ANEKA INFO TEKNIK: DIGITAL MODULATION ; MEASUREMENT ON DIGITAL RF COMMINICATION SYSTEMS

8. Measurements on digital RF communications systems

Complex tradeoffs in frequency, phase, timing, and modulation are made for interference-free, multiple-user communications systems. It is necessary to accurately measure parameters in digital RF communications
systems to make the right tradeoffs. Measurements include analyzing the modulator and demodulator, characterizing the transmitted signal quality, locating causes of high Bit-Error-Rate and investigating new modulation types. Measurements on digital RF communications systems generally fall into four categories: power, frequency, timing, and modulation accuracy.
8.1 Power measurements
Power measurements include carrier power and associated measurements of gain of amplifiers and insertion loss of filters and attenuators. Signals used in digital modulation are noise-like. Band-power measurements
(power integrated over a certain band of frequencies) or power spectral density (PSD) measurements are often made. PSD measurements normalize power to a certain bandwidth, usually 1 Hz.

Figure 35. Power Measurement

8.1.1 Adjacent channel power
Adjacent channel power is a measure of interference created by one user that effects other users in nearby channels. This test quantifies the energy of a digitally-modulated RF signal that spills from the intended
communication channel into an adjacent channel. The measurement result is the ratio (in dB) of the power measured in the adjacent channel to the total transmitted power. A similar measurement is alternate channel
power which looks at the same ratio two channels away from the intended communication channel.

Figure 36. Power and Timing Measurements

For pulsed systems (such as TDMA), power measurements have a time component and may have a frequency component, also. Burst power profile (power versus time) or turn-on and turn-off times may be measured.
Another measurement is average power when the carrier is on or averaged over many on/off cycles.
8.2 Frequency measurements
Frequency measurements are often more complex in digital systems since factors other than pure tones must be considered. Occupied bandwidth is an important measurement. It ensures that operators are staying within the bandwidth that they have been allocated. Adjacent channel power is also used to detect the effects one user has on other users in nearby channels

Figure 37. Frequency Measurements

8.2.1 Occupied bandwidth
Occupied bandwidth (BW) is a measure of how much frequency spectrum is covered by the signal in question. The units are in Hz, and measurement of occupied BW generally implies a power percentage or ratio. Typically, a portion of the total power in a signal to be measured is specified.
A common percentage used is 99%. A measurement of power versus frequency (such as integrated band power) is used to add up the power to reach the specified percentage. For example, one would say “99% of the power in this signal is contained in a bandwidth of 30 kHz.” One could also say “The occupied bandwidth of this signal is 30 kHz” if the desired power ratio of 99% was known.
Typical occupied bandwidth numbers vary widely, depending on symbol rate and filtering. The figure is about 30 kHz for the NADC π/4 DQPSK signal and about 350 kHz for a GSM 0.3 GMSK signal. For digital video signals occupied bandwidth is typically 6 to 8 MHz.
Simple frequency-counter-measurement techniques are often not accurate or sufficient to measure center frequency. A carrier “centroid” can be calculated which is the center of the distribution of frequency versus PSD for a modulated signal.

8.3 Timing measurements
Timing measurements are made most often in pulsed or burst systems.
Measurements include pulse repetition intervals, on-time, off-time, duty cycle, and time between bit errors. Turn-on and turn-off times also involve power measurements.
8.4 Modulation accuracy
Modulation accuracy measurements involve measuring how close either the constellation states or the signal trajectory is relative to a reference (ideal) signal trajectory. The received signal is demodulated and compared with a reference signal. The main signal is subtracted and what is left is the difference or residual. Modulation accuracy is a residual measurement.
Modulation accuracy measurements usually involve precision demodulation of a signal and comparison of this demodulated signal with a (mathematically-generated) ideal or “reference” signal. The difference between the two is the modulation error, and it can be expressed in a variety of ways including Error Vector Magnitude (EVM), magnitude error, phase error, I-error and Q-error. The reference signal is subtracted from the demodulated signal, leaving a residual error signal. Residual measurements such as this are very powerful for troubleshooting. Once the reference signal has been subtracted, it is easier to see small errors that may have been swamped or obscured by the modulation itself. The error signal itself can be examined in many ways; in the time domain or (since it is a vector quantity) in terms of its I/Q or magnitude/phase components.
A frequency transformation can also be performed and the spectral composition of the error signal alone can be viewed.

8.5 Understanding Error Vector Magnitude
Recall first the basics of vector modulation: Digital bits are transferred onto an RF carrier by varying the carrier’s magnitude and phase. At each symbol-clock transition, the carrier occupies any one of several unique locations on the I versus Q plane. Each location encodes a specific data symbol, which consists of one or more data bits. A constellation diagram shows the valid locations (i.e., the magnitude and phase relative to the carrier) for all permitted symbols of which there must be 2ⁿ, given n bits transmitted per symbol. To demodulate the incoming data, the exact magnitude and phase of the received signal for each clock transition must be accurately determined.
The layout of the constellation diagram and its ideal symbol locations is determined generically by the modulation format chosen (BPSK, 16QAM, π/4 4 DQPSK, etc.). The trajectory taken by the signal from one symbol location to another is a function of the specific system implementation, but is readily calculated nonetheless.
At any moment, the signal’s magnitude and phase can be measured.
These values define the actual or “measured” phasor. At the same time, a corresponding ideal or “reference” phasor can be calculated, given knowledge of the transmitted data stream, the symbol-clock timing, baseband filtering parameters, etc. The differences between these two phasors form the basis for the EVM measurements.

Figure 38 defines EVM and several related terms. As shown, EVM is the scalar distance between the two phasor end points, i.e. it is the magnitude of the difference vector. Expressed another way, it is the residual noise and distortion remaining after an ideal version of the signal has been stripped away.

Figure 38. EVM and Related Quantities

In the NADC-TDMA (IS-54) standard, EVM is defined as a percentage of the signal voltage at the symbols. In the ¹/4 DQPSK modulation format, these symbols all have the same voltage level, though this is not true of all formats. IS-54 is currently the only standard that explicitly defines EVM, so EVM could be defined differently for other modulation formats.
In a format such as 64QAM, for example, the symbols represent a variety of voltage levels. EVM could be defined by the average voltage level of all the symbols (a value close to the average signal level) or by the voltage of the outermost (highest voltage) four symbols. While the error vector has a phase value associated with it, this angle generally turns out to be random because it is a function of both the error itself (which may or may not be random) and the position of the data symbol on the constellation (which, for all practical purposes, is random). A more useful angle is measured between the actual and ideal phasors (I/Q phase error), which contains information useful in troubleshooting signal problems. Likewise, I-Q magnitude error shows the magnitude difference between the actual and ideal signals. EVM, as specified in the standard, is the root-mean-square (RMS) value of the error values at the instant of the symbol-clock transition. Trajectory errors between symbols are ignored.
8.6 Troubleshooting with error vector measurements Measurements of error vector magnitude and related quantities can, when properly applied, provide much insight into the quality of a digitally modulated signal. They can also pinpoint the causes for any problems uncovered by identifying exactly the type of degradation present in a signal and even help identify their sources. For more detail on using error-vector-magnitude measurements to analyze and troubleshoot vector-modulated signals, see product note 89400-14. The Hewlett-Packard literature number is 5965-2898E.

EVM measurements are growing rapidly in acceptance, having already been written into such important system standards as NADC and PHS, and they are poised to appear in several upcoming standards including those for digital video transmission.
8.7 Magnitude versus phase error
Different error mechanisms affect signals in different ways: in magnitude only, phase only, or both simultaneously. Knowing the relative amounts of each type of error can quickly confirm or rule out certain types of problems.
Thus, the first diagnostic step is to resolve EVM into its magnitude and phase error components (see figure 38) and compare their relative sizes.
When the average phase error (in degrees) is substantially larger than the average magnitude error (in percent), some sort of unwanted phase modulation is the dominant error mode. This could be caused by
noise, spurious or cross-coupling problems in the frequency reference, phase-locked loops, or other frequency-generating stages. Residual AM is evidenced by magnitude errors that are significantly larger than the phase angle errors.
8.8 I/Q phase error versus time
Phase error is the instantaneous angle difference between the measured signal and the ideal reference signal. When viewed as a function of time (or symbol), it shows the modulating waveform of any residual or interfering PM signal. Sinewaves or other regular waveforms indicate an interfering signal. Uniform noise is a sign of some form of phase noise (random jitter, residual PM/FM, etc.).

Figure 39. Incidental (inband) PM sinewave is clearly visible even at only three degrees peak-to-peak.

A perfect signal will have a uniform constellation that is perfectly symmetric about the origin. I/Q imbalance is indicated when the constellation is not “square”, i.e. when the Q-axis height does not equal the I-axis width.
Quadrature error is seen in any “tilt” to the constellation. Quadrature error is caused when the phase relationship between the I and Q vectors is not exactly 90 degrees.

Figure 40. Phase noise appears random in the time domain.

8.9 Error Vector Magnitude versus time
EVM is the difference between the input signal and the internally-generated ideal reference. When viewed as a function of symbol or time, errors may be correlated to specific points on the input waveform, such as peaks or zero crossings. EVM is a scalar (magnitude-only) value. Error peaks occurring with signal peaks indicate compression or clipping. Error peaks that correlate to signal minima suggest zero-crossing nonlinearities

Figure 41. EVM peaks on this signal (upper trace) occur every time the signal magnitude (lower trace) approaches zero. This is probably a zero-crossing error in an amplification stage.

An example of zero-crossing nonlinearities is in a push-pull amplifier, where the positive and negative halves of the signal are handled by separate transistors. It can be quite a challenge (especially in high-power
amplifiers) to precisely bias and stabilize the amplifiers such that one set is turning off exactly as the other set is turning on, with no discontinuities.
The critical moment is zero crossing, a well-known effect in analog design.
It is also known as zero-crossing errors, distortion, or nonlinearities.

8.10 Error spectrum (EVM versus frequency)
The error spectrum is calculated from the Fast Fourier Transform (FFT) of the EVM waveform and results in a frequency-domain display that can show details not visible in the time domain. In most digital systems,
nonuniform noise distribution or discrete signal peaks indicate the presence of externally-coupled interference.