To understand how wireless data transfer works, we need to understand:
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What is frequency?
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Information/data signal time representation
frequency representation, why is it important?
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How do filters work?
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FCC communication frequency band
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modulation and demodulation
These are the topics that you may have learned in college courses, which involve a very large amount of knowledge. A previous PowerPoint presentation I prepared for non-Engineering students in the senior project group included these topics - students were expected to be able to figure out terms like "900MHz" or "2.4GHz" or "frequency hopping" when we talked about them . This article is limited in length, it is difficult to explain these topics completely and thoroughly, ignoring many details involved in professional courses, and only providing a conceptual description of wireless transmission.
What is frequency?
Frequency is a term that describes how often an oscillation occurs or repeats, measured in Hertz (Hz) or the reciprocal of a second. If it oscillates 60 times per second, its frequency is 60Hz. In this article, we'll focus on audio waves (oscillations of air pressure) and how they travel from a radio station to your car radio (or any AM radio station) at frequencies in the hundreds of kilohertz. Any wave has a frequency, and so does light. Light waves and other higher frequency waves (such as X-rays, gamma rays, microwaves) are generally expressed in terms of wavelength, not frequency. For example, green light has a wavelength of about 400 nanometers. The following figure shows the relationship between traveling wave units:
Basic unit of sine wave
Assuming a constant signal speed, wavelength and frequency can be converted, but this is beyond the scope of this article. Information signals of varying complexity if sent a pure sine wave signal (called "tone"). It doesn't carry any real information, and it doesn't sound nice. The picture below is an image of a sine wave, with time on the X axis and voltage on the Y axis, which is a 150Hz reference signal.
Single tone signal (time domain)
So why look at this image? Let's look at signals of increasing complexity in the time domain. This is a dual tone signal (two tones superimposed together). This sine wave is the same as the previous sine wave, but with another sine wave of double frequency (300Hz) added.
Dual tone signal (time domain)
So what does a signal consisting of multiple tones of different frequencies look like?
Multiple audio signals (time domain)
It gets more glitchy. The only real information you can see in this graph is the voltage level at a given time. That's the nature of information, and it's extremely important—but it also complicates analysis, and makes understanding how modulation works harder. For this, you may want to plot the signal in a different way (frequency domain). It shows the strength of the signal over a range of frequencies. Let's take a look. Why is the frequency spectrum of a signal important? Transforming a large number of signals into the frequency domain requires sophisticated mathematical operations. The work is difficult, computationally intensive, and requires repeated practice to master. I even periodically convolve those important signals to practice my conversion skills. Anyway, let's see how the above three signals can be represented in this form (ignoring the intermediate derivation here). Instead of plotting the signal voltage versus time, we plot the signal power versus frequency.
Single tone signal (frequency domain)
Dual audio signal (frequency domain)
Multiple audio signals (frequency domain)
Notice the obvious spikes in the graph? That's the mathematical representation of a sine wave at a specific frequency (X-axis). Ideally, these spikes should be infinitely narrow (width) and infinitely high, but due to the state of the art of the Spice software I'm using, it's not perfect. This signal is called a pulse signal. For a detailed description of this signal, read here! For this audio, we see a spike in the frequency domain, at 150Hz. Whereas a dual tone signal has two peaks in the frequency domain, at 150Hz and 300Hz. Multi-audio signals are basically uninterpretable in the time domain, and the many small peaks in the time domain signal are composed of the superposition of multiple frequency points.
One last example, an actual audio signal. As shown in the picture below, I sampled the song "White Room (White Room)" by singer Cream for 15 seconds. Don't worry about signal length, neither mic was damaged during Eric Clapton's guitar solo.
Audio Signals This is what most signals look like, especially analog signals. The sounds of people and instruments are not played at discrete frequencies, their frequency content is distributed across the frequency range (although some content is barely audible). This range is between 3Hz and 20kHz, which is about the frequency range that the human ear can hear. The lower frequencies are lower and the higher frequencies are higher. The Y-axis scale is expressed in dB, and dB represents a ratio without units. Essentially, the higher the dB value, the higher the signal at that frequency. Theoretically, we can represent this analog signal as the sum of an infinite number of audio signals. filter! Fortunately, a graphical representation of the frequency domain can provide some assistance in filter design. There are four types of filters, including:
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Low Pass Filter: All frequencies above the Cutoff Frequency are filtered out.
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High Pass Filter: All frequencies below the Cutoff Frequency are filtered out.
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Bandpass filter: All frequencies outside a certain range from the "center frequency" are filtered out.
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Bandstop filter: All frequencies within a certain distance from the "center frequency" are filtered out.
From top to bottom: bandpass filter, lowpass filter, highpass filter
The "3dB" point is where the signal output drops by approximately 30%. dB is a logarithmic scale:
x[dB]=10*log(x[linear])
x[linear]=10^(x[dB]/10)
Based on this formula, x[linear]=0.7, the corresponding x[dB] is about -3.0dB, 0.7 is 70%, that is, the signal is attenuated by 30%, and the corresponding frequency is called the cut-off frequency of the filter. A practical example is a car stereo, which may include a "crossover" with a special filter design that switches low frequencies to the woofer and high frequencies to the tweeter. This is very important for wireless receivers.
FCC communication frequency band
The FCC and other international organizations agree that if anyone is allowed to use any frequency at will, it will inevitably lead to absolute chaos. Therefore, different frequency ranges should be allocated to different users. For example, different frequency bands are allocated for FM radio, AM radio, WiFi, mobile phone, maritime communication, air traffic control, amateur radio, walkie-talkie, military communication, police radio and other applications. Oh, and we haven't even mentioned satellites or space communications! It's such a mess, thankfully the FCC helps manage it. If you're curious, do a Google search and you'll find a more detailed diagram right away.
FCC Spectrum Allocation Table
The FCC has reserved some frequency bands for small-scale personal use, amateur use, and other general "ISM band" applications (industrial, scientific, medical). This is the operating frequency band for WiFi, walkie-talkies, wireless sensors, and other communication devices. Let's discuss frequency again! The hearing range of the human ear is 20Hz to 20kHz. If our AM station is 680kHz, how do radio towers change the sound to that frequency? How does it avoid interfering with other stations? How does the receiver convert the signal frequency back into the audible range?
modulation
Let's leave the frequency domain and go back to the time domain. Just to reiterate: our discussion has been too simplistic and left out a lot of details! This is just to get a conceptual result. The reason for this is that mathematical representations work best in the time domain, while graphical representations work best in the frequency domain.
The job of modulation is to convert a signal from a low frequency (information) to a high frequency (carrier). The idea is simple: multiply your message by a high frequency carrier, say 680kHz, and that's AM broadcasting! Wait a minute, is it really that simple? Let's look at a few mathematical relationships. In this example, θ is the message (audible content) and φ is the carrier (eg AM broadcast frequency).
The text in the picture is bilingual in Chinese and English
If our AM signal is expressed in a formula, it involves the multiplication of multiple signals, which is difficult to imagine in the time domain or frequency domain, because we only see what the audio looks like. But the above correspondence tells us: the multiplication of two signals can be represented by the addition of two signals! Now, we can easily plot the multiplied signal in the frequency domain.
Single tone (150Hz) modulated on carrier (1000Hz)
In this diagram we are multiplying a 150Hz audio by a 1000Hz carrier. The table above shows two half-power signals at 1000-150 and 1000+150Hz, that is, at 850Hz and 1150Hz. So how does each of our syllables behave when modulated?
Sound modulated to 700kHz
As expected, we saw two signals. One is carrier + information and the other is carrier - information (even notice how it's reversed). This is a rough diagram of the AM spectrum and signal content.
Demodulation Now we come to the receiver. All the signals start at the antenna, and looking at all the signals at the same time, it's a mess. The antenna picks up a lot of data, but it's not in charge of sorting it out, that's the job of the tuner and other hardware. The principle of signal demodulation is exactly the same as that of modulation, which is very convenient! To convert our audio signal back to "baseband" and send it to the speaker, we can multiply all the signal by the carrier again.
This formula contains a large list of mathematical functions, parentheses, and frequency variables. But it's right, and we derive four signals from this:
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1/4 power signal, (2*carrier + message)
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1/4 power signal, (info)
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1/4 power signal, (2*carrier-information)
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1/4 power signal, (-info)
Let's ignore this term involving negative frequencies, which is a mathematical artifact that often comes up when we discuss modulation and the operations involved. The two signals on double the carrier (assuming the carrier is much larger than the message, they are nearly identical) can be filtered out with a low pass filter. A low pass filter blocks all high frequency content of the signal, leaving us with only the original information. We use amplifiers to amplify the original information and send it to speakers. so cool! Here's an image of it, but delayed a bit backwards. Conclusion The purpose of this article is to provide a high-level overview of how radio signals are transmitted and modulated. By multiplying multiple audio (or baseband) signals with different high-frequency signals (carriers), we can successfully transmit multiple data streams over the same channel without interfering with each other. Multiply again with the carrier wave, convert the modulated signal back to baseband, and then clean up and amplify the signal with a low-pass filter and amplifier, so that we can hear all kinds of beautiful sounds!
Source: Digital Test
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Original: How Signal Modulation Works - RFASK Radio Frequency Questions
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