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Stochastic Signal Density Modulation

Stochastic Signal Density Modulation is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Stochastic Signal Density Modulation rather than just read about it. In short: Stochastic Signal Density Modulation (SSDM) is a novel power modulation technique primarily used for LED power control. The information is encoded - or the power level is set - using pulses that have pseudo-random widths.

Stochastic Signal Density Modulation — main illustration
Stochastic Signal Density Modulation — illustration

Key takeaways

  • Stochastic Signal Density Modulation belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Stochastic Signal Density Modulation to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Stochastic Signal Density Modulation from memory before moving on to harder problems.

Reference excerpt

Stochastic Signal Density Modulation (SSDM) is a novel power modulation technique primarily used for LED power control. The information is encoded - or the power level is set - using pulses that have pseudo-random widths. The pulses are produced so that, on average, the produced signal will have the desired ratio between high and low states. The main benefit of using SSDM over, for example, Pulse-width modulation (PWM), which is usually the preferred method for controlling LED power, is reduced electromagnetic interference. Figure 1 illustrates a SSDM signal and demonstrates how the average signal density approaches desired value. The pseudo-random pulses in the signal are visible. SSDM can be seen as a special case of Pulse-density modulation (PDM) or Random Pulse Width Modulation (RPWM).

Principle and signal creation

Producing an SSDM signal requires a Linear-feedback shift register (LFSR) or similar source providing a sequence of pseudo-random numbers, a signal density register, and a comparator. On each clock cycle, the LFSR provides one pseudo-random number. This is compared against the signal density register. The output is set to high if the signal density register is lower than the generated pseudo-random number. If the signal density register is higher than the generated pseudo-random number, the output is low. This is illustrated in figure 2. When LFSR is used to provide pseudo-random numbers with a maximum possible period, the sequence will contain each of the numbers in the range once (except the zero) and eventually repeat. For a 4-bit LFSR the sequence is [1 2 5 3 7 6 4]. If the signal density register would be set to 3, would the corresponding SSDM signal be repeating the [1 1 0 1 0 0 0] pattern? Figure 3 demonstrates the signal generation process. The generated sequence of pseudo-random numbers is shown in the first sub-plot and a desired 30% threshold. The lower plot is the produced SSDM signal. It can be seen that the output is high only when the generated pseudo-random numbers are at or below the desired threshold. The SSDM signal will average at 30% of the maximum. Also, the repetitive nature of LFSR is visible in the pseudo-random number sequence and the resulting SSDM signal.

Comparison against other modulation methods

SSDM has significant advantages over PWM when used for power control. In the PWM signal, the frequency at which the output is turned high is constant. Only the width of the pulses is varied. This results in relatively high electromagnetic interference amplitude. In the case of SSDM, as the pulse widths and intervals are not constant, the resulting interference is spread across a wider spectrum, reducing the overall interference amplitude. The fundamentally different operational principles of SSDM and PWM are illustrated in figure 4. Both signals are shown with two different signal density or pulse-width ratios: 10% and 70%. Figure 5 illustrates the simulated spectrum of SSDM signal compared to PWM. Both are set to 30% signal density or pulse width and operate on the same frequency. As it can be seen, the amplitude on the lowest frequency component in SSDM is attenuated by more than 20 dB. This also demonstrates that for SSDM most of the signal energy is shifted to higher frequencies.. Some sources cite attenuation of 30 dB However, due to the higher frequencies present in the signal, the SSDM may demand more from the load-driving circuitry than PWM. If there is any filtering present in the SSDM signal to reduce the higher frequency components, may this also affect the signal density. It's also worth noting that the increased number of individual transitions may also increase the switching losses on the MOSFETs used. Like PWM, Delta-sigma modulation (DSM) produces far higher amplitude on the fundamental frequency and for the four following harmonics than SSDM.

Practical implementation

Hardware support The SSDM technology is patented by Cypress Semiconductor. Hence the microcontrollers supporting SSDM signal generation using dedicated hardware modules are PSoC devices from Cypress Semiconductor. SSDM module is available in PSoC 1 series devices. With PSoC series 3, 4 and 5 Precision Illumination Signal Modulation (PrISM) modules can be used. PrISM is interchangeable for SSDM. While it is recognized in US Patent 8129924 that one practical option in a signal generation is using CPLD or FPGA devices, as of October 2017, no such implementations are publicly disclosed.

Considerations When creating an SSDM signal, regardless of the method (HW, FPGA, Software), some consideration should be put on the frequency at which the signal is created and the other circuitry:

The lowest frequency the signal created will have is determined by the frequency at which the LFSR creates random numbers and the desired resolution as follows: F out = F LFSR 2 n − 1 {\displaystyle F_{\text{out}}={\frac {F_{\text{LFSR}}}{2^{n}-1}}} . When SSDM is used for LED power control, the driving frequency should be higher than the Flicker_fusion_threshold. For PrISM technology, 120 Hz minimum frequency on the output should be sufficient to avoid visible flicker. 300 Hz to guarantee flicker-free operation. When the frequency of the SSDM signal increases, so does the number of high-frequency components. This may affect the output-driving circuitry, and in some cases, filtering may occur. Filtering may affect the resulting pulse density. Some implementations do demonstrate the use of a low-pass filter that is set to filter the higher part of the frequencies in the SSDM signal. The use of SSDM may increase switching losses. The impact of the higher frequency components in the SSDM signal on other systems should be analyzed.

See also Pulse-width modulation Pulse-density modulation Electromagnetic interference

References

External links SSDM spectral analysis scripts for Matlab Cypress Semiconductor AN49262: Modulation Techniques for LED Dimming

Illustrations

Stochastic Signal Density Modulation: Figure 2: SSDM generation block diagram.
Figure 2: SSDM generation block diagram.
Stochastic Signal Density Modulation: Figure 3: creation of 5-bit SSDM signal with 30% signal density.
Figure 3: creation of 5-bit SSDM signal with 30% signal density.
Stochastic Signal Density Modulation: Figure 4: SSDM and PWM signals compared
Figure 4: SSDM and PWM signals compared
Stochastic Signal Density Modulation: Figure 5: Amplitude spectrum of simulated SSDM and PWM signals
Figure 5: Amplitude spectrum of simulated SSDM and PWM signals

Worked examples

Example 1 — a first encounter with Stochastic Signal Density Modulation

Start with the simplest possible case. Write down what Stochastic Signal Density Modulation claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Stochastic Signal Density Modulation before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Stochastic Signal Density Modulation ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Stochastic Signal Density Modulation

In research
Stochastic Signal Density Modulation appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Stochastic Signal Density Modulation in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Stochastic Signal Density Modulation is common in secondary-school and first-year university syllabi. It links to neighbouring topics Electrical components, so understanding it makes those chapters shorter.
In everyday life
Look for Stochastic Signal Density Modulation outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Stochastic Signal Density Modulation in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Stochastic Signal Density Modulation means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Stochastic Signal Density Modulation out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Stochastic Signal Density Modulation in simple terms?

Stochastic Signal Density Modulation (SSDM) is a novel power modulation technique primarily used for LED power control. The information is encoded - or the power level is set - using pulses that have pseudo-random widths.

Why does Stochastic Signal Density Modulation matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Stochastic Signal Density Modulation?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Stochastic Signal Density Modulation.

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  • Electrical components

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