Fading
Types of fading, diversity techniques, and mitigation strategies.
Introduction: The Ghost in the Wireless Machine
In our study of wireless propagation, we learned that propagation models can predict the average path loss, giving us an estimate of how much a signal weakens over a given distance. This provides a crucial baseline for network design. However, anyone who has used a cell phone or a Wi-Fi network has experienced a frustrating phenomenon that these average models do not fully capture: a signal that can be perfectly clear one moment and weak or completely gone the next, even without moving a great distance. This rapid, unpredictable fluctuation in signal strength is known as fading.
is arguably the single most challenging problem in wireless communication. It is the ghost in the machine, the primary reason for dropped calls, stuttering video streams, and slow internet speeds. It is caused by the complex ways in which radio waves interact with the environment. The signal does not just travel in one straight line; it bounces, bends, and scatters, arriving at the receiver via multiple paths. This multipath propagation causes the waves to interfere with one another, sometimes reinforcing the signal, but often canceling it out. The goal of this discussion is to peel back the layers of this complex topic, to understand the different types of fading, their causes, and most importantly, the brilliant engineering techniques developed to combat their effects and make modern wireless communication possible.
Interactive example: two-path interference
Use the controls to see how extra path length and reflection strength shift constructive and destructive combinations at the receiver.
Two-path fading explorer
Adjust the reflection strength and extra path to see how multipath interference reshapes the received field.
Curve shows field magnitude for one direct and one reflected path. Marker highlights the current setting.
Direct path is normalized to 1.0. Reflection strength scales the second path before combining the vectors.
The chart traces the instantaneous field versus path difference, while the diagram highlights how the direct and reflected components add in a simple two-path model.
Classifying Fading: Large-Scale vs. Small-Scale
Fading phenomena are broadly categorized based on the geographic scale over which they occur. This distinction is critical because the causes and characteristics of each type are different, and so are the methods used to mitigate them.
Large-Scale Fading (Shadowing)
Large-scale fading describes the variation in the average received signal power over large distances, typically hundreds or thousands of meters. It is caused by large obstacles in the propagation path that block the signal, casting an RF "shadow."
- Cause: The primary cause is shadowing from large obstructions like buildings, hills, or dense forests. As a user moves, for example, from an open street into an area blocked by a tall building, the average signal strength will drop significantly.
- Characteristics: These fluctuations are slow and occur as the user moves over significant distances. The statistical variation of this shadowing effect is often modeled by a log-normal distribution. This means that while the signal strength stays close to the average predicted by path loss models most of the time, there are probabilities of experiencing much deeper, prolonged drops in signal strength when in a shadow.
- Mitigation: Large-scale fading is primarily dealt with through careful network planning. This includes strategic placement of cell towers to minimize coverage holes, ensuring cells overlap sufficiently, and employing a process called macro-diversity, which is more commonly known as a handoff (or handover). When your signal from one cell tower becomes too weak because you have moved into a shadow, your phone is handed off to a different, nearby cell tower from which it receives a stronger signal.
Small-Scale Fading
This is the type of fading that is much more rapid and occurs over very short distances, often on the order of half a wavelength. A signal at has a wavelength of about 12.5 centimeters, meaning you can experience a deep fade by moving your phone just 6 centimeters.
- Cause: The sole cause of small-scale fading is the constructive and destructive interference of multiple signal copies arriving at the receiver via multipath propagation.
- Characteristics: It is characterized by very deep, rapid fluctuations in signal amplitude and phase as the receiver moves even a tiny distance. The statistical behavior of these fluctuations is often modeled by specific distributions, such as the Rayleigh or Rician distributions, depending on whether a dominant line-of-sight path exists.
- Mitigation: Small-scale fading is too fast and localized to be handled by network planning. It must be combatted at the signal processing level within the receiver and transmitter using advanced techniques like diversity, equalization, and sophisticated modulation schemes, which we will explore in detail.
A Deeper Look into Small-Scale Fading Mechanisms
Small-scale fading itself can be further classified based on two key physical phenomena: the time-smearing effect of multipath (delay spread) and the frequency-shifting effect of motion (Doppler spread). These two effects give rise to a two-by-two classification of fading.
Fading Based on Multipath Time Delay Spread
Delay spread is the difference in arrival time between the first and last significant multipath components. The relationship between the delay spread of the channel and the symbol period of the transmitted signal determines the type of fading.
1. Flat Fading
Condition: Occurs when the signal bandwidth is narrow compared to the channel's . Equivalently, this happens when the symbol period of the signal is much longer than the delay spread of the channel.
Effect: All frequency components within the signal experience the same fading (attenuation and phase shift). The signal's amplitude fluctuates up and down, but its spectral shape is not distorted. It gets weaker or stronger, but it does not get "smeared". The channel is "flat" across the signal's bandwidth.
Applies to: Narrowband communication systems, like pagers or some slow data links.
2. Frequency-Selective Fading
Condition: Occurs when the signal bandwidth is wide compared to the channel's coherence bandwidth. Equivalently, the delay spread of the channel is greater than the symbol period of the signal.
Effect: Different frequency components of the signal experience different, uncorrelated fading. The channel acts as a filter, attenuating some parts of the signal spectrum while leaving others untouched. This distorts the received signal and is the direct cause of Intersymbol Interference (ISI), as the "echoes" from one symbol corrupt the next.
Applies to: All modern wideband communication systems, such as Wi-Fi, 4G, and 5G. Combating frequency-selective fading is one of their primary design challenges.
Fading Based on Doppler Spread
is a measure of how fast the channel is changing. It is caused by the relative motion between the transmitter and receiver, or by the movement of objects in the environment. This motion causes a shift in the frequency of the received signal components, known as the Doppler effect. The relationship between this rate of change and the symbol rate of the signal determines the type of fading.
1. Fast Fading
Condition: The channel impulse response changes rapidly within the symbol duration. This occurs when the coherence time of the channel is shorter than the symbol period of the signal. High Doppler spread.
Cause: High-speed user mobility (e.g., in a car on a highway) or a rapidly changing environment.
Effect: The channel is changing so quickly that it cannot be considered constant even for the duration of a single transmitted symbol. This leads to signal distortion and is a very difficult condition to combat.
2. Slow Fading
Condition: The channel impulse response changes much slower than the transmitted signal. This occurs when the coherence time of the channel is much longer than the symbol period. Low Doppler spread.
Cause: User is stationary or moving at pedestrian speeds.
Effect: The channel can be considered static over one or even many symbol periods. The primary challenge is not the distortion within a symbol but rather the overall amplitude level of the channel during that time, which may be high or low depending on the flat fading condition. Most common communication scenarios fall into this category.
Combating Fading: The Power of Diversity
If we know that a signal can be extremely weak at a certain point in space, at a certain frequency, or at a certain time, how can we design a system to be reliable? The most powerful and widely used strategy is .
The fundamental principle of diversity is to provide the receiver with multiple copies of the same transmitted signal that have experienced different, or ideally independent, fading conditions. It is based on the statistical observation that the probability of all copies being simultaneously in a deep fade is far lower than the probability of a single copy being in a deep fade. If one copy is weak, there is a good chance another one is strong. There are several ways to obtain these independent signal copies.
1. Space Diversity
This is the most common form of diversity. It is achieved by using two or more antennas separated by a certain distance. Because the multipath environment is slightly different at each antenna's location, the fading experienced by each antenna will be largely uncorrelated, as long as the separation is sufficient (typically at least half a wavelength). The receiver can then combine the signals from these antennas to create a much more robust and stable resulting signal. Techniques include:
- Selection Combining: The simplest method. The receiver simply measures the signal strength from all antennas and selects the one with the best signal for decoding.
- Maximal-Ratio Combining (MRC): A more optimal but complex method. The receiver coherently combines the signals from all antennas, weighting each one based on its signal-to-noise ratio. This provides the best possible combined signal. Modern technologies like MIMO are an advanced form of space diversity.
2. Frequency Diversity
This involves transmitting the same information simultaneously on two or more different carrier frequencies. If the frequencies are separated by more than the channel's coherence bandwidth, the fading they experience will be independent. A deep fade on one frequency will likely not coincide with a deep fade on the other. While effective, this technique is not spectrally efficient as it consumes multiple channels for a single stream of information.
3. Time Diversity
This involves transmitting the same information at different points in time. If the time separation between transmissions is longer than the channel's coherence time, the channel will have changed, and the fading conditions will be different. This is often implemented using a combination of error-correction coding and . Interleaving scrambles the order of the transmitted bits, so that if a short fade causes a burst of consecutive errors, these errors are spread out at the receiver after de-interleaving. This transforms a burst error into a series of single-bit errors, which are much easier for error-correction codes to fix.
4. Polarization Diversity
This technique uses two antennas with orthogonal polarizations (for example, one transmitting with vertical polarization and one with horizontal). Reflections in the environment can alter the polarization of a signal. By providing two polarized versions of the signal, the system increases the chance that at least one will be received strongly, even as the polarization state changes through the channel.
Advanced Strategies for Mitigating Fading Effects
Beyond diversity, modern wireless systems employ sophisticated signal processing techniques to actively combat the specific distortions caused by fading.
- Channel Equalization: The primary weapon against Intersymbol Interference (ISI) caused by frequency-selective fading is the equalizer. An equalizer is an adaptive digital filter inside the receiver that attempts to reverse the distortion introduced by the channel. It "learns" what the channel is doing to the signal and applies an inverse filter to cancel it out, effectively sharpening the smeared-out symbols back into their original form before the final decision is made.
- Orthogonal Frequency Division Multiplexing (OFDM): OFDM, the core technology of Wi-Fi, 4G, and 5G, takes a brilliantly different approach to handling frequency-selective fading. Instead of fighting the wideband channel's distortion with a complex equalizer, it cleverly divides the wideband channel into thousands of very narrow, slow subchannels. Each subchannel is now so narrow that it experiences simple flat fading, not frequency-selective fading. This transforms one very difficult problem into many much simpler problems to solve, making high-speed wireless data transmission practical.
- MIMO Systems: As the ultimate form of space diversity, MIMO (Multiple-Input Multiple-Output) uses multiple antennas at both the transmitter and receiver. It can use this spatial dimension not only to improve reliability (diversity gain) but also to send multiple independent data streams simultaneously in the same frequency band (spatial multiplexing), dramatically increasing the data rate. MIMO systems essentially turn the multipath channel from an adversary into an ally.