The “Perfect Simulation” for Wireless Receiver Test

One application that is well-served by RF stream-to-disk technology is wireless receiver design verification and vilification. In this paper, we will discuss several challenges of the wireless environment and explain the motivation for recording these signals with RF stream-to-disk systems.

Introduction

Modern wireless receivers are subject to a variety of increasingly of unpredictable RF environmental conditions.  Changes in weather, interference from interfering transmitters, and the existence of physical structures can have dramatic affects on the receiver signal.  As a result, wireless receiver validation and verification requires increasingly complex test stimulus waveforms.  Moreover, while mathematical models can emulate many of the characteristics of a real-world physical environment, using the real signal provides an even more accurate solution.  In the past, wireless receiver validation and verification required expensive and often non-repeatable field tests.  However, recent RF instrument innovations such in PXI Express bus technology and the increased disk speeds of today’s RAID (redundant array of inexpensive disks) technology enables engineers to take the physical environment back to the lab.

This sounds revolutionary, and it really is.  Today’s RF record and playback systems enable generation or acquisition of RF signals for up to several hours of time.  More specifically, the PXI and PXI Express vector signal generators and vector signal analyzers enable record and playback of up to 20 MHz of real-time RF bandwidth at frequencies up to 2.7 GHz.  As a result, validation and verification of wireless receivers can now be performed with greater accuracy and with less expense. 

Challenges in the RF Environment

Real world communication channels are subject to a variety of imperfections.  Impairments such as fluctuations in signal strength, multi-path reflections from physical structures, and interference from other communications channels can dramatically affect the quality of a received signal. 

Variations in Signal Strength

Signal strength can affect demodulation of communication signals because it affects the signal-to-noise ratio (SNR) of the signal of interest.  In an ideal world, wireless communication signals would be much higher than the noise floor of the receiver.  However, signal strength decreases with the distance from the base station.  In these situations, demodulation of a communications channel becomes impossible when the signal strength is too low.

To illustrate this affect, we can model the low signal strength by introducing additive white Gaussian noise (AWGN).  For illustration purposes, we have added AWGN to an ideal communications signal such that the SNR is on the order of 30 dB.  As the constellation plot (below) illustrates, signal to noise ration can reduce error vector magnitude (EVM) performance of the wireless receiver.

Figure 1. Demodulation of 4-QAM signal with SNR = 30

For a QPSK (quadrature phase shift keying) modulated signal, a SNR of 30 dB will not significantly impair the communications channel.  However, increasing the distance from the base station or increasing the complexity of the modulation scheme can significantly impair the performance of the communications channel.  By contrast, using a more complex modulation scheme such as 64-QAM (quadrature amplitude modulation) under the same conditions would be impossible.

Multi-Path Signal Interference

If you’ve ever tried using a GPS receiver in a downtown environment, you may have noticed the affects of multi-path interference.  Particularly with low-level signals such as GPS, multi-path interference can cause severe fluctuations or distortion of a communications channel.  In the wireless environment, signals propagate from a transmit tower to a receiver according to multiple signal paths.  While we typically think of line-of-sight propagation first, signals actually can take a variety of paths to the receiver.  This is illustrated in the figure below:

Figure 2. Presence of physical structures results in multi-path propagation.

Unfortunately multi-path signal propagation results in phase and amplitude fluctuations of the signal observed by the receiver.  In a communications channel, this is called intersymbol interference (ISI) and it can increase bit-error-rate (BER) of the receiver. 

To illustrate the affect of multi-path interference on a modulated signal, we can simulate multi-path products with a Raleigh fading profile in LabVIEW.  The Raleigh fading profile is a mathematical model used to represent multi-path reflections in an environment where a line of sight from the transmitter to receiver is not present.  For this reasons, it is commonly used to model the multi-path characteristics of cellular networks such as GSM. 

We can visualize the affects of multi-path propagation using a constellation plot in LabVIEW.  In this graph, shown at right below, each recovered symbol appears to show periodic fluctuations in phase or amplitude because of the multi-path signal products. 

Figure 3. Constellation plot with simulated Raleigh fading.

The Raleigh fading profile provides a reasonably accurate mathematical representation of a wireless environment.  However, testing under actual environmental conditions still provide the most accurate assessment of receiver performance.

Interference or Blocker Signals

A third challenge of wireless communication channels is interference from other communication signals.  Interference can be caused by a number of sources including misdirected antennas, illegal transmissions, and the presence of non-conformant hardware.  Of these types of interference, antenna misdirection is perhaps the most interesting.  In this scenario, an antenna at an adjacent base station can cause interference if it just a few degrees off of its desired azimuth.

A common test technique used to characterize a wireless receiver’s resilience to interference signals is the addition of a blocker signal.  In this scenario, a single tone or series of tones are generated at frequencies close to the signal of interest.  Because a blocker can influence symbol recovery when demodulating a communications signal, it is important to test for this characteristic.

One way that we can illustrate the affects of interference signals is by adding a multi-tone component to the signal of interest.  To visualize this affect, we simply apply multi-tone characteristics to a simulated communications system in LabVIEW.   This is shown in the figure below, which illustrates multiple tones adjacent to a modulated carrier.

Figure 4.  Multi-tone interference signals adjacent to a modulated carrier.

Again, we can also visualize the affect of multi-tone interference with a constellation plot.  As the plot below illustrates, interference tones close to the signal of interest result in slight variations in the phase and amplitude of the recovered symbols.

 

 

Figure 5. Constellation plot of a 4-QAM signal with simulated multi-tone interference.

Because interference close to the band of interest can affect demodulation of the communications signal, it is important to characterize a wireless receiver’s performance in this environment.  Again, while simulated models for interference can provide rough prediction of the receiver’s performance, these models are still not as accurate as the real-world signals.

RF Record and Playback for Wireless Receiver Test

The ideal solution to modeling the affects of a wireless environment is to use the real-world signal instead of just a model.  However, testing a wireless receiver in its final environment is expensive and often non-repeatable.  PXI RF record and playback systems offer an alternative to modeling challenges in the wireless environment by enabling test with real-world signals instead.  With this approach, an RF vector signal analyzer is set up in the target destination environment where it acquires RF signals in the spectrum of interest.  The signal is then “played back” in a laboratory environment with a vector signal generator as a test stimulus the wireless receiver.  The use of recorded RF signals allows for the introduction of natural impairments.  This produces a more accurate characterization of how the receiver will perform in its final environment.  A typical test set-up is shown below.

 

 

Figure 6. Block diagram of RF receiver test using stream-to-disk systems.

As the figure above illustrates, a single PXI system can be used for both RF continuous acquisition and generation.  Note that the mechanism for waveform storage in this system can be the hard drive onboard the PXI controller itself.  For even wider bandwidth acquisitions, RAID (redundant array of inexpensive disks) systems can be used as well.

Receiver Sensitivity Test

Because wireless devices operate in an environment where signal strength is constantly fluctuating, one of the most important characteristics of a wireless receiver is its sensitivity.  Wireless receivers, particularly mobile devices, must constantly adapt to changes in signal strength with automatic gain control.  In fact, an attenuator is responsible for amplifying or attenuating the incoming RF signal to ensure the mixer level remains as constant as possible.  To illustrate this, a simplified block diagram of a Low-IF wireless receiver is shown below.

 

 

Figure 7.  Block diagram of typical RF receiver

As figure 7 illustrates, the level of attenuation applied to an RF signal directly affects the mixer level of the receiver.  In this scenario, the effective dynamic range of the receiver can be maximized when the mixer output remains relatively constant.  If it were not for the attenuation stage, high signal strength could cause clipping in the ADC.  On the other hand, without appropriate gain, low signal strength conditions would limit the usable dynamic range of the ADC.

In the past, wireless receiver validation and verification required engineers to simulate many of the characteristics of the physical environment in software.  In addition, it required field testing that was expensive and often non-repeatable.  However, with PXI RF record and playback systems, tests such as receiver sensitivity can be done with greater simplicity and accuracy.  Using recorded RF environment signals as a test stimulus, repeatable measurements can me made through various iterations of receiver prototypes.

From the examples above, we know that the imperfections of wireless systems can often be modeled mathematically.  However, models are only representations of the real world and are often insufficient when providing an accurate picture of a real-world RF environment.  For the best estimation of how a receiver will perform in its final environment, real-world data is required

Technology of RF Stream to Disk Systems

The ability to stream signals to disk with PXI instruments is only possible through the use of several technologies.  One of these is the use of a multi-threaded programming language such as LabVIEW.  This software enables PXI instruments to transfer data two and from an external hard disk (shown below) at rates that exceed the rate of acquisition.  For example, continuous acquisition of 20 MHz of RF bandwidth requires sustained data throughput of 100 MB/s.

 

 

Figure 8. PXI system with external RAID hard drive configuration.

While driver software optimizes throughput using direct memory access (DMA), transferring data from an instrument to a hard disk still poses a significant challenge.  Thus, optimizing stream performance in RF of stream-to-disk applications requires both instrument I/O and disk I/O to be performed in parallel.  In LabVIEW, these operations can operate in multi-threaded fashion with the use of parallel loops.  The recommended programming approach is the producer-consumer loop structure, which is shown in the figure below.

 

 

Figure 9. Producer-consumer loop architecture using the queue structure

In the example above, the top loop (producer) acquires baseband data from a vector signal analyzer and passes it to a queue structure (a LabVIEW FIFO).  The queue structure is able to pass data between multiple loops in LabVIEW, enabling the bottom loop (consumer) to write the data to disk.  When using the queue structure, LabVIEW handles all of the memory access to ensure that read-write race conditions do not occur.  The execution of a queue structure can be visualized with the diagram below:

 
Figure 10.  Data-Flow Programming Model of Queue Structure

As data is acquired from the vector signal analyzer, it is placed into memory in a first-in-first-out (FIFO) buffer using the “enqueue element” LabVIEW function.  The “dequeue element” function accesses the same FIFO, pulling it off each record in the order in which they were added to the queue.   

It is important to note that the use of parallel programming practices in stream-to-disk applications benefits greatly from an inherently multi-threaded programming language.  Moreover, stream-to-disk applications are able to achieve even better performance when running on multi-core processors.  Because multi-core processors divide processor threads between various cores, parallel code is able to execute more efficiently.  Thus, LabVIEW’s inherent multi-threading capabilities are a fundamental technology that enables PXI RF stream-to-disk systems to generate and acquire up to 20 MHz of signal bandwidth continuously for up to several hours.  The implementation of multi-threaded execution in LabVIEW is one of many technologies that make RF stream-to-disk systems possible.  For more information on how technologies such as onboard signal processing (OSP), the PXI Express data bus, and RAID systems enable high throughput stream-to-disk, please see: From RF to RAID:  Enabling Technologies of RF Stream-to-Disk Systems.

Conclusion

Wireless channels provide inherent challenges to communications systems.  As a result, receiver validation and verification requires today’s design and test engineers to model or otherwise account for various conditions.  Historically, various characteristics of the wireless environment were modeled mathematically with impairments such as Raleigh fading and multi-carrier interference.  Today, however, RF stream-to-disk systems provide an alternative approach to creating “perfect simulation.”  Using recorded real-world RF signal bandwidth, validation and verification of wireless receivers can be performed with greater accuracy and repeatability.

Other Resources:

 

• Whitepaper: From RF to RAID:  Enabling Technologies of RF Stream-to-Disk Systems.
• Whitepaper: The “Perfect Simulation” for Wireless Receiver Test 
• Customer Solution: PXI-Based RF Record/Playback System
• Customer Solution: Using NI PXI for Improved Spectral Monitoring in China
• www.ni.com/streaming
• www.ni.com/rf
• www.ni.com/modularinstruments/express

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