Power-Based Broadband RF Interference Detector for Wireless Communication Systems

Getu, Tilahun M.; Ajib, Wessam; Landry, René

doi:10.1109/lwc.2018.2845373

Cited by 8 publications

(5 citation statements)

References 30 publications

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“…According to the results in (2) and (20), without considering the noise uncertainty, similar to the proof of (2), we have…”

Section: B Proof Of Equation (22)mentioning

confidence: 53%

“…As we know, ( ) ∼ N(0, 2 ) and ( ) ∼ N(0, 2 ). Therefore, according to the theorem of large numbers, when is large enough, we can derive the equations as follows: Therefore, aided by (A.4), (A.5), (A.9), and (A.10), the can be given as (2), which completes this proof.…”

Section: Resultsmentioning

confidence: 72%

“…Interference detection has attracted more and more attention in recent years due to its importance to anti-interference processing [1][2][3][4]. There are numerous methods to achieve signal detection, such as cyclostationary detection [3], covariance based detection [5], matched-filter detection, and energy detection (ED).…”

Section: Introductionmentioning

confidence: 99%

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A Two-Step Cooperative Energy Detection Algorithm Robust to Noise Uncertainty

Yang

et al. 2019

Wireless Communications and Mobile Computing

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In order to achieve accurate interference detection in complex electromagnetic environments, a two-step cooperative stochastic resonance energy detection (TCSRED) algorithm is proposed to address the problem, where the traditional energy detection (ED) performance is susceptible to noise uncertainty. By combining two thresholds and two-step cooperation, the generalized stochastic resonance is applied to the energy detection, which effectively reduces the complexity and detection time. In particular, when a certain decision result is obtained in the first step of detection, the decision is finished and the second step of detection is unnecessary. Otherwise, the second step of detection is performed to obtain the final decision result. Simulation results show that the proposed algorithm is robust to the noise uncertainty. Even in the case of a low signal-to-noise ratio (SNR), it also performs better than existing methods without significant increment of the complexity.

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“…According to the results in (2) and (20), without considering the noise uncertainty, similar to the proof of (2), we have…”

Section: B Proof Of Equation (22)mentioning

confidence: 53%

Section: Resultsmentioning

confidence: 72%

See 1 more Smart Citation

A Two-Step Cooperative Energy Detection Algorithm Robust to Noise Uncertainty

Yang

et al. 2019

Wireless Communications and Mobile Computing

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“…where ỹt and ỹf t are the DeepSC signals of the relatively wide trained DeepSC model and the relatively wide trained and finetuned DeepSC model, respectively. For the MI RFI scenario, we presume -without loss of generality -that the trained channel decoders receive time-varying MI RFI from U Gaussian RFI (i.e., broadband RFI) [56]- [59] emitters whose interference signals are received over Rayleigh fading channels. Under MI RFI, the received DeepSC signals during the t-th time slot are equated as…”

Section: A Testing Setup and Assumptionsmentioning

confidence: 99%

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

2023

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Semantic communication (SemCom) aims to convey the meaning behind a transmitted message by transmitting only semantically-relevant information. This semantic-centric design helps to minimize power usage, bandwidth consumption, and transmission delay. SemCom and goal-oriented SemCom (or effectiveness-level SemCom) are therefore promising enablers of 6G and developing rapidly. Despite the surge in their swift development, the design, analysis, optimization, and realization of robust and intelligent SemCom as well as goal-oriented SemCom are fraught with many fundamental challenges. One of the challenges is that the lack of unified/universal metrics of SemCom and goal-oriented SemCom can stifle research progress on their respective algorithmic, theoretical, and implementation frontiers. Consequently, this survey paper documents the existing metrics -scattered in many references -of wireless SemCom, optical SemCom, quantum SemCom, and goal-oriented wireless SemCom. By doing so, this paper aims to inspire the design, analysis, and optimization of a wide variety of SemCom and goal-oriented SemCom systems. This article also stimulates the development of unified/universal performance assessment metrics of SemCom and goal-oriented SemCom, as the existing metrics are purely statistical and hardly applicable to reasoning-type tasks that constitute the heart of 6G and beyond.

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“…Such a lack of knowledge makes the existing hypothesis testing frameworks [16], [17] hardly useful with regard to the aforementioned undertaking. Highlighting the latest research advancements pertaining to this research field, meanwhile, a power-based broadband RFI detector and an energy-based RFI detector are investigated in [18] and [19], respectively. However, these RFI detectors rely on the knowledge of the noise power and they are detectors proposed, mainly, for single-antenna systems.…”

Section: A Related Workmentioning

confidence: 99%

Eigenvalue-Based RF Interference Detector for Multi-Antenna Wireless Communications

Getu¹,

Ajib²,

Landry³

2020

Preprint

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<div>Abstract</div><div><br></div><div>Radio frequency interference (RFI) is occurring in both satellite and terrestrial communication systems. In order to mitigate RFI efficiently, it has to be detected robustly. Toward this end, through the computation of an eigenvalue-based test statistic, an eigenvalue-based blind RFI detector is proposed for single-input multiple-output systems that may suffer from RFI. For medium to large interference-tonoise ratio (INR) regimes and under sample starved settings, Monte-Carlo simulations corroborate that the proposed blind detector manifests a comparable detection performance with a generalized likelihood ratio test (GLRT) detector fed with the knowledge of the signal of interest (SOI) channel, and a matched subspace detector fed with the knowledge of the SOI and RFI channels. Such performance signifies the applicability of the proposed RFI detector for real-time applications. <br></div>

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Power-Based Broadband RF Interference Detector for Wireless Communication Systems

Cited by 8 publications

References 30 publications

A Two-Step Cooperative Energy Detection Algorithm Robust to Noise Uncertainty

A Two-Step Cooperative Energy Detection Algorithm Robust to Noise Uncertainty

Making Sense of Meaning: A Survey on Metrics for Semantic and Goal-Oriented Communication

Eigenvalue-Based RF Interference Detector for Multi-Antenna Wireless Communications

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