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Three Tips to Optimize WLAN Test Systems

Tue, 06/29/2010 - 11:14am
David A. Hall, National Instruments, RF & Wireless Test Product Manager
David_HallWith increasing pressure to lower test costs, many RF test engineers face the challenge of reducing measurement time. As you might expect, wireless LAN (WLAN) device testing is no exception. Whether you are creating an automated test system for design validation or final production test, it has become increasingly important to optimize a test system for measurement speed. Here, we provide three tips that you should consider to reduce measurement time of WLAN devices, including:

1) Measure error vector magnitude (EVM) over only part of a burst
2) Use composite measurements
3) Use the fastest CPU available

In this discussion, all WLAN measurements were configured using a software-defined test system based on PXI modular instrumentation and the NI WLAN Measurement Suite, which contains both generation and analysis toolkits for NI LabVIEW and LabWindows/CVI software.

Tip 1: EVM over Full versus Partial Burst
One method to perform faster EVM measurements is to calculate the measurement over a partial burst rather than over an entire burst. By default, many instruments calculate an 802.11a/g/n EVM measurement as the root-mean-square (RMS) of all sub-carriers over each symbol in the entire burst. However, in some cases, you can reduce measurement time by specifying that an EVM measurement be performed over only a portion of the burst. We can observe this trade-off in Figure 1, which illustrates the relationship between the numbers of symbols used to compute the measurement and the measurement time for an 802.11a/g BPSK (6 Mb/s) burst. 

Figure 1. Measurement time can be decreased by analyzing only a portion of a burst.

As seen in Figure 1, you can significantly reduce measurement time simply by analyzing a portion of the burst instead of every symbol. Note that analyzing only a portion of the burst produces a slight trade-off of measurement repeatability.

Tip 2: Use Composite Measurements
A second strategy to reduce WLAN measurement time is to perform composite measurements on a single IQ data set instead of configuring each measurement sequentially. With composite measurements, you can obtain results for multiple measurements with a single composite measurement. Because composite measurements calculate multiple measurement results on a single burst, it is more efficient than performing each measurement sequentially. In a composite measurement, only a single IQ data capture is necessary, resulting in faster measurement time. Table 1 illustrates the measurement speed reduction of simply performing a transmit power (TxP) and EVM measurement on the same IQ data set, rather than sequentially. 

Table 1. Measurement time of composite versus single measurements for 802.11g and 802.11n

From Table 1, we can calculate that for an 11 CCK burst, an EVM, TxP, and a ramp-up/ramp-down measurement would take 126 ms when performed sequentially, but only 64 ms when performed in parallel.

Tip 3: Use the Fastest CPU Available
A final method to reduce the measurement time of WLAN signals is to use the fastest CPU available. The CPU is one of the most important components of a software-defined PXI measurement system. CPU performance is often the single most significant factor gating faster measurement performance, especially for RF measurements. Fortunately, modern multicore CPUs can be used in conjunction with the highly parallel measurement algorithms of the NI LabVIEW WLAN Analysis Toolkit to deliver extremely fast measurement results.

While actual system performance can depend on a variety of factors such as memory available and other applications running in the background, a strong correlation exists between the CPU performance and measurement time for automated test systems. 

Table 2. Key specifications of various PXI Express controllers

Several CPU characteristics can affect overall measurement speed. Some of the most significant of these include the number of processing cores, CPU clock speed, front side bus, L2 cache size, and system memory. We can observe these effects by benchmarking 802.11g measurement times in Figure 2. In this figure, we compare the measurement time for various PXI embedded controllers over a variety of burst types. Note that each burst contains a payload of 1024 bits – and that lower data rate bursts are longer in duration. 

Figure 2. Measurement time versus burst type for various PXI embedded controllers

In Figure 2, note that the most capable CPU (the NI PXIe-8108 embedded controller) is able to perform a 64-QAM (54 Mbps) EVM measurement in exactly 7.65 ms. In addition, the same controller is able to measure all burst types faster than the other three comparison CPUs. These results suggest that a CPU has a significant effect on measurement time. Thus, using the fastest CPU available is a simple way to reduce measurement time without compromising measurement quality.

Conclusion
A variety of factors can affect the overall measurement time of Wireless LAN signals. While you can adjust many measurement settings to improve measurement time, these settings occasionally require you to make repeatability, accuracy, or completeness trade-offs. Thus, the easiest way to improve test throughput without sacrificing measurement quality is to always use the fastest CPU available.

For more information on how to configure PXI WLAN test systems, read Configuring Software-Defined WLAN Test Systems, http://zone.ni.com/devzone/cda/tut/p/id/8551

For more information on reducing measurement time, see Optimizing WLAN Test Systems for Measurement Speed, http://zone.ni.com/devzone/cda/tut/p/id/8552
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