ArticleslgStudy

science

Pseudorandom noise

Pseudorandom noise 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 Pseudorandom noise rather than just read about it. In short: In cryptography, pseudorandom noise (PRN) is a signal similar to noise which satisfies one or more of the standard tests for statistical randomness. Although it seems to lack any definite pattern, pseudorandom noise consists of a deterministic sequence of pulses that will repeat itself after its period.

Key takeaways

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

Reference excerpt

In cryptography, pseudorandom noise (PRN) is a signal similar to noise which satisfies one or more of the standard tests for statistical randomness. Although it seems to lack any definite pattern, pseudorandom noise consists of a deterministic sequence of pulses that will repeat itself after its period. In cryptographic devices, the pseudorandom noise pattern is determined by a key and the repetition period can be very long, even millions of digits. Pseudorandom noise is used in some electronic musical instruments, either by itself or as an input to subtractive synthesis, and in many white noise machines. In spread-spectrum systems, the receiver correlates a locally generated signal with the received signal. Such spread-spectrum systems require a set of one or more "codes" or "sequences" such that

Like random noise, the local sequence has a very low correlation with any other sequence in the set, or with the same sequence at a significantly different time offset, or with narrow band interference, or with thermal noise. Unlike random noise, it must be easy to generate exactly the same sequence at both the transmitter and the receiver, so the receiver's locally generated sequence has a very high correlation with the transmitted sequence. In a direct-sequence spread spectrum system, each bit in the pseudorandom binary sequence is known as a chip and the inverse of its period as chip rate; compare bit rate and symbol rate. In a frequency-hopping spread spectrum sequence, each value in the pseudorandom sequence is known as a channel number and the inverse of its period as the hop rate. FCC Part 15 mandates at least 50 different channels and at least a 2.5 Hz hop rate for narrow band frequency-hopping systems. GPS satellites broadcast data at a rate of 50 data bits per second – each satellite modulates its data with one PN bit stream at 1.023 million chips per second and the same data with another PN bit stream at 10.23 million chips per second. GPS receivers correlate the received PN bit stream with a local reference to measure distance. GPS is a receive-only system that uses relative timing measurements from several satellites (and the known positions of the satellites) to determine receiver position. Other range-finding applications involve two-way transmissions. A local station generates a pseudorandom bit sequence and transmits it to the remote location (using any modulation technique). Some object at the remote location echoes this PN signal back to the location station – either passively, as in some kinds of radar and sonar systems, or using an active transponder at the remote location, as in the Apollo Unified S-band system. By correlating a (delayed version of) the transmitted signal with the received signal, a precise round trip time to the remote location can be determined and thus the distance.

PN code

A pseudo-noise code (PN code) or pseudo-random-noise code (PRN code) is one that has a spectrum similar to a random sequence of bits but is deterministically generated. The most commonly used sequences in direct-sequence spread spectrum systems are maximal length sequences, Gold codes, Kasami codes, and Barker codes.

See also Barker code Gold Codes Maximum length sequence Zadoff–Chu sequence Pseudorandom number generator Pseudorandomness White noise

References

Worked examples

Example 1 — a first encounter with Pseudorandom noise

Start with the simplest possible case. Write down what Pseudorandom noise 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 Pseudorandom noise 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 Pseudorandom noise 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 Pseudorandom noise

In research
Pseudorandom noise 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 Pseudorandom noise 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
Pseudorandom noise is common in secondary-school and first-year university syllabi. It links to neighbouring topics Noise (electronics), Pseudorandomness, so understanding it makes those chapters shorter.
In everyday life
Look for Pseudorandom noise 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.
Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Pseudorandom noise” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Pseudorandom noise in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Pseudorandom noise 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 Pseudorandom noise out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Pseudorandom noise in simple terms?

In cryptography, pseudorandom noise (PRN) is a signal similar to noise which satisfies one or more of the standard tests for statistical randomness. Although it seems to lack any definite pattern, pseudorandom noise consists of a deterministic sequence of pulses that will repeat itself after its pe…

Why does Pseudorandom noise 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 Pseudorandom noise?

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 Pseudorandom noise.

Tags

  • Noise (electronics)
  • Pseudorandomness

Keep exploring