, blocking, receiver intermodulation distortion, and receiver spurious emissions. A common wireless receiver test is the receiver dynamic range, which includes minimum input sensitivity, maximum input level, and channel noise. For different wireless standards, the definition of the receiver’s dynamic range might be different — it can be the range of input levels or signal-to-noise ratios.
A wireless receiver’s dynamic range test is the input power to an RF receiver at a minimum, and maximum level — the bit-error-rate (BER) or packet-error-rate (PER) does not exceed specified values. Wireless standards, such as Bluetooth and Wi-Fi, define wireless receiver minimum input sensitivity and maximum input level test cases. The standards determine the upper and lower levels of the wireless receiver’s dynamic range.
Another definition of dynamic range is a measure of the capability of the wireless receiver to receive a wanted signal in the presence of an interfering signal. This measurement takes place inside the received channel bandwidth in the 3GPP standard (technical specification 36.104, section 7.3). To simulate realistic channel conditions in a repeatable manner, you need to add random noise — additive white Gaussian noise (AWGN) to the wanted signal.
Channel selectivity is a measure of the receiver’s ability to receive a wanted signal in the presence of an interference signal with a specified channel offset. The interference can be co-channel, adjacent-channel, or alternate-channel signals. This test verifies that a receiver can establish and hold a connection if other channels are in use.
The blocking characteristic is a measure of the receiver’s ability to receive a wanted signal in the presence of an unwanted interferer. The interferer is a modulated or continuous wave interfering signal, typically at a high output power level. The modulated signals simulate co-location with other wireless devices but in a different wireless format.
Third- and higher-order mixing of the two interfering RF signals can produce intermodulation signals in the band of the desired channel at a receiver. The intermodulation signals may degrade the receiver’s sensitivity performance. If the interfering signals are f1 and f2, one of the third-order intermodulation products
(frx1 = 2 f1 – f2 and frx2 = 2 f2 – f1) may fall within the passband of the receiver.
Spurious emissions are unwanted emissions that emanate from the devices under test. Receiver spurious emissions are generated internally by the receiver or result from the interaction of the receiver with the coupling transmitter’s signal. A receiver spurious emissions power measures the power of emissions generated or amplified in a receiver that appears at the antenna connector. The purpose of the test is to limit the interference caused by receiver spurious emissions to other devices or systems.
For long-distance wireless communications, the multipath signals may add up constructively or destructively at the receiver. The Doppler effect causes a frequency shift at the receiver. The effects of multipath and Doppler shift cause linear distortions that are reducible with an adaptive equalizer of a receiver. Also, systems’ channel coding and antenna diversity will reduce the effects. Like the receiver test, test specifications indicate sensitivity or throughput tests under specific channel conditions.
With multiple wireless standards using the same frequency bands, wireless device manufacturers need to verify not only common receiver test cases but also various test scenarios involving interactions of multiple systems. Receiver spurious emissions and intermodulation tests help to identify potential problems with your designs to prevent system degradation. To improve measurement accuracy when you perform these tests, be aware of port termination, signal isolation, and band rejection to improve measurement accuracy. Whether you are working on a single radio format or integrating multiple formats into a wireless device, easy access to the right test signals streamlines validation ensures interoperability.
White paper: Navigate the Complexity of IoT RF Receiver Testing
White paper: Making Noise in RF Receivers
Application note: Testing and Troubleshooting Digital RF Communications Receiver Designs