Noisy Channel Research Articles

Countermeasures Against the Attacker’s Homing Algorithm in a Game of Three Players

The paper considers a game of three players on the plane attacker, target and defender (an ADT-game). The attacker’s dynamics is described by simple motions, while target and defender are moving in a strait line. At the same time in the game model the attacker receives information about the environment through an acoustic channel in which the target and the defender broadcasts some signals. The field of view of this channel is limited by a cone. The attacker’s goal is to intercept the target and the goal of the target-defender coalition is to delay the interception as much as possible by jamming the attacker’s observation channel. During the chase the attacker uses the law of proportional navigation and various algorithms for target’s bearing estimation which are considered known to the target-defender coalition. The behavior of the system is investigated when using a well-known and a promising intelligent estimation algorithm. For each case an optimization problem is set to optimize the defender’s release angle in order to increase the interception time. The dynamics of all players and various trajectories of the defender in conditions of noiseless and noisy observation channels are simulation, the obtained results are compared.

Introduction to the JOCN Special Issue on Spatial Parallelism for Next-Generation High-Capacity Transport Networks

This special issue on Spatial Parallelism for Next-Generation High-Capacity Transport Networks tackles challenging questions of how optical networks will continue to scale in capacity now that the Shannon limit has been reached for single mode fiber systems using the C and L amplifier bands.

Theroretical and Experimental Analysis on Ghost Imaging with Channel Coding Theorem

Theroretical and Experimental Analysis on Ghost Imaging with Channel Coding Theorem

Adaptive tunicate swarm optimization with partial transmit sequence for phase optimization in MIMO-OFDM

<span>Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are widely utilized in wireless systems and maximum data rate communications. The MIMO-OFDM technology increases the efficiency of spectrum utilization. The peak-to-average-power ratio (PAPR) minimization in MIMO-OFDM is a complex task in wireless communications systems. In this research, an adaptive tunicate swarm optimization with partial transmit sequence (ATSO-PTS) algorithm is proposed for a reduction of PAPR in MIMO-OFDM. The nonsquare-matrix-based differential space time coding (N-DSTC) scheme is used for the encoding and decoding process of MIMO-OFDM. The N-DSTC encoding and decoding are linear error-correcting codes that are utilized for message transmission over noisy channels. The pre-specified quadrate phase shift keying (QPSK) symbol is deployed for the modulation and demodulation scheme. On the receiver side, the serial to parallel (S/P) conversion, and fast Fourier transform (FFT) are accomplished, alongside the received data bits being demodulated to obtain the output bits. The proposed ATSO-PTS method achieves better results according to performance metrices PAPR, bit error rate (BER) and signal-to-noise-ratio (SNR), with values of about 2.9, 0.01 and 0.025, respectively. This ensures superior results when compared to the existing methods of twin symbol hybrid optimization applied to partial transmit sequence (TSHO-PTS), selective level mapping and PTS (SLM-PTS), and particle swarm and grey wolf (PS-GW) with PTS, respectively.</span>

Teleportation of Qubits in a Kicked Nonlinear Cavity with Ultra-short Pulses via Quantum Noisy Channels

AbstractIn this paper, we delve into the profound ramifications of noise on qubit teleportation between the esteemed figures of Alice and Bob, ruthlessly quantifying the negativity and distance of the transmitted information. Through the invocation of an audacious modification to the Hamiltonian of the Jaynes–Cummings model, incorporating the ferocious power of a kicked cavity and ultra-short laser pulses, we unleash a tempest that unrelentingly shapes the entanglement and quality of the teleported information. Moreover, we fearlessly venture into the treacherous territory of noisy channels, including the formidable adversaries of phase flip and double phase flip channels, as they mercilessly assail the teleported state, engendered by the tumultuous interaction within the unforgiving depths of the kicked cavity, only to be met with our resolute projection.

Limits of Noisy Quantum Metrology with Restricted Quantum Controls.

The Heisenberg limit [(HL), with estimation error scales as 1/n] and the standard quantum limit (SQL, ∝1/sqrt[n]) are two fundamental limits in estimating an unknown parameter in n copies of quantum channels and are achievable with full quantum controls, e.g., quantum error correction (QEC). It is unknown though, whether these limits are still achievable in restricted quantum devices when QEC is unavailable, e.g., with only unitary controls or bounded system sizes. In this Letter, we discover various new limits for estimating qubit channels under restrictive controls. The HL is shown to be unachievable in various cases, indicating the necessity of QEC in achieving the HL. Furthermore, a necessary and sufficient condition to achieve the SQL is determined, where a single-qubit unitary control protocol is identified to achieve the SQL for certain types of noisy channels, and for other cases a constant floor on the estimation error is proven. A practical example of the unitary protocol is provided.

Examining the quantum fisher information in the interaction of a dirac system with a squeezed generalized amplitude damping channel.

The inherent association between real quantum systems and their surrounding environment invariably results in decoherence, leading to the loss of entanglement. This diminution in entanglement coincides with a decline in the fidelity of transmitted information using the entangled quantum resource. This study scrutinizes the impact of the squeezed generalized amplitude damping (SGAD) channel on quantum Fisher information (QFI) parameters. The SGAD channel model, a versatile framework, is also employed to simulate other dissipative channels, including amplitude damping (AD) and generalized amplitude damping (GAD). Kraus operators facilitate the modeling of noisy channels. The results reveal that, within the SGAD channel, the QFI remains impervious to the squeezing variables (r and ). In the GAD channel, undergoes enhancement to a constant value with an upswing in temperature (T), while the parameter in the GAD channel, , akin to the SGAD channel, surges around T = 2 before complete loss ensues. Concerning the AD channel, the component of the QFI initially experiences decoherence with an augmentation in the AD noise parameter ( ). Subsequently, it is restored to its initial value with a further escalation in . Conversely, the component of the QFI in the AD channel experiences decoherence with an elevation in the AD noise parameter ( ).

Bidirectional quantum controlled teleportation in multi-hop networks: a generalized protocol for the arbitrary n-qubit state through the noisy channel

Bidirectional quantum controlled teleportation in multi-hop networks: a generalized protocol for the arbitrary n-qubit state through the noisy channel

Performance Comparison of Selected Filters in Fast Denoising of Oil Palm Hyperspectral Data

Usually, hyperspectral data captured from an airborne UAV or satellite contain some noise that can be severe in some channels. Often, channels that are badly affected by the noise are discarded. This is because the corrupted channels cannot be reclaimed by common filtering techniques, making important information in the affected channels different from those of field spectroscopy of similar wavelengths. In this study, a fast-denoising method is implemented on some channels of oil palm hyperspectral data that are badly affected by noise. The amount of noise is unknown, and it varies across the noisy channels from bad to severe. This is different from the data normally used by many studies, which are essentially clean data spiked with mild noise of known variance. The process starts by identifying which noisy channels to filter based on the level of the estimated noise in them. Then, filtering is conducted within each channel and across channels. Once the noise is removed, the improvement in signal-to-noise ratio (SNR) is calculated for each channel. The performance of Kalman, Wiener, Savitzky–Golay, wavelet, and cosine filters is tested in the same framework and the results are compared in terms of execution time, signal-to-noise ratio, and visual quality. The results show that the Kalman filter slightly outperformed the other filters. The proposed scheme was implemented using MATLAB R2023b running on an Intel i7 processor, and the average execution time was less than 1 second for each channel. To the best of our knowledge, this is the first attempt to filter real oil palm hyperspectral data containing speckle noise using a Kalman filter. This technique can be a useful tool to those working in the oil palm industry.

Extending the understanding of Shannon’s safe stimulation limit for platinum electrodes: biphasic charge-balanced pulse trains in unbuffered saline at pH = 1 to pH = 12

Objective.In neural electrical stimulation, safe stimulation guidelines are essential to deliver efficient treatment while avoiding neural damage and electrode degradation. The widely used Shannon's limit,k, gives conditions on the stimulation parameters to avoid neural damage, however, underlying damage mechanisms are not fully understood. Moreover, the translation from bench testing toin vivoexperiments still presents some challenges, including the increased polarisation observed, which may influence charge-injection mechanisms. In this work, we studied the influence on damage mechanisms of two electrolyte parameters that are differentin vivocompared to usual bench tests: solution pH and electrolyte gelation.Approach.The potential of a platinum macroelectrode was monitored in a three-electrode setup during current-controlled biphasic charge-balanced cathodic-first pulse trains. Maximum anodic and cathodic potential excursions during pulse trains were projected on cyclic voltammograms to infer possible electrochemical reactions.Main results.In unbuffered saline of pH ranging from 1 to 12, the maximum anodic potential was systematically located in the oxide formation region, while the cathodic potential was located the molecular oxygen and oxide reduction region whenkapproached Shannon's damage limit, independent of solution pH. The results support the hypothesis that Shannon's limit corresponds to the beginning of platinum dissolution following repeated cycles of platinum oxidation and reduction, for which the cathodic excursion is a key tipping point. Despite similar potential excursions between solution and gel electrolytes, we found a joint influence of pH and gelation on the cathodic potential alone, while we observed no effect on the anodic potential. We hypothesise that gelation creates a positive feedback loop exacerbating the effects of pH ; however, the extent of that influence needs to be examined further.Significance.This work supports the hypothesis of charge injection mechanisms associated with stimulation-induced damage at platinum electrodes. The validity of a major hypothesis explaining stimulation-induced damage was tested and supported on a range of electrolytes representing potential electrode environments, calling for further characterisation of platinum dissolution during electrical stimulation in various testing conditions.

Preservation of entanglement in local noisy channels

Preservation of entanglement in local noisy channels

Hyperentanglement quantum communication over a 50 km noisy fiber channel

High-dimensional entanglement not only offers a high security level for quantum communication but also promises improved information capacity and noise resistance of the system. However, due to various constraints on different high-dimensional degrees of freedom, whether these advantages can bring improvement to the actual implementation is still not well proven. Here we present a scheme to fully utilize these advantages over long-distance noisy fiber channels. We exploit polarization and time-bin hyperentanglement to achieve high-dimensional coding, and observe significant enhancements in secure key rates and noise tolerance that surpass the capabilities of qubit systems. Moreover, the demonstration achieves a distribution up to 50 km, which is the longest distance for high-dimensional entanglement-based quantum key distribution up to date, to our knowledge. Our demonstration validates the potential of high-dimensional entanglement for quantum communications over long-distance noisy channels, paving the way for a resilient and resource-efficient quantum network.

Localizing Mobile Target using Kalman Filtering and Least Square Boosting Ensemble Learning based Approach

Trilateration-based target localization using received signal strengths (RSS) within wireless sensor networks (WSN) often results in inaccurate location estimates due to the considerable fluctuations in RSS measurements encountered in indoor environments. Enhancing the precision of RSS-based localization systems has been a primary area of interest in extensive research efforts. This study introduces two range-free algorithms, Ensemble Learning (EL) and EL+KF, which leverage RSS measurements for localization. In contrast to trilateration, the EL- based localization approach enables the direct estimation of target locations based on field measurements, eliminating the need for distance calculations. Notably, unlike other cutting-edge localization and tracking (L&T) scheme like the support vector regression (SVR), the LSBoost (Least Squares Boosting) EL based localization architecture can be trained very quickly using RSS measurements to determine the mobile target's position. Furthermore, the proposed EL-based localization scheme incorporates the Kalman filter (KF) to achieve additional refinement in target location estimates. To assess the localization effectiveness of these proposed algorithms in the presence of noisy RF channels and dynamic target motion models, rigorous simulations were conducted. Thanks to the robust generalization capabilities of EL, the simulation results reveal that the presented EL-based localization algorithms exhibit superior performance compared to trilateration and the SVR-based localization scheme, particularly in terms of indoor localization accuracy.

Quantum state reconstruction in a noisy environment via deep learning

Quantum noise is currently limiting efficient quantum information processing and computation, impacting on the fidelity and reliability of quantum states. In this work, we consider the tasks of reconstructing and classifying quantum states corrupted by the action of an unknown noisy channel using classical feed-forward neural networks. By framing reconstruction as a regression problem, we show how such an approach can be used to recover with fidelities exceeding 99% the noiseless density matrices of quantum states of up to three qubits undergoing noisy evolution, and we test its performance with both single-qubit (bit-flip, phase-flip, depolarizing, and amplitude damping) and two-qubit quantum channels (correlated amplitude damping). Furthermore, a critical aspect of our investigation involves also a comprehensive comparison between mean squared error and infidelity as loss functions. Our findings reveal that these two metrics yield comparable results in the context of state reconstruction. Moreover, we also consider the task of distinguishing between different quantum noisy channels, and show how a neural network-based classifier is able to solve such a classification problem with perfect accuracy.

Probing quantum discord and coherence dynamics in the discrete-time quantum walk under generalized amplitude damping noise channel

We investigate the behaviour of one-dimensional dissipative Hadamard discrete-time quantum walk (DTQW) in the generalized amplitude damping channel. By manipulating the noise intensity, we uncover intriguing dynamics in the coherence of the coin state such as rebounding and freezing phenomena. The entanglement between the quantum walker’ states diminishes at lower dissipation rates despite the pronounced coherence. The non-classical characters of the dissipative DTQW becomes evident through the manifestation of quantum discord. Our study shows that even under maximum dissipation stemming from both zero and finite-temperature environment, the quantum walker retains rudimentary non-classical behaviours. It is shown that fine-tuning the parameter governing the coin rotation angle optimizes the quantum discord of the walker. These results are useful for optimizing quantum walks in the presence of noisy channels.

All-optical correlated noisy channel and its application in recovering quantum coherence

All-optical correlated noisy channel and its application in recovering quantum coherence

Entanglement Protection Using Weak Measurement in Non‐Markovian Environment

AbstractIn this work, a scheme to protect quantum entanglement from a non‐Markovian noisy environment is proposed. By applying two quantum weak measurements before and after sending the quantum state into the noisy channel, the quantum state can be “pushed” closer to a decoherence‐free state, reducing decoherence during the time evolution. Then, the second weak measurement can partially retrieve the initial quantum state from the state corrupted by the noisy environment. The study involves a non‐Markovian dynamic equation to examine the impact of the memory effect on the protection scheme's performance. Various factors affecting the residual entanglement and the success probability are analyzed. The results suggest that two measurement strengths shall be chosen approximately in a linear relation, with the best ratio determined by the memory time of the environment. Additionally, it is demonstrated that the memory effect significantly enhances the protection efficiency. Lastly, the scheme's robustness against systematic errors is evaluated.

Optimized decoder for low-density parity check codes based on genetic algorithms

Low-density parity check (LDPC) codes, are a family of error-correcting codes, their performances close to the Shannon limit make them very attractive solutions for digital communication systems. There are several algorithms for decoding LDPC codes that show great diversity in terms of performance related to error correction. Also, very recently, many research papers involved the genetic algorithm (GA) in coding theory, in particular, in the decoding linear block codes case, which has heavily contributed to reducing the bit error rate (BER). In this paper, an efficient method based on the GA is proposed and it is used to improve the power of correction in terms of BER and the frame error rate (FER) of LDPC codes. Subsequently, the proposed algorithm can independently decide the most suitable moment to stop the decoding process, moreover, it does not require channel information (CSI) making it adaptable for all types of channels with different noise or intensity. The simulations show that the proposed algorithm is more efficient in terms of BER compared to other LDPC code decoders.

Channel-optimized quantum communication scheme based on combination code

In this paper, a channel-optimized quantum communication scheme with imperfect Bell states is being considered, based on quantum teleportation and error correction codes technology. In this scheme, a novel “combination code” technique is proposed to protect the pre-shared Bell states from storage errors and to safeguard the information-encoded states from noisy channels. Ultimately, it is revealed by Monte Carlo simulation results that the channel fidelity of the proposed channel-optimized quantum communication scheme with imperfect Bell states is significantly advantageous over standard quantum error-correcting code (QECC) and entanglement-assisted quantum error-correcting code (EAQECC) communication schemes.

Rate-Distortion-Perception Optimized Neural Speech Transmission System for High-Fidelity Semantic Communications.

We consider the problem of learned speech transmission. Existing methods have exploited joint source-channel coding (JSCC) to encode speech directly to transmitted symbols to improve the robustness over noisy channels. However, the fundamental limit of these methods is the failure of identification of content diversity across speech frames, leading to inefficient transmission. In this paper, we propose a novel neural speech transmission framework named NST. It can be optimized for superior rate-distortion-perception (RDP) performance toward the goal of high-fidelity semantic communication. Particularly, a learned entropy model assesses latent speech features to quantify the semantic content complexity, which facilitates the adaptive transmission rate allocation. NST enables a seamless integration of the source content with channel state information through variable-length joint source-channel coding, which maximizes the coding gain. Furthermore, we present a streaming variant of NST, which adopts causal coding based on sliding windows. Experimental results verify that NST outperforms existing speech transmission methods including separation-based and JSCC solutions in terms of RDP performance. Streaming NST achieves low-latency transmission with a slight quality degradation, which is tailored for real-time speech communication.