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Industry News

Add Realism to Your Test Signals with RF Channel Simulators

March 9, 2010
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All radio frequency (RF) links are subject to distortion due to the physics of the transmission media, as well as the physical environment in which the link is operating. While designers take these effects into account when developing communication systems, actual testing with these distortions realistically applied to the system under test can be problematic and costly, unless RF channel simulation is utilized.

Margin testing of a transmitter/receiver pair can occur throughout the design phase. Typically, this is done with signal generators substituting for the transmitter portion of the design and spectrum analyzers or vector signal analyzers acting as receivers. However, even with the most sophisticated equipment, this testing is typically performed in static conditions, possibly stressing a few worst, best cases, and nominal operating conditions. For many communication system designs, especially those where one or both of the ends of the communication path are in motion, maintaining realistic RF test conditions offers unique challenges. Static testing can miss communication issues related to the way the signals are impacted by the actual operating environment.

This article discusses how a new category of test tools, called channel simulators, are used in the laboratory and QA areas to create RF signals that match those that occur when communication systems are deployed on platforms in motion. Sometimes channel simulators will be referred to as link emulators, channel emulators or link simulators, depending on region and specific application. Channel simulators provide engineers with an effective and economical way of verifying and optimizing the operation and quality of communication devices, where one or more nodes are in motion.

Channel simulators do exactly what the name implies; they emulate the distortions on an RF signal when receivers and transmitters move with respect to one another. The reasoning behind utilizing a channel simulator in this case is that there are no simple alternatives. The engineering team could finish their design and place the communication system on an aircraft or satellite, thereby putting it into motion and creating realistic conditions. However, the risks of this approach can be disastrous and almost certainly costly. Consider the condition where the link is used for control of the moving platform. It is easy to see where realistic emulation in a controlled environment is a preferred approach, over a possible loss of the communication link and therefore control of the platform. A channel simulator can be utilized throughout the design phase to realistically impair signals, just as if they were in their intended operating environment, whether that environment relates to a drone flying overhead or a mission to the edge of the solar system.

Some may remember the Cassini-Huygens potentially mission-ending communications issues during its undertaking to gather data on Saturn’s moon, Titan. The issues were related to the Doppler shift impacts on the communications link, which left uncorrected would have corrupted data received from Huygens as it descended to Titan’s surface. The issue was uncovered only after the spacecraft had been launched, making a solution difficult to apply. In the end, the orbital plan of Cassini was altered in order to hold the Doppler shift in the communication channel from the Huygens craft within restricted parameters, thereby preserving most of the mission’s goals.

These environmental effects have historically been difficult to simulate in a laboratory, especially in an electrically realistic and physics-compliant way. The channel simulator was created to address exactly this issue. When the channel simulator is placed into the communication link of the system under test, it “passes” (RF or cable connections at RF/IF) the signal from the transmitter on to the receiver, adding impairments that match link conditions that exist in the actual operational environment. This allows every part of the device under test including antennas, amplifiers, converters, transponders, modems, demodulators, and even data recovery and firmware to be tested under realistic RF signal conditions.

Programming of the environmental conditions can be accomplished in multiple ways, from simple point-by-point input of variables to sophisticated modeling of terrain, velocity, antenna locations, interference, weather and background noise to name a few. When this latter methodology is used, the resulting signals can be so realistic that operators would find them indistinguishable from the actual in-motion test. This level of sophistication and realism is achieved by coupling sophisticated motion, terrain, and link budget modeling software to a channel simulator allowing it to add environmental effects to the input signals, as determined by the simulation. The result is a realistic test signal appropriate for detailed parametric transmit- and receive-chain testing. Another aspect of this realistic test signal is that it can also be used for training operators of the equipment being tested.

Figure 1 Aircraft flight modeled at T=0 on Analytical Graphics Inc. STK SW.

Figure 1 is an example of an actual flight plan programmed into a modeling software. The simulation can include data such as the aircraft flight characteristics and path, along with the terrestrial features, antenna parameters, link budget parameters, and even antenna placements on the aircraft and ground. This information is then translated into a continuous stream of control parameters, which allows the channel simulator to mimic the RF perturbations encountered continuously throughout the flight. For example, if this were the first flight of an experimental aircraft, for which the communication link in question would relay all operating parameters of the first flight, the flight could be flown virtually over and over before any aircraft or personnel were put at risk. By utilizing the actual communication equipment, along with a channel simulator creating realistic waveform impairments, the system can be optimized, insuring reliable communication throughout the actual maiden flight.

The yellow line in the figure represents the communication link between the aircraft and the receiving antenna. As the aircraft proceeds around the flight path (shown in green), the running scenario passes the appropriate programming variables to the channel simulator. The channel simulator in turn adds exact RF perturbations to the signal as the physics of the motion would impart in an actual flight. Some of the communication link variables being modified at the instant the figure was captured include: Doppler (aircraft moving away from the receiving antenna); delay (time for signal to travel the distance between aircraft and receiving antenna); power levels (influenced by distance); and line-of-sight connectivity (terrain and antenna placement on the aircraft are affecting transmission). Other variables to add realism can be included in this scenario, such as radio transmissions, modulation type, data rate, signal-to-noise ratios and radar signals to name a few. It is also important to point out that this can be done with full motion simulation in real-time, accelerated time, or slowed time, not just as a static test. If, for example, the tracking station on the ground was using the time delay of the communication path as a backup measurement of distance from the receiver, the delay imparted by the channel simulator would mimic the delay, even though the test may be running in the lab.

Channel Simulator Block Diagram

One might wonder at this point how a channel simulator creates this realistic environment. Figure 2 shows a simplified block diagram. The signal is typically down-converted (not shown) to an IF that is digitized by an ADC, processed through an FPGA with DSP capability, returned to IF with a DAC, and finally up-converted (not shown) back to RF. The key is that the channel simulator must have a real-time RF path, which can then also apply physics-compliant impairments to the signals under test. The end results are test signals that accurately match the real signals when exposed to the actual link environment. A variety of effects outside of the physics-related channel distortions can also be added via signal sources, for example, an intentional or unintentional jamming signal overlapping the link.

Figure 2 Channel simulator block diagram.

Let us now use the example flight plan discussed previously, to highlight the details of how signals are modified due to the physics of a communication system in motion. In this example, the aircraft is in motion with respect to the ground station, creating a Doppler shift. This effect must be considered in order to ensure that the receiver remains locked to the signal while maintaining proper BER performance, even as the received signal’s frequency shifts over time due to the relative motion of the transmitter and the receiver. Equation 1 describes the Doppler shift, based on the actual transmitted frequency and the relative velocity between the transmitter and the receiver.

The graphical data shown in Figure 3 is calculated using Equation 1. The relative velocity of the aircraft, along with the actual transmitted carrier frequency, serve as input data. This allows the Doppler shift to be graphed at any point along the flight path. You can see the result of the Doppler shift on a 2.4 GHz signal. As the aircraft moves towards the fixed receiving station, the received signal is at a higher frequency than is actually being transmitted. When the aircraft is moving away, the received signal frequency is lower than the transmitted frequency.

Figure 3 Doppler shift vs. time for a 2.4 GHz signal observed at the ground station.

For this aircraft and flight path, the following Doppler shift ranges observed at a fixed ground station are shown in Table 1. Similar data can be constructed for other frequencies, as well as for a number of potential platforms in motion including Middle Earth Orbit (MEO), High Earth Orbit (HEO), and Geostationary Earth Orbit (GEO) satellites, UAVs, and missiles.

On a laboratory bench, a channel simulator used in the configuration shown in Figure 4 can apply the anticipated Doppler shift to the input signal, so that the signal into the receiver system under test is identical to what would actually be received from the transmitter.

Figure 4 Channel simulator configuration for receiver system testing.

Figure 5 shows a similar setup for transmitter system testing. In either test setup, receivers or transmitters under test may be used for flying or ground-based applications. As well, up-converters, down-converters and modems may be necessary in an actual test setup, depending on available equipment and receiver and transmitter characteristics.

Figure 5 Channel simulator configuration for transmitter testing.

Note that these setups allow testing of all receive-chain components, such as antennas, amplifiers, modulators, encryptors, demodulators, decoders, decryptors, bit syncs, etc., because the input signal is completely realistic. Signal connections into and out of channel simulators can be over cables, near-field RF, or long distance RF.

As Equation 1 describes, the Doppler shift is frequency dependent. Since data signals have non-zero bandwidth, various portions of the signal are actually at different frequencies as can be observed with the 120 kbit/sec QPSK signal shown in Figure 6. For precise simulation, the Doppler shift capacity of the channel simulator must apply appropriate and different Doppler shifts across its bandwidth. In Figure 6, for example, the left side of the waveform would receive a slightly lower Doppler shift than the right side, since the left side is at a lower frequency than the right side. This is especially important at high data rates that result in wide bandwidth data signals.

Figure 6 Typical 60 kHz bandwidth of a 120 kbit/sec (60 kSymbols/sec) QPSK signal.

Referring back to Figure 3, it also shows that the Doppler shift rate changes throughout the flight. The flatter, more horizontal areas of the plot are where the Doppler shift remains relatively constant due to comparatively small changes in the closing velocity between the aircraft and the ground station. The steeper portion of the curve is where the aircraft’s range from the ground station is changing more rapidly; as the plot crosses the X axis, the velocity changes sign from positive values (aircraft approaching receiver) to negative values (aircraft moving away from receiver). Channel simulators, configured as those shown previously, must apply Doppler shift rates both within and beyond the anticipated ranges for verification of appropriate receiver system margin.


All communication systems have some form of inherent delay in propagation between transmitter and receiver. This is true for wire-line systems, optical systems and wireless radio systems, where propagation velocity is related to the dielectric constant of the medium through which the signal passes. Propagation velocity is expressed as a percentage of the speed of light, and in vacuums (dielectric constant = 1) and in air (dielectric constant = 1.00054), propagation velocity can be considered to be 100 percent of the speed of light for most practical purposes.

Therefore, in most wireless communication systems the propagation delay between a transmitter and receiver can be very closely approximated by dividing the straight line distance between the transmitter and the receiver, by the speed of light.

Figure 7 Range delays vs. time for a signal from nearly elliptical flight seen at a ground station.

For the specific flight path discussed earlier, the range delay profile of Figure 7 can be expected. Modeling different types of moving platforms and flight paths will produce dramatically different results. When performing one-way tests, where a receiver or transmitter is being tested, the channel simulator must be capable of signal delay ranges dictated by both the closest and farthest expected separation between transmitter and receiver, plus margin. Complete simulations of relay communications scenarios require that the channel simulator be capable of delaying for the full communication path, both to and from the transmitter/receiver.

For the flight plan illustrated previously, a channel simulator would need a delay capacity of at least 40 µs as given in Equation 2, as well as any other transmitter/receiver delays, plus margin for worst-case system analysis.

Communications systems testing between satellites, space vehicles and ground stations follow the same considerations, except that maximum delays are much larger due to the longer distances between transmitters and receivers.

Path Losses

Receiver system performance also depends on the power level of the received signal. A variety of factors can affect the power levels in the flight example, including terrain, antenna location, weather conditions and orientation. Modeling dynamic signal power levels and validating operation under worst-case conditions are key receiver system tests.

The power level of a received signal is affected by free-space path loss, which can be calculated from Equation 3.

A channel simulator must accept a low-level input signal, then further attenuate it according to the attenuation profile of the communications system being tested. Properly simulating communication links to satellites requires much greater attenuation ranges. A LEO satellite requires a channel simulator relative attenuation capacity of 10 to 20 dB. Modeling MEO and HEO satellites having highly elliptical orbits, or where atmospheric, Rician, Rayleigh, or Nakagami fading is to be modeled, the needed relative attenuation range is more on the order of 50 dB.

Additive White Gaussian Noise (AWGN)

As with the Doppler, range delay and range attenuation parameters mentioned previously, all communications systems are subject to noise received by the antenna (cosmic noise and radiation from the Earth), as well as other atmospheric and man-made noise. Receiver noise itself is also an important factor. In order for channel simulators to be capable of creating signals truly identical to those that would be received from wireless transmitters, they must contain noise sources capable of generating expected and worst-case noise profiles.

Real-time (Continuous) Signal Pass Through

Channel simulators must perform their operations in a fully physics-compliant and phase-continuous manner. This ensures that throughout the instrument’s capabilities, no data errors are introduced as a result of waveform discontinuities, inappropriate transitions, or glitches. The channel simulator must faithfully model nature in this regard, so that the instrument can be confidently substituted into the communications system for accurate and dependable results. Among other key attributes, this implies sophisticated high-resolution interpolation between commanded Doppler, delay, or attenuation points.


While this article used the example of an aircraft circling a ground communication site, the principles and concepts discussed apply similarly to transmitters and receivers that are in motion relative to each other. The understanding of how the environment will modify electrical signals, along with utilization of revolutionary test equipment like the channel simulator, ensure that the system that works on the bench, will also work in motion. In conclusion, while testing of communication systems is a long-standing, well-honed art, the advent of the channel simulator provides engineers with a unique and important test capability that further ensures functionality when it absolutely counts.

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