Optimal Detection Threshold Research Articles

Non-Cooperative Spectrum Sensing Based on Cyclostationary Model of Digital Signals in the Context of Cognitive Radio

This paper addresses the problem of the opportunistic spectrum access in Cognitive Radio. Indeed, most spectrum sensing algorithms suffer from a high computational cost to achieve the detection process. They need a prior knowledge of signal characteristics and present a bad performance in low Signal to Noise Ratio (SNR) environment. The choice of the optimal detection threshold is another issue for these spectrum sensing algorithms. To overcome the limits of spectrum detectors, we propose in this paper, a blind detection method based on the cyclostationary features of communication signals. Our detector evaluates the level of hidden periodicity contained in the observed signal to make decision on the state of a bandwidth. In order to reduce the computational cost, we take advantage of the FFT Accumulation Method to estimate the cyclic spectrum of the observed signal. Then, we generate the Cyclic Domain Profile of the cyclic spectrum which allows us to evaluate the level of the hidden periodicity in the signal. This level of periodicity is quantified through the crest factor of Cyclic Domain Profile, which represents the decision statistic of the proposed detector. We have established the analytic expression of the optimal threshold of the detection and the probability of detection to evaluate the performance of the proposed detector. Simulation results show that the proposed detector is able to detect the presence of a communication signal on a bandwidth in a very low SNR scenario.

Covert Communications With Channel Inversion Power Control in the Finite Blocklength Regime

In this letter, we investigate covert communications with finite blocklength under the channel inversion power control (CIPC) scheme, where a transmitter is allowed to communicate with a receiver without transmitting the pilot signals, which facilitates the hidden of the transmitter from the warden. Considering both the conventional and truncated CIPC schemes, we provide the novel expressions of the optimal detection threshold and the minimum total error probability at the warden. Furthermore, the optimization of the power control parameter at the transmitter is presented to maximize the effective covert throughput, which quantifies the amount of the information bits transmitted from the transmitter to the receiver subject to the covert constraint, under two kinds of CIPC schemes.

Diagnostic Value of ROC Curve Evaluating Serum Related Indexes for Bloodstream Infection in Patients with Hematopathy

Sixty hematopathy patients with bloodstream infection from July 2016 to June 2018 were selected and enroued in bloodstream infection group. Sixty-five patients with negative blood culture during the same period were selected and enrolled in non-bloodstream infection group. The ROC curves were drawn and used to eualuate the diagnostic value of above montioned indexes. The levels of PCT, CRP and SAA in the bloodstream infection group were higher than those in the non-bloodstream infection group (P<0.05). ROC curve showed that AUC values of PCT, CRP, SAA and the combined test detection were 0.868, 0.746, 0.678 and 0.900, respectively, there was no significant difference in AUC between combined test and PCT test (P>0.05). AUC of combined test and PCT test were higher than those of CRP and SAA test, and the difference was statistically significant (P<0.05), but there was no significant difference in AUC between CRP and SAA (P>0.05). The optimal PCT detection threshold was 0.49 ng/ml, the sensitivity and specificity were 75.0% and 83.1%, respectively. The optimal critical value for CRP detection was 15.76 mg/L, the sensitivity and specificity were 60.0% and 80.0% respectively. The optimal SAA detection threshold was 35.66 mg/L, the sensitivity and specificity were 81.7% and 53.8%, respectively. PCT, CRP and SAA detection have good diagnostic value for blood stream infection in patients with hematopathy. The diagnostic value of PCT is better than CRP and SAA, and there is no significant difference in diagnostic value between combined test and PCT test.

Power Control for ISI Mitigation in Mobile Molecular Communication

In mobile molecular communication (MC), inter-symbol interference (ISI) can be mitigated by power control, requiring accurate estimates of the distance from transmitter to receiver. We present two power control strategies based on binary concentration shift keying (BCSK), namely BCSK with power control based on distance (BCSK-d), and BCSK with power control jointly considering distance and residual molecules in the channel (BCSK-d-RM). Performance of BCSK-d and BCSK-d-RM are analyzed in terms of the bit error rate (BER), the average energy consumption per bit, and the optimal detection threshold. Simulation results show that BCSK-d-RM and BCSK-d outperform BCSK in BER with the varying distance and the number of transmitted molecules. As BCSK-d-RM has higher performance, while BCSK-d has lower complexity, these schemes present a useful design tradeoff for mobile MC.

Harvest-and-Opportunistically-Relay: Analyses on Transmission Outage and Covertness

To enhance transmission performance, privacy level, and energy manipulating efficiency of wireless networks, this article initiates a novel simultaneous wireless information and power transfer (SWIPT) full-duplex (FD) relaying protocol, named harvest-and-opportunistically-relay (HOR). Due to the FD characteristics, the dynamic fluctuation of relay’s residual energy is difficult to quantify and track. To solve this problem, the Markov Chain (MC) theory is invoked. Furthermore, to improve the privacy level of the proposed HOR relaying system, covert transmission performance analysis is performed, where closed-form expressions of the optimal detection threshold and minimum detection error probability are derived. Last but not least, with the aid of stationary distribution of the MC, closed-form expression of transmission outage probability is calculated, based on which transmission outage performance is analyzed. Numerical results have validated the correctness of analyses on transmission outage and covertness. The impacts of key system parameters on the performance of transmission outage and covertness are given and discussed. Based on mathematical analysis and numerical results, we showcase that the proposed HOR model can not only reliably enhance the transmission performance via smartly managing residual energy but also efficiently improve the privacy level of the legitimate transmission party via dynamically adjusting the optimal detection threshold.

Performance Analysis of OFDM With Peak Cancellation Under EVM and ACLR Restrictions

This paper presents performance analysis of an adaptive peak cancellation method to reduce the high peak-toaverage power ratio (PAPR) for OFDM systems, while keeping the out-of-band (OoB) power leakage as well as an in-band distortion power below the pre-determined level. In this work, the increase of adjacent leakage power ratio (ACLR) and error vector magnitude (EVM) are estimated recursively using the detected peak amplitude. We present analytical framework for OFDM-based systems with theoretical bit error rate (BER) representations and detection of optimum peak threshold based on predefined EVM and ACLR requirements. Moreover, the optimum peak detection threshold is selected based on the oretical design to maintain the predefined distortion level. Thus, their degradations are automatically restricted below the pre-defined levels which correspond to target OoB radiation. We also discuss the practical design of peak-cancellation (PC) signal with target OoB radiation and in-band distortion through optimizing the windowing size of the PC signal. Numerical results show the improvements with respect to both achievable bit error rate (BER) and PAPR with the PC method in eigen-beam space division multiplexing (E-SDM) systems under restriction of OoB power radiation. It can also be seen that the theoretical BER shows good agreements with simulation results.

Covert Communications Against an Adversary With Low-SNR Sensing Capability in Nakagami Fading

We show how to achieve covert communications in the presence of a warden equipped with sensing capabilities, even at a low signal to noise ratio (SNR). The warden Willie tries to minimize its false alarm and missed detection probabilities for weak signals. To this end, Willie selects optimal detection threshold for sensing particular legitimate users who want to cover their communication. Our solution to guarantee covertness involves deriving the lower bound for the sum of missed detection and false alarm probabilities, i.e., the mistake at the warden. To hide the message exchange, we derive the conditions for the minimum probability of mistake at Willie to be greater than a threshold. Our simulation results elucidate the roles played by various parameters, such as the number of samples, the target mistake threshold, the amount of noise uncertainty, etc., in undetectable communications over Nakagami fading. Our analysis demonstrates the feasibility of positive-rate hidden communications against a watchful adversary whose receiver is designed to be sensitive to weak SNR.

Resistance-Conferring Mutations on Whole-Genome Sequencing of Fluoroquinolone-resistant and -Susceptible Mycobacterium tuberculosis Isolates: A Proposed Threshold for Identifying Resistance.

Fluoroquinolone resistance in Mycobacterium tuberculosis (Mtb) is conferred by DNA gyrase mutations, but not all fluoroquinolone-resistant Mtb isolates have mutations detected. The optimal allele frequency threshold to identify resistance-conferring mutations by whole-genome sequencing is unknown. Phenotypically ofloxacin-resistant and lineage-matched ofloxacin-susceptible Mtb isolates underwent whole-genome sequencing at an average coverage depth of 868 reads. Polymorphisms within the quinolone-resistance-determining region (QRDR) of gyrA and gyrB were identified. The allele frequency threshold using the Genome Analysis Toolkit pipeline was ~8%; allele-level data identified the predominant variant allele frequency and mutational burden (ie, sum of all variant allele frequencies in the QRDR) in gyrA, gyrB, and gyrA + gyrB for each isolate. Receiver operating characteristic (ROC) curves assessed the optimal measure of allele frequency and potential thresholds for identifying phenotypically resistant isolates. Of 42 ofloxacin-resistant Mtb isolates, area under the ROC curve (AUC) was highest for predominant variant allele frequency, so that measure was used to evaluate optimal mutation detection thresholds. AUCs for 8%, 2.5%, and 0.8% thresholds were 0.8452, 0.9286, and 0.9069, respectively. Sensitivity and specificity were 69% and 100% for 8%, 86% and 100% for 2.5%, 91% and 91% for 0.8%. The sensitivity of the 2.5% and 0.8% thresholds were significantly higher than the 8% threshold (P = .016 and .004, respectively) but not significantly different between one another (P = .5). A predominant mutation allele frequency threshold of 2.5% had the highest AUC for detecting DNA gyrase mutations that confer ofloxacin resistance, and was therefore the optimal threshold.

Do you cov me? Effect of coverage reduction onmetagenome shotgunsequencing studies.

Shotgun metagenomics sequencing is a powerful tool for the characterization of complex biological matrices, enabling analysis of prokaryotic and eukaryotic organisms and viruses in a single experiment, with the possibility of reconstructing de novo the whole metagenome or a set of genes of interest. One of the main factors limiting the use of shotgun metagenomics on wide scale projects is the high cost associated with the approach. We set out to determineif it is possible to use shallow shotgun metagenomics to characterize complex biological matrices while reducing costs. We used a staggered mock community to estimate the optimal threshold for species detection. We measured the variation of several summary statistics simulating a decrease in sequencing depth by randomly subsampling a number of reads. The main statistics that were compared are diversity estimates, species abundance, and ability of reconstructing de novo the metagenome in terms of length and completeness. Our results show that diversity indices of complex prokaryotic, eukaryotic and viral communities can be accurately estimated with 500,000 reads or less, although particularly complex samples may require 1,000,000 reads. On the contrary, any task involving the reconstruction of the metagenome performed poorly, even with the largest simulated subsample (1,000,000 reads). The length of the reconstructed assembly was smaller than the length obtained with the full dataset, and the proportion of conserved genes that were identified in the meta-genome was drastically reduced compared to the full sample. Shallow shotgun metagenomics can be a useful tool to describe the structure of complex matrices, but it is not adequate to reconstruct-even partially-the metagenome.

Censor-Based Cooperative Multi-Antenna Spectrum Sensing with Imperfect Reporting Channels

The present contribution proposes a spectrally efficient censor-based cooperative spectrum sensing (C-CSS) approach in a sustainable cognitive radio network that consists of multiple antenna nodes and experiences imperfect sensing and reporting channels. In this context, exact analytic expressions are first derived for the corresponding probability of detection, probability of false alarm, and secondary throughput, assuming that each secondary user (SU) sends its detection outcome to a fusion center only when it has detected a primary signal. Capitalizing on the findings of the analysis, the effects of critical measures, such as the detection threshold, the number of SUs, and the number of employed antennas, on the overall system performance are also quantified. In addition, the optimal detection threshold for each antenna based on the Neyman-Pearson criterion is derived and useful insights are developed on how to maximize the system throughput with a reduced number of SUs. It is shown that the C-CSS approach provides two distinct benefits compared with the conventional sensing approach, i.e., without censoring: i) the sensing tail problem, which exists in imperfect sensing environments, can be mitigated; and ii) less SUs are ultimately required to obtain higher secondary throughput, rendering the system more sustainable.

Analysis and Design of Two-Hop Diffusion-Based Molecular Communication With Ligand Receptors

This work presents a performance analysis of a decode-and-forward (DF) relay-assisted diffusion-based molecular communication system consisting of one nanotransmitter, one nanoreceiver and one nanotransceiver acting as relay. We consider cases using one molecule in our two-hop relay network (1M2H), and using two molecules (2M2H). Inspired by the biological signal transduction systems, the ligand-receptor binding mechanism is introduced for the receptors on the surface of receiver. Inter-symbol interference (ISI) and self-interference (SI) can be identified as the performance-limiting effects in our relaying network. The number of received molecules can be approximated by the normal distribution, and using this approximation, a closed-form expression of bit error probability for the relay-assisted network is derived. Then, we put forward an optimization problem for minimizing the bit error probability, and solve it using an algorithm based on the gradient descent to find the optimal detection threshold. In addition, the expression of channel capacity is obtained for two-hop molecular communication with ligand receptors. Numerical results show that the 2M2H network has greater capacity than the 1M2H network.

Modeling and Analysis of Spatial Inter-Symbol Interference for RGB Image Sensors Based on Visible Light Communication

In this paper, RGB image sensors based on visible light communication system are designed and researched. In our study, the spatial inter-symbol interference is considered and the formation mechanism of the stray light, the influence of the spatial inter-symbol interference, and the influence of RGB image sensors are analyzed. The mathematics expression of the system signal-to-noise ratio (SNR) and bit error ratio (BER) is given. The simulation result indicates that there is a critical communication distance in the system. Once the communication distance exceeds the critical value, the system BER performance increases sharply. In addition, an adaptive threshold detection method is introduced and the performance is simulated. By means of estimating the spatial inter-symbol interference noise power, the optimal detection threshold can be obtained and the system BER performance increases significantly.

Optimal Transmitted Molecules and Decision Threshold for Drift-Induced Diffusive Molecular Channel With Mobile Nanomachines.

We study a drift-induced diffusive mobile molecular communication system where source, destination and cooperative nanomachines follow the one-dimensional Brownian motion. For information exchange from source nanomachine to receiver nanomachine, both direct and decode-forward (DF) relay-assisted cooperative paths are considered. The closed-form expressions for the probabilities of detection and false alarm are derived at the cooperative and destination nanomachines considering the multiple-source interference (MSI) and the inter-symbol-interference (ISI). The closed-form expressions for end-to-end average probability of error, and maximum achievable rate are also obtained. Moreover, to achieve minimum expected probability of error the optimum number of molecules to be transmitted from transmitter and optimal detection threshold in receiver nanomachine are found. The analytical expressions are validated through particle-based and Monte-Carlo simulation methods.

Primary signal detection algorithms for spectrum sensing at low SNR over fading channels in cognitive radio

The generalized detector (GD) can be implemented at the low signal-to-noise ratio (SNR) in cognitive radio (CR) systems to improve the spectrum sensing performance under correlated antenna array elements. The weighted GD (WGD) and the generalized likelihood ratio test for GD (GLRT-GD) are proposed to be used for coarse spectrum sensing when the noise power is known and unknown, respectively. The GD optimal detection threshold is defined based on the minimum probability of error criterion for various fading channels, namely, the additive white Gaussian noise (AWGN), Nakagami-m, and Rayleigh fading channels. The performance of the proposed algorithms are compared with the spectrum sensing performance of the energy detector (ED), weighted ED (WED), maximum-minimum eigenvalue (MME) detector, generalized likelihood ratio test for ED (GLRT-ED), matched filter (MF), arithmetic to geometric mean (AGM) detector, scaled largest eigenvalue (SLE) detector, moment based detector (MBD), covariance based detector (CBD), and others. The simulation results demonstrate superiority in the spectrum sensing performance of the proposed algorithms in comparison with the above-mentioned detectors. For example, the GLRT-GD achieves the SNR gain equal to 1.2 dB, 4.0 dB, and 4.5 dB in comparison with GLRT-ED, MME, and GM detectors, respectively, at the probability of false alarm PFA=0.1. The WGD and GLRT-GD implementation allows us to achieve a considerable spectrum sensing performance improvement at small number of samples under the low SNR and the correlated antenna array elements.

Offshore Platform Extraction Using RadarSat-2 SAR Imagery: A Two-Parameter CFAR Method Based on Maximum Entropy.

The ability to determine the number and location of offshore platforms is of great significance for offshore oil spill monitoring and offshore oil and gas development. Considering the problem that the detection threshold parameters of the two-parameter constant false alarm rate (CFAR) algorithm require manual and repeated adjustment of the during the extraction of offshore platform targets, this paper proposes a two-parameter CFAR target detection method based on maximum entropy based on information entropy theory. First, a series of threshold parameters are obtained using the two-parameter CFAR algorithm for target detection. Then, according to the maximum entropy principle, the optimal threshold is estimated to obtain the target detection results of the possible offshore platform. Finally, the neighborhood analysis method is used to eliminate false alarm targets such as ships, and the final target of the offshore platform is obtained. In this study, we conducted offshore platform extraction experiments and an accuracy evaluation using data from the Pearl River Estuary Basin of the South China Sea. The results show that the proposed method for platform extraction achieves an accuracy rate of 97.5% and obtains the ideal offshore platform distribution information. Thus, the proposed method can objectively obtain the optimal target detection threshold parameters, greatly reduce the influence of subjective parameter setting on the extraction results during the target detection process and effectively extract offshore platform targets.

Opportunistic Ambient Backscatter Communication in RF-Powered Cognitive Radio Networks

In the present contribution, we propose a novel opportunistic ambient backscatter communication (ABC) framework for radio frequency (RF)-powered cognitive radio (CR) networks. This framework considers opportunistic spectrum sensing (SS) integrated with ABC and harvest-then-transmit (HTT) operation strategies. Novel analytic expressions are derived for the average throughput, the average energy consumption and the energy efficiency (EE) in the considered set up. These expressions are represented in closed-form and have a tractable algebraic representation which renders them convenient to handle both analytically and numerically. In addition, we formulate an optimization problem to maximize the EE of the CR system operating in mixed ABC—and HTT—modes, for a given set of constraints, including primary interference and imperfect SS constraints. Capitalizing on this, we determine the optimal set of parameters which in turn comprise the optimal detection threshold, the optimal degree of trade-off between the CR system operating in the ABC—and HTT—modes and the optimal data transmission time. Extensive results from respective computer simulations are also presented for corroborating the corresponding analytic results and to demonstrate the performance gain of the proposed model in terms of EE.

A game-theoretic approach for selecting optimal time-dependent thresholds for anomaly detection

Adversaries may cause significant damage to smart infrastructure using malicious attacks. To detect and mitigate these attacks before they can cause physical damage, operators can deploy anomaly detection systems (ADS), which can alarm operators to suspicious activities. However, detection thresholds of ADS need to be configured properly, as an oversensitive detector raises a prohibitively large number of false alarms, while an undersensitive detector may miss actual attacks. This is an especially challenging problem in dynamical environments, where the impact of attacks may significantly vary over time. Using a game-theoretic approach, we formulate the problem of computing optimal detection thresholds which minimize both the number of false alarms and the probability of missing actual attacks as a two-player Stackelberg security game. We provide an efficient dynamic programming-based algorithm for solving the game, thereby finding optimal detection thresholds. We analyze the performance of the proposed algorithm and show that its running time scales polynomially as the length of the time horizon of interest increases. In addition, we study the problem of finding optimal thresholds in the presence of both random faults and attacks. Finally, we evaluate our result using a case study of contamination attacks in water networks, and show that our optimal thresholds significantly outperform fixed thresholds that do not consider that the environment is dynamical.

Unilateral left‐tail Anderson Darling test‐based spectrum sensing with Laplacian noise

This paper focuses on spectrum sensing under Laplacian noise. To remit the negative effects caused by heavy-tailed behavior of Laplacian noise, the fractional lower order moments (FLOM) technology is employed to pre-process the received samples before spectrum sensing. Via exploiting the asymmetrical difference between the distribution for the FLOM of received samples in the absence and presence of primary users, we formulate the spectrum sensing problem under Laplacian noise as a unilateral goodness-of-fit (GoF) test problem. Based on this test problem, we propose a new GoF-based detector which is called unilateral left-tail Anderson Darling (ULAD) detector. The analytical expressions for the theoretical performance, in terms of false-alarm and detection probabilities, of the ULAD are derived. Moreover, a closed-form expression for the optimal detection threshold is also derived to minimize the total error rate. Simulation results are provided to validate the theoretical analyses and to demonstrate the superior performance of the proposed detector than others.

Signal Detection for Ambient Backscatter Communication with OFDM Carriers.

Ambient backscatter communication (AmBC) is considered as a promising future emerging technology. Several works on AmBC have been proposed thanks to its convenience and low cost property. This paper focuses on finding the optimal energy detector at the receiver side and estimating the corresponding bit error rate for the communication system utilizing the AmBC. Through theoretical and numerical analyses, we present two important results. First, we improve the existing energy detector by calculating the optimal averaging power orders. Second, we take advantage of the early work on orthogonal frequency division multiplexing (OFDM), where the repeating structure of ambient OFDM signals is exploited to cancel out the direct-link interference by using a cyclic prefix, then provide a test statistic in which optimal detection threshold and optimal power order are derived accordingly. The study reveals the inherent limitation of AmBC energy detectors and provides a guidance for achieving optimal power order for a given significance level.

Proactive Eavesdropping via Covert Pilot Spoofing Attack in Multi-Antenna Systems

Proactive eavesdropping is an effective method for government to monitor suspicious users who are deemed to misuse communication systems for illegal activities. In this paper, considering that a legitimate full-duplex (FD) eavesdropper tries to monitor a dubious multi-antenna system, we propose a covert pilot spoofing attack (PSA) scheme to enhance the legitimate eavesdropping performance by taking the channel training phase into consideration. For the proposed covert PSA scheme, the total error detection probability and optimal detection threshold of suspicious source are derived as the worst case for the considered monitoring system. Given the optimal detection threshold, the closed-form expressions of effective eavesdropping rate are also derived based on the results of detection at suspicious source. Furthermore, an optimal power allocation algorithm to maximize the effective eavesdropping rate is proposed under the covert PSA and transmission power constraints. Simulation results illustrate that the adversary's uncertain about channel state information (CSI) before channel estimation process, can be exploited by legitimate eavesdropper to cover the PSA without being detected. Therefore, the proposed covert PSA scheme can achieve a better performance with respect to effective eavesdropping rate and effectively combat with a suspicious multi-antenna system.