EVM Measurements: Subcarrier vs. Symbol Analysis

This article explores the concept of Error Vector Magnitude (EVM) and its application in analyzing signal quality, particularly within OFDM-based systems like WLAN/WiMAX. We’ll delve into how EVM is measured against both individual subcarriers and complete symbols, highlighting the differences and insights each approach provides.

What is EVM?

EVM, short for Error Vector Magnitude, is a crucial metric for assessing the quality of a modulated signal. Sometimes referred to as Relative Constellation Error (RCE), it quantifies the difference between the ideal and actual positions of received symbols on the constellation diagram (IQ diagram). In simpler terms, it tells us how much the received signal deviates from what it should ideally be. EVM is typically expressed as an RMS (root mean square) value.

Figure 1: EVM measurement

EVM measurement plays a vital role in evaluating modem performance under various impairments, such as:

• Local Oscillator Stability
• Filter compression
• DAC/ADC imperfections
• Symbol rate variations
• Interfering signals

Moreover, the high Peak-to-Average Power Ratio (PAPR) often seen in OFDM systems demands highly linear Power Amplifiers (PAs). EVM measurements help verify this linearity and overall system efficiency.

Figure 2: EVM formula

OFDM and Subcarriers

Let’s consider a typical WLAN system. An OFDM symbol often consists of 64 subcarriers, divided into:

• 48 data subcarriers
• 4 pilot subcarriers
• 1 DC subcarrier
• 6 left guard subcarriers
• 5 right guard subcarriers

Imagine a frame containing 20 such symbols spanning 10ms with a 20MHz bandwidth. This provides the context for understanding how we can analyze EVM.

EVM vs. Subcarrier: Error Vector Spectrum

Measuring EVM against individual subcarriers provides us with an Error Vector Spectrum.

Figure 3: EVM vs subcarrier

As seen in Figure 3, the X-axis represents the subcarriers, and the Y-axis plots the corresponding EVM values. In this example, we have 52 utilized subcarriers plotted on the X-axis with their respective EVM values on the Y-axis. This visualization allows us to identify specific subcarriers that might be experiencing higher error rates.

EVM vs. Symbol: Error Vector Time

Now, let’s consider measuring EVM against the symbols. This gives us an Error Vector Time plot.

Figure 4: EVM vs symbol

In Figure 4, the X-axis represents the symbols (e.g., 20 symbols in this case), and the Y-axis shows the EVM values. Note that for each symbol, we have 52 subcarriers, giving us a total of 1040 data points in this plot. The figure illustrates the EVM measurement for all subcarriers within symbol number 5.

The aggregate (RMS) EVM value for one OFDM symbol is derived by individually calculating the EVM of each of its 52 subcarriers and then applying the provided EVM formula.

Key Differences

In essence:

• EVM vs. subcarrier (Error Vector Spectrum): Shows how EVM varies across different frequency components (subcarriers) within a signal. This is helpful for identifying frequency-specific impairments.
• EVM vs. symbol (Error Vector Time): Shows how EVM changes over time for different symbols within a frame or transmission. This is helpful for identifying time-varying impairments.

Both EVM vs. subcarrier and EVM vs. symbol measurements offer unique perspectives on signal quality and allow for a deeper understanding of system performance. By combining both methods, engineers can effectively diagnose and mitigate issues in their communication systems.