Noise Channel Research Articles

An improved robust algorithm for optimisation-based colour medical image watermarking

Recently, significant attention has been focused on copyright protection of medical images, causing watermarking to become a prevalent research topic. In this paper, we propose an optimisation-based robust watermarking algorithm for the copyright protection of colour medical images. Initially, we decompose a host medical image by lifting wavelet transform (LWT), followed by discrete cosine transform (DCT) into transformed coefficients, and then embed multiple watermarks into the transformed host image by using hybrid optimisation algorithms. To further improve security and reduce the channel noise distortion, we then apply hashing and Hamming code to image and text mark, respectively, before the embedding process. Finally, we utilise 2D chaotic map to encrypt the marked media, aiming to achieve enhanced security and confidentiality. The experimental outcome shows satisfactory invisibility, watermark payload and robustness against image-processing attacks. Furthermore, through numerous comparative experiments with nine state-of-the-art algorithms on two standard datasets, the effectiveness of the proposed algorithm is demonstrated.

Polar code-based secure transmission with higher message rate combining channel entropy and computational entropy

The existing physical layer security schemes, which are based on the key generation model and the wire-tap channel model, achieve security by utilizing channel reciprocity entropy and noise entropy, respectively. In contrast, we propose a novel secure transmission framework that combines noise entropy with reciprocity entropy, achieved by inserting reciprocity entropy into the frozen bits of polar codes. Note that in real-world scenarios, when eavesdroppers employ polynomial-time attacks, the bit error rate (BER) increases due to the introduction of computational entropy. To achieve indistinguishability security, we convert the practical physical layer security metric, BER, into the average min-entropy, a widely accepted concept in cryptography. The simulation results demonstrate that the eavesdropper’s BER can be significantly increased without compromising the communication performance of the legitimate receiver. Under concrete parameters we selected, when compared to the joint scheme of physical layer key generation and one time pad, the modular semantically-secure scheme based on the wire-tap channel model, and the simple channel entropy combination scheme, our scheme achieves a message rate approximately 1.2 times, 3.8 times, and 1.4 times better, respectively. Experimental testing validates the feasibility of our scheme.

A generic quantum Wielandt's inequality

Quantum Wielandt's inequality gives an optimal upper bound on the minimal length k such that length-k products of elements in a generating system span Mn(C). It is conjectured that k should be of order O(n2) in general. In this paper, we give an overview of how the question has been studied in the literature so far and its relation to a classical question in linear algebra, namely the length of the algebra Mn(C). We provide a generic version of quantum Wielandt's inequality, which gives the optimal length with probability one. More specifically, we prove based on [KS16] that k generically is of order Θ(log⁡n), as opposed to the general case, in which the best bound to date is O(n2log⁡n). Our result implies a new bound on the primitivity index of a random quantum channel. Furthermore, we shed new light on a long-standing open problem for Projected Entangled Pair State, by concluding that almost any translation-invariant PEPS (in particular, Matrix Product State) with periodic boundary conditions on a grid with side length of order Ω(log⁡n) is the unique ground state of a local Hamiltonian. We observe similar characteristics for matrix Lie algebras and provide numerical results for random Lie-generating systems.

Comparative analysis of coding schemes for effective wireless communication

Communication systems have recently focused on sending information efficiently and effectively from one sending point to another across a communication channel in the shortest amount of time. The main objective of this work is to compare the high-range coding scheme types, such as low density parity check (LDPC), turbo, and convolution, to see which works better and is more efficient. to establish a coding system with quadrature amplitude modulation (QAM) modulation and an additive white gaussian noise (AWGN) noisy channel to find which is more reliable and resilient for encoding and decoding. Because of this, digital media has to be sent over wireless channels and through satellites, requiring a connected network all the time, which has become a major concern over time. Furthermore, the high amount of data and efficiency are the focus points. After running the simulation, it was found that 64 QAM with a rate of 0.455 and an efficiency of 2.731 has a bit error rate (BER) of 0.001 and a 7.08 dB energy per bit Eb/No, and the 256 QAM simulation revealed that it has a BER of 0.001 and 11.88 dB Eb/No with a rate of 0.736 and an efficiency of 5.891. Over the AWGN channel noise, the simulation built a standard orthogonal frequency division multiplexing (OFDM) system, which used MATLAB.

Cross layered adaptive rate optimized irregular LDPC for WSN

This paper proposes a cross layered adaptive rate optimized technique that uses irregular low-density parity-check (LDPC) codes over an additive white Gaussian noise (AWGN) channel in wireless sensor networks (WSNs). Irregular LDPC is used as error control code. Cross layer design along with error control code gives the energy balance in the network. This new algorithm uses the physical layer parameters such as coherence time of the channel, BER and SNR and the routing layer parameter such as demanded data rate to determine the rate of the LDPC coder. The algorithm adaptively changes the code rates as ¾, ½, and 1/3. We have conducted the simulations to verify our methods using MATLAB and find that the proposed scheme increases the network performance in terms of energy balance and quality of data by using irregular LDPC codes in the cross-layer environment.

A comprehensive perspective for single-mode Gaussian coherence

In this work, we theoretically investigate single-mode Gaussian quantum coherence from a comprehensive perspective. Based on analytical expressions of the first and second moments of single-mode Gaussian states undergoing various Gaussian noisy channels, we use quantum mater equation and the method of the relative entropy to quantify the quantum coherence of any single-mode Gaussian state. We demonstrate that the displaced thermal state achieves maximum quantum coherence when using only the displaced vacuum state, which is a pure coherent state. However, for various lossy noise channels, quantum coherence shows a significant decrease. In the context of a squeezed thermal state, when controlling the squeezing parameter for a given environmental temperature, quantum coherence has been witnessed to increase. The ultimate upper bound of quantum coherence is then attained with the squeezed vacuum state. In particular, we determined the most generalized scenario of the displaced squeezed thermal state. The maximum value of quantum coherence is obtained when displacement and squeeze parameters both attain maximum value. Our study might be important in the future for the characterisation as well as the estimation of various nonclassical quantum correlations in single-mode Gaussian states.

Minimizing Task Age upon Decision for Low-Latency MEC Networks Task Offloading with Action-Masked Deep Reinforcement Learning.

In this paper, we consider a low-latency Mobile Edge Computing (MEC) network where multiple User Equipment (UE) wirelessly reports to a decision-making edge server. At the same time, the transmissions are operated with Finite Blocklength (FBL) codes to achieve low-latency transmission. We introduce the task of Age upon Decision (AuD) aimed at the timeliness of tasks used for decision-making, which highlights the timeliness of the information at decision-making moments. For the case in which dynamic task generation and random fading channels are considered, we provide a task AuD minimization design by jointly selecting UE and allocating blocklength. In particular, to solve the task AuD minimization problem, we transform the optimization problem to a Markov Decision Process problem and propose an Error Probability-Controlled Action-Masked Proximal Policy Optimization (EMPPO) algorithm. Via simulation, we show that the proposed design achieves a lower AuD than baseline methods across various network conditions, especially in scenarios with significant channel Signal-to-Noise Ratio (SNR) differences and low average SNR, which shows the robustness of EMPPO and its potential for real-time applications.

Performance analysis of two-way multi-users cooperative communication system based on GSPIM-DCSK scheme

Based on the Joint Grouping Subcarrier-Permutation Index Modulation-DCSK (GSPIM-DCSK) system, we provide a new two-way multi-user half-duplex cooperative communication system in this work. Given its many benefits, the GSPIM-DCSK modulation is specifically selected as a choice for network coding techniques. A permutation index is used in the GSPIM-DCSK system to incorporate additional data bits with the modulating and carrier index bits. Establishing a cooperative multiuser system where users attempt to make contact with one another over a common relay is the main goal of this effort. Multi-user nodes and a single relay with a cooperative operator on staff for decoding and forwarding make up this system. To avoid interference from other users, the user’s nodes multiplex across various time intervals. We derive analytical expressions for the average bit error rate (BER) of the GSPIM-DCSK multi-user cooperative communication system in the presence of additive white Gaussian noise (AWGN) and multiple paths Rayleigh fading channels. The analytical and simulated average BER findings have been contrasted to verify the accurateness of the average BER analysis. Additionally, a comparison is presented between the average bit error rate (BER) performance of a novel GSPIM-DCSK cooperative system and an established DCSK cooperative system. The throughput and link spectral efficiency of this novel cooperative system are analyzed and compared with those of existing traditional cooperative systems. For the two-way two-user cooperative system, this comparison is done with two-way two-user systems like DCSK-CC and one-way cooperative system based on CIM-SR-DCSK-CC; for the two-way three-user cooperative system, it is done with scheme1 and scheme2. To compare and assess the performance of various systems, simulation results are employed. Furthermore, an analysis demonstrates how the proposed cooperative system, when combined with GSPIM-DCSK techniques, improves the efficiency of conventional cooperative DCSK systems.

End-to-end learning of adaptive coded modulation schemes for resilient wireless communications

Adaptive modulation and coding schemes play a crucial role in ensuring robust data transfer in wireless communications, especially when faced with changes or interference in the transmission channel. These schemes involve the use of variable coding rates, which can be achieved normally through code puncturing or shortening, and have been adopted in 4G and 5G communication standards. In recent works, auto-encoders for wireless communications have demonstrated the ability to learn short code representations that achieve gains over conventional codes. Such a methodology is attractive as it can learn optimal representations under a variety of channel conditions. However, due to its structure the auto-encoder does not currently support multiple code rates with a single model. This article draws upon the discipline of multi-task learning, as it applies to deep learning and therefore devises a branching architecture for the auto-encoder and custom training algorithm in training transmitter and receiver for adaptive modulation and coding. In this article we aim to demonstrate improvements in Block Error Rate over conventional methods in the Additive White Gaussian Noise channel, and to analyse the performance of the model under Rayleigh fading channels without retraining the auto-encoder on the new channel. This article demonstrates a novel approach towards training auto-encoder models to jointly learn adaptive modulation and coding schemes framed as a multi-task learning problem. The research outcomes extend end-to-end learning approaches to the design of adaptive wireless communications systems.

A Temporal Methodology for Assessing the Performance of Concatenated Codes in OFDM Systems for 4K-UHD Video Transmission

The communication channel is a critical part of the process of information degradation. In the 4K ultra-resolution video transmission domain, the communication channel is a crucial part where information degradation occurs, inevitably leading to errors during reception. To enhance the transmission process in terms of fidelity, advanced technologies such as digital video broadcasting terrestrial (DVB-T) and its evolutionary successor, digital video broadcasting terrestrial second generation (DVB-T2), are utilized to mitigate the effects of data transmission errors. Within this scenario, this research presents an innovative methodology for the temporal analysis of 4K ultra-resolution video quality under the influence of additive white Gaussian noise (AWGN) and Rayleigh channels. This analytical endeavor is facilitated through the application of concatenated coding schemes, specifically, the Bose–Chaudhuri–Hocquenghem concatenated low-density parity check (BCH-LDPC) and Reed–Solomon concatenated convolutional (RS-CONV) coders. A more comprehensive understanding of video quality can be attained by considering its temporal variations, a crucial aspect of the ongoing evolution of technological paradigms. In this study, the Structural Similarity Index (SSIM) serves as the main metric for quality assessment during simulations. Furthermore, the simulated Peak Signal-to-Noise Ratio (PSNR) values validate these findings, exhibiting consistent alignment with the SSIM-based evaluations. Additionally, the performance of the BCH-LDPC significantly outperforms that of RS-CONV under the 64-QAM modulation scheme, yielding superior video quality levels that approximate or surpass those achieved by RS-CONV under QPSK (Quadrature Phase Shift Keying) modulation, leading to an increase in spectral efficiency. This enhancement is evidenced by SSIM gains exceeding 78% on average. The computation of average gains between distinct technologies in video quality analysis furnishes a robust and comprehensive evaluation framework, empowering stakeholders to make informed decisions within this domain.

Evaluating Puncture and Non-puncture for the Turbo Code Model based the on AWGN Channel with 16-QAM

In general, a 5G new radio network is defined by three primary utilization situations, namely upgraded versatile broadband, ultra-reliable, and low latency interchanges of information, as well as huge machine-type correspondences. These utilizations require improved throughput, inertness, dependability contrasted, and a 4G framework. As a coding plan for information, 5G Turbo codes attain high throughput, a variable code rate, and length, and crossover programmed rehash with good error-detecting capability. The execution boundaries of 5G advancements are normal and are tens and thousands of times better compared with 4G. In this paper, the evaluations of puncturing and non-puncturing for turbo code depending on the minimization of penetrating of efficient pieces are discussed. It also provides penetrating of equality pieces considering additive white Gaussian noise (AWGN) Channel with 16 quadrature amplitude modulation (QAM) to attain high spectral efficiency. In addition to this, the super encoder encodes the separated progression with a code speed of 1/3. The code block association progressively connects the yields from the super encoder. The sign mapper employed in this paper adjusts the progression using a 16-QAM balance. Also, the mapper takes effective pieces, one uniformity bit from the upper encoder, and the deinterleaved equity bit from the base encoder. The Orthogonal frequency-division multiplexing (OFDM) mapper parts into more modest equivalent channels, named subcarriers and the information is sent on these equivalent channels at a reduced rate.

Bipolar valued probabilistic hesitant fuzzy sets based on Generalized Hybrid Operators in multi-criteria decision-making problems based on TOPSIS

This paper aims to present Bipolar valued probabilistic hesitant fuzzy sets (BVPHFSs) by combining bipolar fuzzy sets and probabilistic hesitant fuzzy sets (PHFSs). PHFSs are a strong version of hesitant fuzzy sets (HFSs) in terms of evaluated as probabilistic of each element. Probabilistic hesitant fuzzy sets (PHFSs) are a set structure that argues that each alternative should be evaluated probabilistically. In this framework, the proposed cluster allows probabilistic evaluation of decision- makers’ opinions as negative. Thus, this case proposes flexibility about selection of an element and aids to overcome with noise channels. Furthermore, some new aggregation operators are discussed called bipolar valued probabilistic hesitant fuzzy weighted average operator (BVPHFWA), Generalized bipolar valued probabilistic hesitant fuzzy weighted average operator (GBVPHFWA), bipolar valued probabilistic hesitant fuzzy weighted geometric operator (BVPHFWG), Generalized bipolar valued probabilistic hesitant fuzzy weighted geometric operator (GBVPHFWG), bipolar valued probabilistic hesitant fuzzy hybrid weighted arithmetic and geometric operator (BVPHFHWAG) and Generalized bipolar valued probabilistic hesitant fuzzy hybrid weighted arithmetic and geometric (GBVPHFHWAG) and some basic properties are presented. A score function is defined ranking alternatives. Moreover, two different algorithms are put forward with helping to TOPSIS method and by using aggregation operators over BVPHFSs. The validity of proposed operators are analyzed with an example and results are compared in their own.

Simulation of a spin-boson model by iterative optimization of a parametrized quantum circuit

Time evolution of the populations of spin states coupled with bosons, which can be a model of photosynthetic excitation energy transfer of dye molecules surrounded by proteins, is simulated using the projected-variational quantum dynamics algorithm. By a transformation of the Hamiltonian describing the spin-boson model into the one-dimensional nearest-neighbor form, it is shown that the spin-boson model can be simulated using the sequential ansatz even if a quantum computer has limited connectivity. The optimization of the parametrized quantum circuits is performed by the gradient descent method on a classical computer using the automatic differentiation, and the population of the spins is simulated on a noisy intermediate-scale quantum computer. The error originating from the quantum computing is mitigated by the Clifford data regression, in which the noise channel is estimated using the data obtained from all the time steps.

Performance of Relaying System with NOMA over Symmetric a-Stable Noise Channels

Objectives: This paper investigates the performance of a candidate 5G transmission system technique that is Non-Orthogonal Multiple Access (NOMA) over α-stable channels. This type of channel gets more attention in the research community because of its ability to model new IoT scenarios. However, there is a research gap in applying this type of channel to different wireless communications scenarios. In this work, we envision a scenario where users employ NOMA communications in the presence of an obstacle. As our mathematical analysis and simulation results show, there is a significant difference in performance when considering α-stable channels. Methods: To characterize the performance of the proposed noise channel, performance metrics such as outage probability and achievable rate are discussed. More particularly, we derive expressions for both outage probability and achievable rate for three NOMA users, considering the near user as a relay. In this paper, we consider additive symmetric α-stable noise channels with alpha α ∈ (1, 2). We present expressions for achievable rate and outage probability for each user (near, middle, and far) and investigate its behavior for different values of alpha (α). Findings: Based on the simulation results, it is shown that the high achievable rate observed for low alpha values while reduced as alpha is increased. Also, due to the influence of alpha, the outage probability is highly affected by α for small rate thresholds (Ro). In an envisioned scenario of three users with only one user forwarding the transmission to the other two, our results show that the near and middle users’ outage probability decreases as alpha α increases. Novelty: Despite this extensive study of the NOMA on individual channels, transmission under α-stable channel is not considered to the best of the authors’ knowledge. Keywords: NOMA, relaying, Cooperative Non-Orthogonal Multiple Access, Symmetric α-Stable Noise Channels, Achievable rate

Digital data transmission system over the Gaus noise channel using a 16-QAM modulator, hamming source encoding, and turbo channel encoding

Digital data transmission system over the Gaus noise channel using a 16-QAM modulator, hamming source encoding, and turbo channel encoding

Adapted Beamforming: A Robust and Flexible Approach for Removing Various Types of Artifacts from TMS-EEG Data.

Electroencephalogram (EEG) recorded as response to transcranial magnetic stimulation (TMS) can be highly informative of cortical reactivity and connectivity. Reliable EEG interpretation requires artifact removal as the TMS-evoked EEG can contain high-amplitude artifacts. Several methods have been proposed to uncover clean neuronal EEG responses. In practice, determining which method to select for different types of artifacts is often difficult. Here, we used a unified data cleaning framework based on beamforming to improve the algorithm selection and adaptation to the recorded signals. Beamforming properties are well understood, so they can be used to yield customized methods for EEG cleaning based on prior knowledge of the artifacts and the data. The beamforming implementations also cover, but are not limited to, the popular TMS-EEG cleaning methods: independent component analysis(ICA), signal-space projection (SSP), signal-space-projection-source-informed-reconstruction method (SSP-SIR), the source-estimate-utilizing noise-discarding algorithm (SOUND), data-driven Wiener filter (DDWiener), and the multiple-source approach. In addition to these established methods, beamforming provides a flexible way to derive novel artifact suppression algorithms by considering the properties of the recorded data. With simulated and measured TMS-EEG data, we show how to adapt the beamforming-based cleaning to different data and artifact types, namely TMS-evoked muscle artifacts, ocular artifacts, TMS-related peripheral responses, and channel noise. Importantly, beamforming implementations are fast to execute: We demonstrate how the SOUND algorithm becomes orders of magnitudes faster via beamforming. Overall, the beamforming-based spatial filtering framework can greatly enhance the selection, adaptability, and speed of EEG artifact removal.

KOMUNIKASI INTERPERSONAL GURU DAN MURID DALAM MENGIMPLEMENTASIKAN TRI KAYA PARISUDHA DI SANGGAR KEGIATAN BELAJAR KOTA DENPASAR

In the implementation of character education in educational institutions, interpersonal communication patterns are very important so that character education can run well. This is because each student has a different background. This research was conducted to examine the interpersonal communication of teachers and students in implementing tri kaya parisudha at the Learning Activity Center in Denpasar. The theory that underlies this research is Rational Choice Theory. This study used a qualitative approach. The type of qualitative data collected is sourced from primary and secondary data. Data collection techniques used are observation, interviews, documentation. The findings of the research results are that the interpersonal communication applied by the teacher to the students of the Denpasar City Learning Activity Center in forming the religious character of children is using the preservation strategy model, one-way communication and interaction communication or two-way communication. This type of communication is expected to foster student activity both in teaching and learning activities and in play activities. The obstacles encountered are mechanical constraints (mechanical, channel noise), semantic between students and teachers (semantic noise), ecological constraints in learning activities in the city of Denpasar. Quality improvement is carried out by increasing educational input, improving the quality of the educational process, improving the school environment. The implications of interpersonal communication between teachers and students in tri kaya parisudha learning in the Learning Activity Center in Denpasar city are changes in the quality of children from the cognitive aspect, changes in the quality of children from the affective aspect, changes in the quality of children from the psychomotor aspect.

Low‐density algebra‐check codes for ultra reliable low latency communications

AbstractA novel channel code, the low‐density algebra‐check (LDAC) code, is introduced in this letter. LDAC code is constructed by combining sparse matrice with algebraic constraints from two types of subcodes. Detailed explanations for the encoding and decoding process of the LDAC codes are provided in the paper. Simulation results demonstrate that LDAC codes offer advantages over LDPC codes in constructing low rate codes. The proposed ultra‐low rate LDAC code can achieve approximately 0.4 and 0.2 dB improvement in SNR compared to CA‐polar and 5G LDPC, respectively, at the block error rate (BER) over the additive white Gaussian noise (AWGN) channel. LDAC codes demonstrate superior performance over LDPC codes at low rates, due to the enhanced error correction capabilities of the two types of subcodes and reduced rates without introducing short cycles.

414 Post-stroke Cognitive deficits are associated with reduced cognitive conflict evoked mid-frontal EEG theta oscillations and can be potentially improved with prefrontal transcranial electrical stimulation

OBJECTIVES/GOALS: Cognitive dysfunction and/or depressionfollowing ischemic stroke results in loss of independence in daily functioning. The objective of this work is to assess neural correlates of post-stroke cognitive deficits and the effect of left frontal transcranial electrical stimulation on cognitive control and associated brain rhythms. METHODS/STUDY POPULATION: We recorded midfrontal scalp EEG from 15 healthy and 13 participants with stroke while they performed a multi-source interference task (MSIT). The stroke cohort also performed additional MSIT sessions where they received active and sham transcranial direct current stimulation (tDCS) on the left prefrontal cortex (PFC). The EEG was pre-processed to get rid of eye movement and other channel noise artifacts and filtered to retain 0.5-55 Hz components. A Morlet wavelet was used to estimate power in theta (4-8 Hz), alpha (8-15 Hz) and gamma (35-50 Hz) frequency bands over a period of 2 seconds following MSIT image presentation. A generalized linear mixed effects model was used to find effect of group on behavior and EEG oscillations. A GLME was also used to find effects of active tDCS on behavior and EEG. RESULTS/ANTICIPATED RESULTS: We found Group (healthy v stroke) as a significant predictor of both response time (behavior) and conflict evoked theta power in the frontal channels (F1-Fz, F2-Fz). We also found that active tDCS significantly improved MSIT performance as compared to sham, after accounting for cognitive load. Active tDCS also induced low frequency oscillations in frontal EEG channels compared to sham. Preliminary results indicate that mid-frontal theta oscillations are a potential neural correlate of post-stroke cognitive deficit and tDCS of the left PFC might be a promising therapeutic intervention to ameliorate this. DISCUSSION/SIGNIFICANCE: Current therapeutic approaches often do not alleviate post stroke executive dysfunction, hence a better understanding of the brain network changes underlying such deficit can elucidate neural correlates of post stroke cognitive deficit to inform the development of neuromodulation interventions.

Design of a Short Reference Differential Chaotic Shift Keying Communication System Based on Reference Signal Scrambling Transformation

A short reference differential chaotic shift keying communication system based on reference signal scrambling transformation (RSST-SR-DCSK) is proposed in this paper. The system introduces information-bit-driven scramblers at the transmission end to effectively eliminate the correlation between the reference signal and information signal. At the receiving end, a descrambler is used to restore the correlation, thereby enhancing information transmission security. Additionally, the system employs a short reference transmission mechanism to further increase the information transmission rate. The transmitter and receiver structures of the system are designed through signal structure analysis. Theoretical analyses and simulations conducted in an additive white Gaussian noise (AWGN) channel demonstrate promising performance, including a low bit error rate (BER) and a favorable data-energy-to-bit-energy ratio (DBR). Simulation verification is performed to examine the impact of parameters on the bit error rate performance. A comparative analysis with traditional DCSK and SR-DCSK systems highlights the superior performance of the RSST-SR-DCSK system.