Interference Statistics Research Articles

Multi-UAV adaptive super-twisting integral terminal sliding mode formation control

This paper addresses issues such as model uncertainties, actuator failures, and gust disturbances in multi-quadrotor UAV formation flight. An adaptive super-twisting integral terminal sliding mode control method is proposed, incorporating a ‘Leader-Follower’ formation control strategy. The approach includes designing an adaptive super-twisting integral terminal sliding mode controller and a formation adaptive cooperative controller. Additionally, adaptive gains are utilized to manage the effects of actuator failures, gust disturbances, and ground station interference, ensuring safe formation flight. Simulation and experimental results indicate that the proposed controller can track the target trajectory within a finite time and effectively maintain formation flight.

Measuring statistics-induced entanglement entropy with a Hong–Ou–Mandel interferometer

Despite its ubiquity in quantum computation and quantum information, a universally applicable definition of quantum entanglement remains elusive. The challenge is further accentuated when entanglement is associated with other key themes, e.g., quantum interference and quantum statistics. Here, we introduce two novel motifs that characterize the interplay of entanglement and quantum statistics: an ‘entanglement pointer’ and a ‘statistics-induced entanglement entropy’. The two provide a quantitative description of the statistics-induced entanglement: (i) they are finite only in the presence of quantum entanglement underlined by quantum statistics and (ii) their explicit form depends on the quantum statistics of the particles (e.g., fermions, bosons, and anyons). We have experimentally implemented these ideas by employing an electronic Hong–Ou–Mandel interferometer fed by two highly diluted electron beams in an integer quantum Hall platform. Performing measurements of auto-correlation and cross-correlation of current fluctuations of the scattered beams (following ‘collisions’), we quantify the statistics-induced entanglement by experimentally accessing the entanglement pointer and the statistics-induced entanglement entropy. Our theoretical and experimental approaches pave the way to study entanglement in various correlated platforms, e.g., those involving anyonic Abelian and non-Abelian states.

Assessment of Radio-Frequency Radiation Exposure from Selected Mobile Base Stations in Yenagoa, Bayelsa State, Nigeria

The antennas from mobile base stations radiate non-ionizing radio frequency radiation into space. The human body can experience negative health effects from prolonged exposure to radiofrequency (RF) radiation. Because base station installations and telecommunication networks are growing, there is a growing need to address the health risks connected with exposure to telecommunication masts. Using the Electrosmog Meter Cornet Model, power density from many telecom masts owned by various network operators was measured in this investigation. At 10-meter intervals, the RF radiation in seven (7) settlements in Yenagoa town, located in the Yenagoa Local Government Area of Bayelsa State, was measured within radial distances of 100 meters. With a mean value of 4.0569mWm-2, the measured values vary from 0.650mWm-2 to 9.810mWm-2. Still, values evolved. Nevertheless, additional factors, such as adjacent electromagnetic sources' wave interference or reference base station interference, caused readings to fluctuate. It was discovered that the greatest power density level was 9.810 mWm-2, and it was measured 20 meters away from the base station at site MBS1. As per the International Commission on Non-ionizing Radiation Protection (ICNIRP) and other regulatory authorities, the standard limit of 4.5Wm-2 for the 900 MHz system is not exceeded by the radiation exposure level, as the findings show. This shows that the exposure levels in these areas are low enough to not seriously jeopardize the health of those living in the research area.

The Analysis and Verification of IMT-2000 Base Station Interference Characteristics in the FAST Radio Quiet Zone

In this study, we aim to analyze the electromagnetic interference (EMI) regarding the Five-hundred-meter Aperture Spherical radio Telescope (FAST) caused by base stations in the International Mobile Telecommunications-2000 (IMT-2000) frequency band. By analyzing the frequency bands used by the transmitting and receiving devices and the surrounding environmental parameters and utilizing an approach to predicting radio wave propagation loss that is based on deterministic methods, we conclude by comparing the predicted received power at the FAST with its interference protection threshold. Our analysis demonstrates that, currently, only 55.31% of IMT-2000 base stations in the FAST radio quiet zone (RQZ) meet the protection threshold. Additionally, this article verifies the applicability and accuracy of the radio wave propagation model used in the research based on field strength measurements. Overall, this study provides valuable insights for improving the electromagnetic environment surrounding FAST and reducing the EMI caused by mobile communication base stations. It also provides corresponding analysis methods and useful suggestions for analyzing electromagnetic radiation interference in other radio telescopes.

Sensorless control of marine permanent magnet synchronous propulsion motor based on adaptive extended Kalman filter

Gross error interference or noise statistical deviation is the main factor that leads to the accuracy deterioration of extended Kalman filter (EKF) in estimating the speed and rotor position of ship propulsion permanent magnet synchronous motor (PMSM). In this paper, an adaptive extended Kalman filter (AEKF) algorithm based on innovation sequence is proposed. In the proposed method, gross error interference is first added to EKF to analyze its influence on the observation accuracy. Then, the weighting coefficient is set in the calculation of innovation covariance. By adjusting the weight of the innovation covariance matrix at the adjacent time, the innovation covariance difference is calculated and then used in the calculation of Kalman gain. The observation performance comparison between AEKF and EKF strategies is conducted with subject to gross error interference and noise statistics deviate. Simulation and experimental results demonstrate that the proposed AEKF has stronger robustness and higher prediction accuracy of speed and rotor position.

Effect of Number of Interference on Long-Term Evolution Throughput with Minimum Mean Square Error-Interference Rejection Combining Receiver

Different interference measurement methodologies for the Narrowband Internet of Things network are depicted and examined in this article. The Co-Channel Interference is a unit of the master exporter of interference, which happens mostly because of the frequency reuse concept. Co-Channel Interference has a stronger influence in Code Division Multiple Access based approaches since the frequency reuse ratio in those systems is identical. The impact of various interference measurement methodologies on Narrowband Internet of Things link adaptability and throughput performance is investigated. Different interference measuring approaches are described, and evaluated, their core process ideas, including technique overhead aspects, are reviewed, and an itemized performance assessment and comparison is made. In order to reduce the effects of interference signals and increase user throughput, Minimum Mean Square Error-Interference Rejection Combining receivers are deployed as a mobile station interference rejection and inhibition technology. The presented data show that one interference approach outperforms the others in terms of throughput.

Distribution of Depression Among Different Groups and Sub-Groups of Women During the Covid Pandemic an Analysis from an Interdisciplinary Perspective

Objective. In this article, we analyze depression in the female population using interference and descriptive statistics applied to multiple groups and subgroups to better understand depression in the population (pregnant, not pregnant, and newly mothers-6 to 8 weeks) and also analyzing the perspective of suicide during the COVID-19 pandemic. Thus, depending on the analyzed perspective, we have from 2 to 6 study groups. <br />Methods. The analysis was done by applying the Edinburgh Postnatal Depression Scale (EPDS) questionnaire in groups of pregnant women during pregnancy and new mothers (six to eight weeks after birth) and Beck Depression Inventory BDI in all the groups. <br />Results. According to forecasts, all hypothesis where validated . Conclusions: An immediate priority of the scientific community should be collecting high-quality data on the mental health effects of the COVID-19 pandemic across the whole population and especially vulnerable groups such as that of pregnant women who were presented in this study.

Radio Frequency Interference Mitigation and Statistics in the Spectral Observations of FAST

In radio astronomy, radio frequency interference (RFI) becomes more and more serious for radio observational facilities. The RFI always influences the search and study of the interesting astronomical objects. Mitigating the RFI becomes an essential procedure in any survey data processing. The Five-hundred-meter Aperture Spherical radio Telescope (FAST) is an extremely sensitive radio telescope. It is necessary to find out an effective and precise RFI mitigation method for FAST data processing. In this work, we introduce a method to mitigate the RFI in FAST spectral observation and make a statistic for the RFI using ∼300 h FAST data. The details are as follows. First, according to the characteristics of FAST spectra, we propose to use the Asymmetrically Reweighted Penalized Least Squares algorithm for baseline fitting. Our test results show that it has a good performance. Second, we flag the RFI with four strategies, which are to flag extremely strong RFI, flag long-lasting RFI, flag polarized RFI, and flag beam-combined RFI, respectively. The test results show that all the RFI above a preset threshold could be flagged. Third, we make a statistic for the probabilities of polarized XX and YY RFI in FAST observations. The statistical results could tell us which frequencies are relatively quiescent. With such statistical data, we are able to avoid using such frequencies in our spectral observations. Finally, based on the ∼300 h FAST data, we obtained an RFI table, which is the most complete database currently for FAST.

A SIC-Based BS Coordination Scheme for Full Duplex Cellular Networks

Full Duplex (FD) in cellular networks is expected to increase the cell spectral efficiency. However, while the downlink (DL) spectral efficiency (SE) increases with FD, the uplink (UL) SE decreases because of the Base Station to Base Station (BS) interference. In this paper, assuming a three-node model, we propose a method based on Successive Interference Cancellation (SIC) to reduce the BS-to-BS interference present in FD cellular networks. The approach consists in coordinating BSs to enable the decoding and the suppression of undesired signals that impair uplink transmissions. We analyze both distributed and Centralized Radio Access Networks (CRAN) architectures. Stochastic geometry is used to derive the coverage probability and mean data rate of the proposed scheme. In the distributed scenario, the FD UL average data rate is increased by 25% with our solution compared to a classical FD network, while our FD scheme still outperforms Half-Duplex (HD) on the DL. In the centralized scenario, our solution outperforms HD by 10% and classical FD by 78% on the UL, while preserving classical FD gains on the DL.

Performance Analysis of Random Access Mechanism in 5G Millimeter Wave Networks: Effect of Blockage, Shadowing and Mobility

5G NR has gained importance in academic and industrial research communities in recent times as its millimetre wave (mmWave) band operations offer a promising alternative for next-generation wireless communications. However, the susceptibility of mmWave signals to severe path loss and shadowing requires the use of highly directional antennas. Since the narrow beams are vulnerable to blockages, the interference behaviour becomes the key factor in building the network. In this paper, we propose a blockage model by considering the distribution of buildings in the cell as a Poisson point process. We analytically derive the blockage probability using the queuing theory. Subsequently, we derive the interference statistics using the blockage model considering the spatial randomness of the locations of blockages and User Equipments (UEs). We define and derive the coverage probability of a UE depending on the interference statistics. We calculate the success probability of a preamble transmission of a UE subjected its coverage. The effect of mobility on blockage, coverage and preamble success probability has been presented through extensive simulations.

Quantum control of reactions and collisions at ultralow temperatures.

At temperatures close to absolute zero, the molecular reactions and collisions are dominantly governed by quantum mechanics. Remarkable quantum phenomena such as quantum tunneling, quantum threshold behavior, quantum resonances, quantum interference, and quantum statistics are expected to be the main features in ultracold reactions and collisions. Ultracold molecules offer great opportunities and challenges in the study of these intriguing quantum phenomena in molecular processes. In this article, we review the recent progress in the preparation of ultracold molecules and the study of ultracold reactions and collisions using ultracold molecules. We focus on the controlled ultracold chemistry and the scattering resonances at ultralow temperatures. The challenges in understanding the complex ultracold reactions and collisions are also discussed.

Automotive interference statistics and their effect on radar detector

Millimetre-wave frequency-modulated continuous wave (FMCW) radars are at present widely deployed in the autonomous vehicles. The growing usage of such sensors, as a vital part of a robust future autonomous sensing system, sees the potential for significant increase in mutual interference and adverse effects on sensor operation. Effective target detection in the background of interference requires knowledge of the interference statistics. In the case that such statistics are found to be similar to that of additive white Gaussian noise (AWGN), then classical well-established detection techniques can be applied. Conversely, if statistics are found to be different, traditional techniques (matched filtering) will not be optimal. Here, a statistical analysis of mutual interference within an FMCW victim radar is presented. The majority of cases show a low correlation between the interference pulses received at the victim radar, with close to a Gaussian distribution. Some specific cases show a high correlation between the interference pulses in the victim radar chirps with a sinusoidal-like distribution, which degrades the victim radar’s detection performance. The presented analysis is validated by experimental data for various interference cases.

Adaptive Channel Hopping for IEEE 802.15.4 TSCH-Based Networks: A Dynamic Bernoulli Bandit Approach

In IEEE 802.15.4 standard for low-power low-range wireless communications, only one channel is employed for transmission which can result in increased energy consumption, high network delay and poor packet delivery ratio (PDR). In the subsequent IEEE 802.15.4-2015 standard, a Time-slotted Channel Hopping (TSCH) mechanism has been developed which allows for a periodic yet fixed frequency hopping pattern over 16 different channels. Unfortunately, however, most of these channels are susceptible to high-power coexisting Wi-Fi signal interference and to possibly some other ISM-band transmissions. This interference manifests itself in the form of the presence/absence of other devices with either or both static and dynamic channel selection policies. In order to isolate channels with undesirable conditions, blacklisting mechanisms are defined to adapt the channel hopping process. However, the existing solutions which form blacklists unrealistically assume that the statistical model of the external interference remains fixed, and do not vary over time. In this paper, we realistically assume that the impact of external interferes on 802.15.4 may generally follow a non-stationary pattern, and accordingly formulate the adaptive channel hopping problem as a Dynamic Multi-Armed Bernoulli Bandit (Dynamic MABB) process from the machine learning theory. We then propose an online learning algorithm with track-ability properties for computing an adaptive hopping policy. Simulations confirm that when the statistics of the external interference has a switching regime, the proposed solution outperforms the previous schemes in terms of both energy efficiency as well as two important KPIs for TSCH-based networks, i.e., PDR and latency.

Interference Analysis for mmWave Automotive Radar Considering Blockage Effect.

Due to the increasing number of vehicles equipped with millimeter wave (mmWave) radars, interference among automotive radars is becoming a major issue. This paper explores the automotive radar interference in both two-lane and multi-lane scenarios using stochastic geometry. We derive closed-form expressions for mean and variance of interference power considering directional antenna with constant and Gaussian decaying gains. In view of the sensitivity of mmWave radar signals to the blockages, we propose a blockage model including partially and completely blocking, and then calculate the effective number of the interferers. By means of modeling randomness for interferers and blockages as Poisson point process, we characterize the statistics of radar interference under different conditions. We further utilize the interference characterization to estimate the successful ranging probability of automotive radars. These theoretical analyses are verified by using Monte Carlo simulations. The results show that the increasing interfering density and ranging distance largely degrade the radar detection performance, whereas the interference levels decrease as blockage intensity increases.

Influence of Chirp, Jitter, and Relaxation Oscillations on Probabilistic Properties of Laser Pulse Interference

Interference of laser pulses is an essential ingredient of quantum randomness; therefore, probabilistic properties of laser pulses gains new relevance. Here, we consider in detail the combined influence of the three effects – chirp, jitter and relaxation oscillations – on the probability density function of the interference of pulses from a gain-switched semiconductor laser. We develop a rigorous model based on laser rate equations and demonstrate that only consideration of all these three effects together allows describing the interference statistics properly. We supplement our theoretical calculations with corresponding measurements at various pump currents. Experimental results demonstrate perfect agreement with predictions of the model and are well reproduced by Monte-Carlo simulations.

A Full Second-Order Analysis of the Widely Linear MVDR Beamformer for Noncircular Signals

A full performance analysis of the widely linear (WL) minimum variance distortionless response (MVDR) beamformer is introduced. While the WL MVDR is known to outperform its strictly linear counterpart, the Capon beamformer, for noncircular complex signals, the existing approaches provide limited physical insights, since they explicitly or implicitly omit the complementary second-order (SO) statistics of the output interferences and noise (IN). To this end, we exploit the full SO statistics of the output IN to introduce a full SO performance analysis framework for the WL MVDR beamformer. This makes it possible to separate the overall signal-to-interference plus noise ratio (SINR) gain of the WL MVDR beamformer w.r.t. the Capon one into the individual contributions along the in-phase (I) and quadrature (Q) channels. Next, by considering the reception of the unknown signal of interest (SOI) corrupted by an arbitrary number of orthogonal noncircular interferences, we further unveil the distribution of SINR gains in both the I and Q channels, and show that in almost all the spatial cases, these performance advantages are more pronounced when the SO noncircularity rate of the interferences increases. Illustrative numerical simulations are provided to support the theoretical results.

Space-Time Adaptive Detection at Low Sample Support

An important problem in space-time adaptive detection is the estimation of the large p-by-p interference covariance matrix from training signals. When the number of training signals n is greater than 2p, existing estimators are generally considered to be adequate, as demonstrated by fixed-dimensional asymptotics. But in the low-sample-support regime (n < 2p or even n < p) fixed-dimensional asymptotics are no longer applicable. The remedy undertaken in this paper is to consider the "large dimensional limit" in which n and p go to infinity together. In this asymptotic regime, a new type of estimator is defined (Definition 2), shown to exist (Theorem 1), and shown to be detection-theoretically ideal (Theorem 2). Further, asymptotic conditional detection and false-alarm rates of filters formed from this type of estimator are characterized (Theorems 3 and 4) and shown to depend only on data that is given, even for non-Gaussian interference statistics. The paper concludes with several Monte Carlo simulations that compare the performance of the estimator in Theorem 1 to the predictions of Theorems 2-4, showing in particular higher detection probability than Steiner and Gerlach's Fast Maximum Likelihood estimator.

Experimental Evidence for Heavy Tailed Interference in the IoT

5G and beyond sees an ever increasing density of connected things. As not all devices are coordinated, there are limited opportunities to mitigate interference. As such, it is crucial to characterize the interference in order to understand its impact on coding, waveform and receiver design. While a number of theoretical models have been developed for the interference statistics in communications for the IoT, there is very little experimental validation. In this letter, we address this key gap in understanding by performing statistical analysis on recent measurements in the unlicensed 863 MHz to 870 MHz band in different regions of Aalborg, Denmark. In particular, we show that the measurement data suggests the distribution of the interference power is heavy tailed, confirming predictions from theoretical models.

Semi-Blind Post-Equalizer SINR Estimation and Dual CSI Feedback for Radar-Cellular Coexistence

Current cellular systems use pilot-aided statistical-channel state information (S-CSI) estimation and limited feedback schemes to aid in link adaptation and scheduling decisions. However, in the presence of pulsed radar signals, pilot-aided S-CSI is inaccurate since interference statistics on pilot and non-pilot resources can be different. Moreover, the channel will be bimodal as a result of the periodic interference. In this paper, we propose a max-min heuristic to estimate the post-equalizer SINR in the case of non-pilot pulsed radar interference, and characterize its distribution as a function of noise variance and interference power. We observe that the proposed heuristic incurs low computational complexity, and is robust beyond a certain SINR threshold for different modulation schemes, especially for QPSK. This enables us to develop a comprehensive semi-blind framework to estimate the wideband SINR metric that is commonly used for S-CSI quantization in 3GPP Long-Term Evolution (LTE) and New Radio (NR) networks. Finally, we propose dual CSI feedback for practical radar-cellular spectrum sharing, to enable accurate CSI acquisition in the bimodal channel. We demonstrate significant improvements in throughput, block error rate and retransmission-induced latency for LTE-Advanced Pro when compared to conventional pilot-aided S-CSI estimation and limited feedback schemes.

Computationally-Efficient Algorithm for Real-Time Absence Seizure Detection in Wearable Electroencephalography.

Advances in electroencephalography (EEG) equipment now allow monitoring of people with epilepsy in their daily-life environment. The large volumes of data that can be collected from long-term out-of-clinic monitoring require novel algorithms to process the recordings on board of the device to identify and log or transmit only relevant data epochs. Existing seizure-detection algorithms are generally designed for post-processing purposes, so that memory and computing power are rarely considered as constraints. We propose a novel multi-channel EEG signal processing method for automated absence seizure detection which is specifically designed to run on a microcontroller with minimal memory and processing power. It is based on a linear multi-channel filter that is precomputed offline in a data-driven fashion based on the spatial-temporal signature of the seizure and peak interference statistics. At run-time, the algorithm requires only standard linear filtering operations, which are cheap and efficient to compute, in particular on microcontrollers with a multiply-accumulate unit (MAC). For validation, a dataset of eight patients with juvenile absence epilepsy was collected. Patients were equipped with a 20-channel mobile EEG unit and discharged for a day-long recording. The algorithm achieves a median of 0.5 false detections per day at 95% sensitivity. We compare our algorithm with state-of-the-art absence seizure detection algorithms and conclude it performs on par with these at a much lower computational cost.