Software Defined Radio (SDR) represents an important move forward for mobile and personal communications, promising a major increase in flexibility, capability, and cost efficiency. It utilizes a combination of field-programmable gate arrays (FPGAs), digital signal processors (DSPs), and analog/RF designs to achieve the radio’s system performance. The SDR’s core functionality can be changed by modifying the software and firmware instead of the hardware. Because of this flexibility, the radio isn’t limited to just one transmission scheme or waveform. Rather, it can be reconfigured to support new waveforms or to operate as a different type of radio altogether. For a true SDR, the waveform stands on its own, and waveforms can even be ported to different hardware platforms.

Figure 1. The ability to compare measurement results using common measurement software at different locations in the radio helps isolate the source of errors.

All of this flexibility comes at a price. SDR designs require greater integration of DSP/digital and RF functions and a wider range of tests, which in turn gives rise to a number of mixed-signal test challenges. Consequently, ensuring successful operation and proliferation of today’s SDR designs requires use of modern instruments capable of bridging the digital-analog divide, while also addressing any challenges stemming from use of the SDR technology itself.

Warning: Challenges Ahead

By their very nature, SDR designs are mixed-signal (signals in both analog and digital form within the radio), so testing complexities will arise when the baseband hardware and RF hardware are integrated together. This complexity stems from the impact of impairments on the SDR’s overall system performance, which makes issues difficult to isolate during system integration testing.

Many factors can contribute to error along the mixed-signal transmitter chain and in turn, affect waveform quality and the SDR’s overall error vector magnitude (EVM) performance. EVM is a measure of waveform quality and is typically used as a metric for wireless transmitter performance. For example, the D/A converter may introduce nonlinearities and the D/A converter clock may introduce jitter. Additionally, local oscillator (LO) phase noise, IF/RF filters, and nonlinear gain/phase distortion from the IF/RF up-converter and power amplifier may introduce waveform distortion to the SDR’s EVM performance.

Figure 2. The left, center, and right screen shots show the EVM and constellation measurement of a QPSK radio at IF (EVM = 12.5%), analog IQ (EVM = 6.4%), and digital IQ (EVM = 4.2%), respectively.

Multiple-input multiple-output (MIMO) technologies further add to the complexity associated with testing and debugging mixed-signal SDR designs. SDR orthogonal frequency division multiple access (OFDMA) technologies often employ MIMO as a way to increase data rates relative to single-input single-output (SISO) approaches. However, MIMO technology is highly complex with its spatial multiplexing algorithms, multiple transmit/ receive IF/RF chains, and multiple antennas, and MIMO performance can be impacted by impairments such as timing errors and cross-coupling between the multiple channels.

The Solution: Software Defined Instruments

These challenges underscore the need for instrumentation capable of working across the digital and RF elements in the SDR design, and that allows for probing at every stage along the mixed-signal chain. This would enable engineers to gain insight into the incremental impairments introduced to the waveform at every stage of the mixed-signal SDR design and to perform system-level debugging. Probing at various stages within an FPGA implementation and debugging with the same signal analysis measurement software (and the same demodulation algorithms) used to measure the analog IQ, IF, and RF stages can provide an additional level of insight into issues occurring in the FPGA implementation itself.

Figure 3. SystemVue creates a waveform, in this case a custom OFDM waveform, which can operate in the test environment (simulation) or be downloaded into a signal generator to look at with a device under test, or analyzer to see how it performs and interoperates with any part of the block diagram.

Software defined instruments (SDIs) offer one means of delivering this functionality. Much like the SDR itself, modern SDIs are versatile and perform many functions by simply adding or changing software. Measurements traditionally done with hardware are now performed with software. The result is instrument measurement capability that is largely software-based with the flexibility needed for mixed-signal system- level testing. In some cases, the measurement software can even stand on its own and be leveraged across completely different measurement platforms such as logic analyzers, high-performance digital oscilloscopes, and RF signal analyzers. This provides powerful measurement functionality and seamless continuity for the system engineer in evaluating and debugging issues across the digital, analog, and RF sections of an SDR.

One example of an SDI is an RF signal analyzer that incorporates an all-digital IF section. In this instrument’s analog front end, the input signal is down converted to an IF and then digitized. From there, many of the analyzer’s modulation domain measurements are performed using vector signal analyzer measurement software. With the right software, the analyzer operates as a complete swept-tuned spectrum analyzer, but it can also operate as an FFT analyzer, modulation analyzer, or even a full-fledged vector signal analyzer. In contrast, a high-performance digital oscilloscope utilizes a different approach in digitizing the modulated RF waveform directly at sample rates up to 80 GSa/s. It then uses vector signal analyzer software functionality to change the sample rate and center frequency of the data, and then performs the modulation domain analysis.

Such flexibility does not suggest that RF signal analyzer and digital oscilloscope hardware, or any SDI hardware for that matter, is completely generic. Like the SDR, the SDI’s cost, functional, and performance constraints shape the hardware platform selection. In other words, SDIs are not without their practical boundaries and tradeoffs.

Changing Signal Formats

One of the key challenges that arises during SDR testing is changing signal formats for emerging waveforms. Conventional radio transmitters typically use a baseband IC that outputs an analog baseband signal. The signal modulates an IF, which is then up-converted to RF and amplified. Today though, more of the radio is being implemented in the digital realm, and it is becoming commonplace to work with digital representations of the signal (e.g., digital IQ or digital IF). These digital signals represent a digitized form of the modulated analog waveform and can be formatted in various ways such as parallel or serial, two’s complement or binary, or packetized in a form defined by one of the digital interface standards.

Test equipment venders have responded to these changing signal formats by providing digital interfaces to traditionally analog test tools. Today’s vector signal generators, for example, can be equipped with digital signal I/O capability. Based in part on an arbitrary waveform generator, they have the flexibility to recreate, with the right software, user-defined signals within their performance constraints. Further, impairments, such as noise or channel effects, can be modeled into the signal using software processing.

With this versatility, vector signal generators have the flexibility to provide test stimulus for a wide variety of emerging SDR waveforms. Moreover, they can output test signals at RF, IF, analog IQ, digital IF, or digital IQ. For the digital signal output, the generator can utilize a digital signal interface that is reconfigurable to various digital formats and clock rates. The flexibility of an SDI like the vector signal generator enables it to provide a consistent test stimulus to any part of the radio and to independently verify the performance of each component or section.

Flexible SDR Signal Analysis

Flexibility can also be found in SDIs used for SDR signal analysis. As an example, consider the 89600B VSA measurement software, which can operate on many different instrument platforms or analog and digital “front ends” (Figure 1). This flexible measurement tool supports many demodulation formats and measurements. It can run on an RF signal analyzer as well as on a high-performance digital oscilloscope or a logic analyzer. As a result, it provides insight for signals of any format including RF, IF, analog baseband, digital baseband, or digital IF.

A key benefit of being able to consistently measure signals anywhere within the radio with the same test tool is that it allows the engineer to directly compare the signal quality at different test points along a mixed-signal SDR transmitter chain. To better illustrate this point, consider the screenshots in Figure 2, which shows the EVM and constellation measurement of a QPSK radio in various formats using the VSA software running on the signal analyzer, oscilloscope, and logic analyzer. While this is a basic QPSK signal, the concept works for any supported modulation format including more complex OFDMA waveforms such as Mobile WiMAX™ and Long-Term Evolution (LTE), or even custom OFDM waveforms. In addition, MIMO demodulation measurements can be performed with the VSA software by selecting a hardware measurement platform such as a high-performance digital oscilloscope with four phase coherent inputs for two or four-channel MIMO measurements.

As shown in the measurement results in Figure 2, the waveform quality has degraded with an approximate 6% EVM difference between the analog IQ to IF, and approximately a 2% EVM difference between the digital IQ to analog IQ. A closer examination of the results using the 89600B’s detailed analysis functions reveals the cause of the errors. In this case, the majority of error between the IF and analog IQ is due to quadrature error introduced by the IQ modulator. The error introduced between the digital IQ and analog IQ signals is largely the result of dispersion introduced by analog filters located just after the DAC. The digital IQ signal’s 4% EVM is primarily due to the ripple in the passband of the digital filter implemented within the FPGA.

Connecting to the Real World

Figure 4. The ability of the 89600B VSA software to record, store, and play back signals in either the physical world or in simulation enables it to act as both a measurement tool and a source within the simulation, and as a result, designers can test their simulated system using real-world signals.

The versatility of the VSA software is not limited to multiple instrument platforms; it can also be operated within design simulation environments to provide a flexible connection to the real world. In the case of the 89600B VSA, for example, the software can operate within a software design environment such as Agilent’s SystemVue software for electronic system level (ESL) design.

SystemVue creates the radio signals that can be used to model and test Layer 1 PHY architectures, both in simulation as well as when downloaded into test equipment (Figure 3). It enables scenario modeling by adding fading, noise, interferers, and the RF effects necessary for realistic system analysis and early R&D verification. Once in the SystemVue platform, the signals can be used throughout the larger design flow and input into other EDA tools or even used for testing and integration.

The 89600B VSA software is then used to demodulate the signals and perform any associated analysis. By using the VSA software in simulation, the engineer is able to measure simulated signals with the same algorithms, user interface, and functionality that will eventually be used to test the hardware implementation of the simulated design (Figure 4). Moreover, because the software works seamlessly with spectrum analyzers, signal analyzers, oscilloscopes, logic analyzers, modular vector analyzers, and simulation software, signals can be evaluated during the design cycle, or at any point along the SDR mixed-signal hardware chain, including analog and digital baseband and IF, RF, and microwave. This can help the SDR system engineer mitigate potential integration risks and optimize tradeoffs that may arise from the distinctly different design and test methodologies used by the digital baseband and RF design teams.

Conclusion

The flexibility of today’s software defined instruments greatly improves SDR designer efficiency by providing the versatility necessary to use common measurement tools throughout the radio, as well as through all stages of development. Such versatility is critical to enabling the proliferation of emerging trends in modern radio designs, like the SDR, which utilize more digital signal processing and require greater functionality as well as more rapid development.

This article was written by Greg Jue, applications development engineer/scientist with Agilent’s High Performance Scopes team; and John Barfuss, field applications engineer for Agilent Technologies. For more information, Click Here .