Evidence map›Paper›PMID 42045497›Full record

ArticleScientific reports2026

Adaptive frequency-domain CFAR for robust spectrum sensing under jamming and administrator-controlled counter-access.

Mohamed Salah Shams, Ahmed A Abouelfadl, Ahmed Mansour, Mohamed Samir Abdel Latif Soliman

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mohamed Salah ShamsElectrical Engineering Branch, Military Technical College, Cairo, Egypt. mohamedsalahshams56@gmail.com.
Ahmed A AbouelfadlElectrical Engineering Branch, Military Technical College, Cairo, Egypt.
Ahmed MansourElectronic Warfare Department, Military Technical College, Cairo, Egypt.
Mohamed Samir Abdel Latif SolimanElectronic Warfare Department, Military Technical College, Cairo, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cognitive radio networks (CRN) enable secondary users (SUs) to opportunistically access underutilized licensed spectrum while protecting primary users (PUs) from interference. However, robust spectrum sensing under heterogeneous interference and noise uncertainty remains challenging. Conventional energy detection, matched filtering, and cyclostationary approaches either require extensive prior knowledge or degrade under interference, leading to excessive false alarms and service denial. We propose an adaptive frequency-domain constant false alarm rate (CFAR) spectrum sensing approach that dynamically sets frequency-specific thresholds based on neighboring spectral samples. This enhancement requires minimal prior knowledge. To address potential security risks from untrusted SUs exploiting this resilience, we introduce a centralized counter-access mechanism: an administrator-controlled jammer that defeats CFAR-equipped adversaries, preventing unauthorized access during emergencies. It safeguards primary communications by creating strategic frequency gaps that avoid known jammed PU channels. Using APCO Project 25 waveforms for PUs, Monte Carlo simulations evaluate cell-averaging (CA), greatest-of (GO), smallest-of (SO), order-statistics (OS), and censored CFAR variants across different channel models combined with multiple jamming scenarios. Results show OS and censored CFAR variants best stabilize false alarm rates and enhance detection in heterogeneous conditions, outperforming CA and GO/SO schemes. The comb-sweep jammer effectively denies service to CFAR-equipped SUs without impacting PUs, though at the expense of reduced spectrum availability. Sensitivity analysis confirms robustness across varied CFAR window configurations, precluding parameter-based evasion by unauthorized SUs. This work frames spectrum sensing and jamming in CRNs as a two-sided interaction between electronic protection for secondary users and administrative electronic attack for controlled denial.

Indexed as

CFARCognitive radioEnergy detectionJammingSecure accessSpectrum sensing

Identifiers

PMID42045497
PMCPMC13121610

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.