How the Coherent Detector Works in Spread Spectrum Signals

This research investigates the detection of direct sequence spread spectrum (DSSS) signals, comparing the performance of a traditional energy detector with that of a cross-correlation detector. While energy detectors are widely used, they suffer from reduced sensitivity at low signal-to-noise ratios (SNR) and require accurate noise power estimation. In contrast, the cross-correlation detector utilizes the processing gain of DSSS signals to achieve higher detection accuracy without needing prior noise estimation. Using MATLAB simulations, Receiver Operating Characteristic (ROC) curves were generated for both detectors. Results show that the cross-correlation detector achieves up to 30% higher probability of detection (PD) at a false alarm probability (PFA) of 0.1 and SNR = –11 dB compared to the energy detector. This demonstrates the cross-correlation detector’s robustness and suitability for reliable DSSS signal detection in noisy environments.

Authors

Publication Details

Journal
Al-Farahidi Expert Systems Journal
Published
2025-12-29
DOI
https://doi.org/10.65645/3105-9104.1011
Primary Topic
Cognitive Radio Networks and Spectrum Sensing
Type
article
Field-Weighted Citation Impact
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article

How the Coherent Detector Works in Spread Spectrum Signals

Aymen Mohammed Khodayer, Louay Habib Skef, jenan J. abdulkareem
Al-Farahidi Expert Systems Journal
Cognitive Radio Networks and Spectrum Sensing
article

How the Coherent Detector Works in Spread Spectrum Signals

Aymen Mohammed Khodayer, Louay Habib Skef, jenan J. abdulkareem
article en

Abstract

This research investigates the detection of direct sequence spread spectrum (DSSS) signals, comparing the performance of a traditional energy detector with that of a cross-correlation detector. While energy detectors are widely used, they suffer from reduced sensitivity at low signal-to-noise ratios (SNR) and require accurate noise power estimation. In contrast, the cross-correlation detector utilizes the processing gain of DSSS signals to achieve higher detection accuracy without needing prior noise estimation. Using MATLAB simulations, Receiver Operating Characteristic (ROC) curves were generated for both detectors. Results show that the cross-correlation detector achieves up to 30% higher probability of detection (PD) at a false alarm probability (PFA) of 0.1 and SNR = –11 dB compared to the energy detector. This demonstrates the cross-correlation detector’s robustness and suitability for reliable DSSS signal detection in noisy environments.

Al-Farahidi Expert Systems JournalVol. 1(2)
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Openalex Percentile: Top 28%
Cognitive Radio Networks and Spectrum Sensing
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