PN (Pseudorandom Noise)

Definition

PN stands for Pseudorandom Noise, a sequence of numbers that appears random but is generated deterministically using mathematical algorithms. The sequence has properties similar to random noise, such as being unpredictable over short periods, but can be reproduced if the algorithm and seed are known. PN sequences are crucial in various communication systems, including spread spectrum technologies like DSSS (Direct Sequence Spread Spectrum) and CDMA (Code Division Multiple Access), where they are used to spread signals across wide bandwidths to reduce interference and enhance security.

Usage

In communication systems, Pseudorandom Noise sequences are used to spread the data signal over a broader frequency range, creating a wider signal bandwidth that is more resilient to interference. By correlating the received signal with the Pseudorandom Noise sequence, the original data can be retrieved even in noisy environments. Pseudorandom Noise sequences are also used in encryption, GPS systems, and other applications that require a level of unpredictability while maintaining reproducibility when needed.

Relevance to the Industry

Pseudorandom Noise sequences play a critical role in drone communication, particularly when using DSSS or FHSS (Frequency Hopping Spread Spectrum). By spreading the signal using a Pseudorandom Noise sequence, drone communication systems can reduce the impact of interference and improve signal integrity in crowded frequency bands. The predictable, yet seemingly random nature of PN sequences makes them ideal for applications that need both security and robust signal transmission.

How Does Pseudorandom Noise (PN) Work?

Generating the PN Sequence:

1. Deterministic Algorithm:
   • Mathematical Generation: A pseudorandom noise (PN) sequence is generated using a deterministic algorithm that produces a series of numbers with statistical properties similar to random noise. However, the sequence is not truly random; it is pseudorandom because it follows a specific mathematical formula and can be reproduced if the algorithm and initial seed (starting point) are known. Common algorithms for generating Pseudorandom Noise sequences include linear feedback shift registers (LFSRs), which shift bits in a sequence and apply specific feedback rules to determine the next bit in the sequence.
   • Predictable Yet Seemingly Random: Although PN sequences appear random over short intervals, they are predictable if the seed and algorithm are known. This allows the sequence to be synchronized between the transmitter and receiver, a key feature in communication systems where reproducibility is required to decode the signal.
2. Properties of PN Sequences:
   • Balance and Autocorrelation: A good Pseudorandom Noise sequence has a balance property, meaning that over time, it contains an equal number of 1s and 0s (for binary sequences). Additionally, the sequence has a low autocorrelation, meaning that the sequence does not resemble any shifted version of itself, which is essential for distinguishing the signal from noise or interference in communication systems.
   • Periodicity: PN sequences are typically periodic, meaning they repeat after a certain length of time (the sequence length). In applications like spread spectrum communication, this periodicity allows the receiver to synchronize with the sequence and correctly interpret the data.

Spreading the Signal in Communication Systems:

3. Spreading the Data Signal:
   • Spreading Factor: In systems like Direct Sequence Spread Spectrum (DSSS), the PN sequence is used to spread the original data signal over a wider frequency range. This is done by multiplying the data signal with the PN sequence at a higher rate, called the spreading factor. The spreading factor determines how much the signal is spread across the available bandwidth. A higher spreading factor results in a wider signal bandwidth and better resistance to interference and noise.
   • Wideband Transmission: Once the data is combined with the PN sequence, the signal is transmitted over a wide range of frequencies. This wideband signal appears as low-power noise to unintended receivers, making it difficult for them to detect or interfere with the signal. At the receiver end, the same PN sequence is used to despread the signal, allowing the original data to be retrieved.
4. Despreading at the Receiver:
   • Correlation with PN Sequence: The receiver must use the same PN sequence to correlate with the incoming signal. Since the sequence is synchronized between the transmitter and receiver, the receiver can match the PN sequence to despread the signal and recover the original data. If the receiver does not have the correct PN sequence or is out of sync, it will not be able to decode the signal, which provides an inherent level of security.
   • Interference Rejection: The correlation process effectively filters out any interference or noise that does not match the PN sequence. This allows the system to maintain a strong signal even in environments with significant RF noise or other interfering signals.

Applications and Advantages of PN:

5. Use in Spread Spectrum Systems:
   • Direct Sequence Spread Spectrum (DSSS): In DSSS, PN sequences are used to spread the data signal, improving its resistance to interference and providing some level of security, as the signal appears like noise to anyone not using the correct PN sequence.
   • Frequency Hopping Spread Spectrum (FHSS): In FHSS systems, PN sequences determine the order of frequency hopping, ensuring that both the transmitter and receiver hop between frequencies in a synchronized pattern. This hopping provides additional resistance to jamming and interception, as an unauthorized receiver would need to know the hopping pattern to follow the transmission.
6. Applications in Modern Communication:
   • GPS Systems: PN sequences are used in Global Positioning System (GPS) satellites to encode unique signals for each satellite. This allows GPS receivers to differentiate between signals from multiple satellites, improving accuracy and precision.
   • Encryption and Cryptography: PN sequences are used in cryptographic systems to introduce randomness and enhance security. The ability to generate a sequence that appears random but can be reproduced with a known seed is essential for secure key generation and data encryption.

By generating a sequence that appears random but is reproducible, pseudorandom noise (PN) sequences play a vital role in spreading data across wide frequency ranges, enhancing signal security, and improving resistance to interference in modern communication systems.

Example in Use

“The drone’s communication system relies on a pseudorandom noise (PN) sequence to spread the control signal across multiple frequencies, minimizing interference and ensuring a stable connection.”

Frequently Asked Questions about PN (Pseudorandom Noise)

1. What is a pseudorandom noise (PN) sequence?

Answer: A Pseudorandom Noise sequence is a deterministic sequence that mimics the properties of random noise. It appears random but is generated using a specific algorithm and seed, which allows it to be reproduced if the same inputs are known.

2. How is a PN sequence used in communication systems?

Answer: In communication systems like DSSS and FHSS, PN sequences spread the signal across a wide frequency band. The receiver, knowing the same Pseudorandom Noise sequence, despreads the signal, retrieving the original data while filtering out interference and noise.

3. What are some common applications of PN sequences?

Answer: Pseudorandom Noise sequences are used in:

• Spread Spectrum Communication: For spreading data across multiple frequencies to improve resistance to interference.
• GPS Systems: To encode satellite signals with unique PN codes for accurate positioning.
• Encryption: Providing unpredictability in cryptographic systems.