Biblio

{The paper considers the efficiency of an adaptive non-recursive filter using the adjustment algorithm for weighting coefficients taking into account the constant envelope of the desired signal when receiving signals with multi-position phase shift keying against the background of noise and non-fluctuation interference. Two types of such interference are considered - harmonic and retranslated. The optimal filter parameters (adaptation coefficient and length) are determined by using simulation; the effect of the filter on the noise immunity of a quadrature coherent signal receiver with multi-position phase shift keying for different combinations of interference and their intensity is estimated. It is shown that such an adaptive filter can successfully deal with the most dangerous sighting harmonic interference}.

ECG signals are often corrupted by 50 Hz noise, the frequency from the power supply. So it becomes quite necessary to remove Power Line Interference (PLI) from the ECG signal. The reference ECG signal data was taken from the MIT-BIH database. Different filtering techniques comprising of Discrete Wavelet Transform (DWT), Normalized Least Mean Square (NLMS) filter, Finite Impulse Response (FIR) filter and Infinite Impulse Response (IIR) filter were used in this paper for denoising the ECG signal which was corrupted by the PLI. Later, the comparison was made among the methods, to find the best methodology to denoise the corrupted ECG signal. The parameters that were used for the comparison are Mean Square Error (MSE), Mean Absolute Error (MAE), Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR). Higher values of SNR & PSNR and lower values of MSE & MAE define the best denoising algorithm.

Originally implemented by Google, QUIC gathers a growing interest by providing, on top of UDP, the same service as the classical TCP/TLS/HTTP/2 stack. The IETF will finalise the QUIC specification in 2019. A key feature of QUIC is that almost all its packets, including most of its headers, are fully encrypted. This prevents eavesdropping and interferences caused by middleboxes. Thanks to this feature and its clean design, QUIC is easier to extend than TCP. In this paper, we revisit the reliable transmission mechanisms that are included in QUIC. More specifically, we design, implement and evaluate Forward Erasure Correction (FEC) extensions to QUIC. These extensions are mainly intended for high-delays and lossy communications such as In-Flight Communications. Our design includes a generic FEC frame and our implementation supports the XOR, Reed-Solomon and Convolutional RLC error-correcting codes. We also conservatively avoid hindering the loss-based congestion signal by distinguishing the packets that have been received from the packets that have been recovered by the FEC. We evaluate its performance by applying an experimental design covering a wide range of delay and packet loss conditions with reproducible experiments. These confirm that our modular design allows the protocol to adapt to the network conditions. For long data transfers or when the loss rate and delay are small, the FEC overhead negatively impacts the download completion time. However, with high packet loss rates and long delays or smaller files, FEC allows drastically reducing the download completion time by avoiding costly retransmission timeouts. These results show that there is a need to use FEC adaptively to the network conditions.

The main information and communication systems (ICS) effectiveness parameters are: reliability, resiliency, network bandwidth, service quality, profitability and cost, malware protection, information security, etc. Most modern ICS refers to multiuser systems, which implement the most promising method of distributing subscribers (users), namely, the code distribution, at which, subscribers are provided with appropriate forms of discrete sequences (signatures). Since in multiuser systems, channels code division is based on signal difference, then the ICS construction and systems performance indicators are determined by the chosen signals properties. Distributed spectrum technology is the promising direction of information security for telecommunication systems. Currently used data generation and processing methods, as well as the broadband signal classes used as a physical data carrier, are not enough for the necessary level of information security (information secrecy, imitation resistance) as well as noise immunity (impedance reception, structural secrecy) of the necessary (for some ICS applications). In this case, discrete sequences (DS) that are based on nonlinear construction rules and have improved correlation, ensemble and structural properties should be used as DS that extend the spectrum (manipulate carrier frequency). In particular, with the use of such signals as the physical carrier of information or synchronization signals, the time expenditures on the disclosure of the signal structure used are increasing and the setting of "optima", in terms of the counteracting station, obstacles becomes problematic. Complex signals obtained on such sequences basis have structural properties, similar to random (pseudorandom) sequences, as well as necessary correlation and ensemble properties. For designing signals for applications applied for measuring delay time, signal detecting, synchronizing stations and etc, side-lobe levels of autocorrelation function (ACF) minimization is essential. In this paper, the problem of optimizing the synthesis of nonlinear discrete sequences, which have improved ensemble, structural and autocorrelation properties, is formulated and solved. The use of nonlinear discrete signals, which are formed on the basis of such sequences, will provide necessary values for impedance protection, structural and information secrecy of ICS operation. Increased requirements for ICS information security, formation and performance data in terms of internal and external threats (influences), determine objectively existing technical and scientific controversy to be solved is goal of this work.The paper presents the results of solving the actual problem of performance indicators improvements for information and communication systems, in particular secrecy, information security and noise immunity with interfering influences, based on the nonlinear discrete cryptographic signals (CS) new classes synthesis with the necessary properties.

Compressed sensing can represent the sparse signal with a small number of measurements compared to Nyquist-rate samples. Considering the high-complexity of reconstruction algorithms in CS, recently compressive detection is proposed, which performs detection directly in compressive domain without reconstruction. Different from existing work that generally considers the measurements corrupted by dense noises, this paper studies the compressive detection problem when the measurements are corrupted by both dense noises and sparse errors. The sparse errors exist in many practical systems, such as the ones affected by impulse noise or narrowband interference. We derive the theoretical performance of compressive detection when the sparse error is either deterministic or random. The theoretical results are further verified by simulations.

Vehicular ad hoc networks (VANETs) are designed to provide traffic safety by exploiting the inter-vehicular communications. Vehicles build awareness of traffic in their surroundings using information broadcast by other vehicles, such as speed, location and heading, to proactively avoid collisions. The effectiveness of these VANET traffic safety applications is particularly dependent on the accuracy of the location information advertised by each vehicle. Therefore, traffic safety can be compromised when Sybil attackers maliciously advertise false locations or other inaccurate GPS readings are sent. The most effective way to detect a Sybil attack or correct the noise in the GPS readings is localizing vehicles based on the physical features of their transmission signals. The current localization techniques either are designed for networks where the nodes are immobile or suffer from inaccuracy in high-interference environments. In this paper, we present a RSSI-based localization technique that uses mobile nodes for localizing another mobile node and adjusts itself based on the heterogeneous interference levels in the environment. We show via simulation that our localization mechanism is more accurate than the other mechanisms and more resistant to environments with high interference and mobility.

A robust adaptive filtering algorithm based on the convex combination of two adaptive filters under the maximum correntropy criterion (MCC) is proposed. Compared with conventional minimum mean square error (MSE) criterion-based adaptive filtering algorithm, the MCC-based algorithm shows a better robustness against impulsive interference. However, its major drawback is the conflicting requirements between convergence speed and steady-state mean square error. In this letter, we use the convex combination method to overcome the tradeoff problem. Instead of minimizing the squared error to update the mixing parameter in conventional convex combination scheme, the method of maximizing the correntropy is introduced to make the proposed algorithm more robust against impulsive interference. Additionally, we report a novel weight transfer method to further improve the tracking performance. The good performance in terms of convergence rate and steady-state mean square error is demonstrated in plant identification scenarios that include impulsive interference and abrupt changes.

In adaptive processing applications, the design of the adaptive filter requires estimation of the unknown interference-plus-noise covariance matrix from secondary training data. The presence of outliers in the training data can severely degrade the performance of adaptive processing. By exploiting the sparse prior of the outliers, a Bayesian framework to develop a computationally efficient outlier-resistant adaptive filter based on sparse Bayesian learning (SBL) is proposed. The expectation-maximisation (EM) algorithm is used therein to obtain a maximum a posteriori (MAP) estimate of the interference-plus-noise covariance matrix. Numerical simulations demonstrate the superiority of the proposed method over existing methods.

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interference-limited communications considered in prior works, we propose active cooperative relaying based schemes. We consider a network with nl legitimate nodes and ne eavesdroppers, and path loss exponent α ≥ 2. As long as ne2(log(ne))γ = o(nl) holds for some positive γ, we show one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given a fixed total power constraint for the entire network. We achieve this result with (i) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays, and (ii) the relays acting as a virtual multi-antenna to apply beamforming against the eavesdroppers. Our simpler parallel (two-stage) relaying scheme can achieve the same unbounded secure aggregate rate when neα/2 + 1 (log(ne))γ+δ(α/2+1) = o(nl) holds, for some positive γ, δ.