Effect Of Channel Noise Research Articles

Research on improved YOLOx weed detection based on lightweight attention module

Accurate weed detection is essential for precise weed control in farmland, and machine vision serves as an effective method for identifying and targeting these unwanted plants. An advanced YOLOx weed detection model, incorporating a deep network connection lightweight attention mechanism, has been proposed to effectively identify distinct types of weeds in maize seedling fields. The lightweight attention module is connected to the deep network of YOLOx-Darknet, which weakens the channel noise effect of residual computation and thus makes the detection model more efficient. A deconvolution layer has been introduced in the residual module to improve the small size feature extraction capability. The Generalized Intersection over Union (GIoU) has replaced the Intersection over Union (IoU) to minimize the positional discrepancy between the predicted frame and the actual frame, thereby enhancing the learning capacity of the detection model. Compared with the original algorithm, the improved one achieved an average detection accuracy of 94.86% in the performance evaluation, 0.07% better in the F1 value, and 1.16% better in the AP value. The weeding robot with an improved YOLOx algorithm had 92.45% detection rate of maize seedlings and 88.94% detection rate of weed recognition at 0.2 m s−1. The results of this study can provide technical references for real-time weed detection and robotic precision weeding.

Securing information using a proposed reliable chaos-based stream cipher: with real-time FPGA-based wireless connection implementation

In this paper, a robust chaos-based stream cipher (CBSC) is proposed. The novelty of this work is that it addresses all challenges confronting chaos-based cryptography. The PCBSC (proposed CBSC) has a robust synchronization circuit that mitigates the effect of channel noise, a perturbation block that overcomes the dynamical degradation, a robust encryption scheme, and an efficient control parameters’ generator that generates strong keys. According to the complexity evaluation, the improved chaotic map provides good statistical properties. This can be confirmed by the obtained high values of the statistical metrics (largest Lyapunov exponent, approximate entropy, permutation entropy, and sample entropy) used for the evaluation. According to the security analysis, the PCBSC has good security features and provides strong keys that ensure confusion property, as well as enough space to withstand brute-force attacks. On the other hand, the proposed encryption scheme proves its efficiency; the result of the differential attack clearly shows that the diffusion property is guaranteed. Additionally, the original images’ statistical properties are completely dispersed on the encrypted images. The obtained performance over noisy channels proves the synchronization circuit’s efficiency. When compared to other proposals, the PCBSC provides the best results. In addition, the PCBSC is implemented on an FPGA and evaluated in real-time over a wireless link.

Application of optimization methods to minimize noise in quantum key distribution systems integrated into fiber-optic communication lines using dense wavelength division multiplexing

Subject of study. This study examined the applicability of the simulated annealing optimization algorithm to the search for optimal configurations of quantum and information channels required for a successful quantum key distribution session considering grids with different frequency spacings between channels, such as 12.5, 25, 50, and 100 GHz. Aim of study. This study was aimed at optimization of a search for configurations of quantum and information channels for a grid corresponding to dense wavelength division multiplexing standards using optimization methods based on analysis of the channel noise effect on quantum key distribution sessions and investigation of these methods. Method. Naturally, quantum signal powers are significantly lower than those of classic signals. Therefore, noise from information channels for a configuration where they propagate in the same fiber with quantum channels results in considerable reduction of quantum key distribution system performance. This problem can be mitigated by reducing the noise level in the channel via the selection and use of an optimal spectral channel allocation. The search for such channel allocation schemes, which are further referred to as configurations, can be implemented via several methods, such as the educated guess method and the approach entailing optimization using the simulated annealing optimization algorithm, which are the subjects of this study. The results obtained using this method were compared with similar results obtained using the educated guess method. Descriptions of the methods and their interpretation for the context of the objectives of the study are presented together with mathematical models for calculation of noise resulting from spontaneous Raman scattering, four-wave mixing, and linear channel crosstalk. Optimal allocation schemes of quantum and information channels in the grid with dense wavelength division multiplexing (configurations) obtained using the two methods are described. The configurations were considered optimal when the total value of all channel noise types considered in the mathematical model was minimal. Main results. Optimal configurations obtained using methods of simulated annealing and educated guess are described in this study. We demonstrated that the educated guess method is applicable when the spontaneous Raman scattering is the primary contributor to the total losses. In this case, the information channels should be arranged according to the Raman scattering cross-section graph. However, when the contribution of four-wave mixing is comparable with or exceeds that of spontaneous Raman scattering, the simulated annealing algorithm is preferrable to search for the optimal configurations. In this case, information channels should be located at a distance from the quantum channel: the smaller the grid spacing, the further the information channels are positioned from the quantum channel to obtain optimal configurations. Increase in the number of channels results in reduction in this separation distance inside the grid with fixed channel spacing. Practical significance. Currently, practical implementations of fiber-optic communication lines are inextricably connected with multiplexing technologies, particularly, dense wavelength division multiplexing, to satisfy the constantly growing demand in increasing information capacity of communication channels and constructing quantum networks. Assignment of separate fibers for quantum key distribution systems is not optimal; thus, existing technologies of channel multiplexing must be integrated into the quantum key distribution systems. However, a rapid increase in the quantum bit error rate occurs owing to the presence of undesirable channel noise in fiber-optic communication lines, which eventually results in the impossibility of performing a successful quantum key distribution session. Therefore, accurate and profound analysis of the contributions of channel noise types is required to minimize this noise via the selection of an optimal configuration of classical and quantum channels on the frequency grid.

Deterministic distribution of orbital angular momentum multiplexed continuous-variable entanglement and quantum steering

Orbital angular momentum (OAM) multiplexing provides an efficient method to improve data-carrying capacity in various quantum communication protocols. It is a precondition to distribute OAM multiplexed quantum resources in quantum channels for implementing quantum communication. However, quantum steering of OAM multiplexed optical fields and the effect of channel noise on OAM multiplexed quantum resources remain unclear. Here, we generate OAM multiplexed continuous-variable (CV) entangled states and distribute them in lossy or noisy channels. We show that the decoherence property of entanglement and quantum steering of the OAM multiplexed states carrying topological charges l = 1 and l = 2 are the same as that of the Gaussian mode with l = 0 in lossy and noisy channels. The sudden death of entanglement and quantum steering of high-order OAM multiplexed states is observed in the presence of excess noise. Our results demonstrate the feasibility to realize high data-carrying capacity quantum information processing by utilizing OAM multiplexed CV entangled states.

Average-ILC-Based Consensus Tracking of Multiagent Systems over Wireless Networks in Presence of Channel Noise and Data Dropout

In a multiagent system (MAS), communication signals are affected by harsh wireless networks when they are transmitted from an agent to its neighboring agents, leading to the inconsistency of the MAS. In this paper, an average-iterative learning control (average-ILC) method is studied to address the consensus problem of MAS over wireless networks in the presence of channel noise and data dropout. The combined effects of channel noise and data dropout on iterative learning controllers are carefully analyzed. Based on graph theory and mathematical expectation, the corresponding average-iterative learning scheme is proposed. Especially, a sufficient condition is derived for the average-iterative learning scheme. Rigorous theoretical analysis demonstrates that the convergence of the covariance matrix of tracking error can be guaranteed with the help of an average-iterative learning scheme. Finally, simulation results are given to show the effectiveness of the proposed method.

Noise effect on the temporal patterns of neural synchrony

Neural synchrony in the brain is often present in an intermittent fashion, i.e., there are intervals of synchronized activity interspersed with intervals of desynchronized activity. A series of experimental studies showed that this kind of temporal patterning of neural synchronization may be very specific and may be correlated with behaviour (even if the average synchrony strength is not changed). Prior studies showed that a network with many short desynchronized intervals may be functionally different from a network with few long desynchronized intervals as it may be more sensitive to synchronizing input signals. In this study, we investigated the effect of channel noise on the temporal patterns of neural synchronization. We employed a small network of conductance-based model neurons that were mutually connected via excitatory synapses. The resulting dynamics of the network was studied using the same time-series analysis methods as used in prior experimental and computational studies. While it is well known that synchrony strength generally degrades with noise, we found that noise also affects the temporal patterning of synchrony. Noise, at a sufficient intensity (yet too weak to substantially affect synchrony strength), promotes dynamics with predominantly short (although potentially very numerous) desynchronizations. Thus, channel noise may be one of the mechanisms contributing to the short desynchronization dynamics observed in multiple experimental studies.

Distributed Event-Triggered $H_{\infty}$ Filtering for Discrete-Time T–S Fuzzy Systems Over Sensor Networks

This paper investigates the distributed event-triggered (ET) ${H} _{\boldsymbol \infty }$ filtering problem for discrete-time T–S fuzzy systems over sensor networks. In order to mitigate the effect of channel noise on the filtering error systems, dynamic saturation levels are considered in this paper. Different from the existing linear distributed ET filters design results, new piecewise fuzzy distributed filters are established to address the challenges caused by the distributed ET mechanisms. By constructing piecewise differentiable Lyapunov functionals, sufficient conditions in terms of linear matrix inequalities are obtained to guarantee the exponential stability and desired performance of the filtering error system. Finally, two examples are employed to verify the effectiveness of the proposed method.

Enhancing localization accuracy of collaborative cognitive radio users by internal noise mitigation

Location information of mobile primary users is one of the essential requirements for an underlay cognitive radio user to utilize the licensed spectrum efficiently. The performance of various location-based applications such as global navigation satellite system, device to device communication in dense urban 5G network also depends on the localization accuracy. In this paper, a collaborative localization scheme based on received signal strength has been proposed. The weighted centroid localization algorithm has been applied in the proposed network scenario to compute location coordinates of the mobile primary user. Since the channel noise effects are random and unavoidable, this paper has focused on the mitigation of the internal noise by designing a suitable reconfigurable FIR filter after the demodulator stage of a cognitive radio receiver circuit to improve precision of signal measurement during primary user localization. The localization error rate has come down to (1.3–1.62) % after internal noise mitigation. The enhancement in the localization accuracy improves the overall spectrum utilization efficiency and reduces the miss detection and false detection probabilities in the proposed underlay network.

Output Tracking Control of Single-Input-Multioutput Systems Over an Erasure Channel.

The output tracking control problem is investigated in this article. First, a new tradeoff performance index is presented for single-input-multioutput (SIMO) systems. Based on the frequency-domain method, the tracking performance limitations under time delay, packet loss, and channel noise effects are derived. We use a bivariate stochastic process to model the packet loss, and assume that channel noise is additive white Gaussian noise (AWGN). Two explicit expressions of the best tradeoff performance are given with the single-degree-of-freedom (SDOF) and two-degree-of-freedom (TDOF) control structures. It is shown that the tracking control performance has a close relation with the intrinsic characteristic of the plant, as well as the time delay, packet-dropouts rate, and power spectral density of AWGN. We also demonstrate that compared with the SDOF control structure, the TDOF control structure can improve the systems' attainable performance. A simulation example is finally discussed to validate the conclusions.

Fault Tolerant Controlled Quantum Dialogue with Logical Brown States Against Collective Noise

In view of the fact that the effects of channel noise are inevitable but easily ignored, we come up with two controlled quantum dialogue(CQD) protocols based on logical Brown states, which are against collective-dephasing and collective-rotation noises, respectively. Compared with existing protocols, there exist several outstanding advantages: firstly, Brown states, as the quantum resource, are the maximally entangled five-qubit states, which own stronger entanglement than GHZ states, W states and cluster states; secondly, the specific quantum circuits are designed to explain how two kinds of logical Brown states, to be strongly against collective noise, are constructed in theory; thirdly, the controller can be offline after quantum resource distribution and permission announcement such that his/her waiting time is effectively reduced; and fourthly, the security analysis manifests that our proposed protocols can not only eliminate the information leakage, but also resist against various well-known attacks, especially the dishonest controller’s attacks.

Channel noise effects on neural synchronization

Synchronization in neural networks is believed to be linked to cognitive processes, while abnormal synchronization has been associated with disorders such as epilepsy and schizophrenia. We examine the synchronization of small Hodgkin–Huxley neuronal networks. The principal features of Hodgkin–Huxley neurons are protein channels in the neural membrane that transition between open and closed states with voltage dependent rate constants. The standard assumption of infinitely many channels neglects the fact that real neurons have finitely many channels, which leads to fluctuations in the membrane voltage and modifies neuronal spike times. These fluctuations are referred to as channel noise. We demonstrate that regardless of channel noise magnitude, neurons in the network reach a steady state synchronization level dependent only on the number of neurons in the network, equivalent to the steady state level of uncoupled Poisson neurons. The channel noise only affects the time to reach the steady state synchronization level.

Quantum error rejection for faithful quantum communication over noise channels

Quantum state transmission is a prerequisite for various quantum communication networks. The channel noise inevitably introduces distortion of quantum states passing through either a free-space channel or a fibre channel, which leads to errors or decreases the security of a practical quantum communication network. Quantum error rejection is a useful technology to faithfully transmit quantum states over large-scale quantum channels. It provides the communication parties with an uncorrupted quantum state by rejecting error states. Usually, additional photons or degrees of freedom are required to overcome the adverse effects of channel noise. As quantum error rejection method consumes less quantum resource than other anti-noise methods, it is more convenient to perform error-rejection quantum state transmission with current technology. In this review, several typical quantum error-rejection schemes for single-photon state transmission are introduced in brief and some error-rejection schemes for entanglement distribution are also briefly presented.

An improved least squares channel estimation algorithm for coherent optical FBMC/OQAM system

In this paper we propose an improved least squares (LS) based channel estimator for 60 Gbps optical filter bank multicarrier with off-set quadrature amplitude modulation (FBMC/OQAM) system by employing an interference suppression technique based on discrete Fourier transform (DFT). The interference approximation method (IAM) is used to combat the inherent intrinsic interference in FBMC/OQAM system, however, residual intrinsic interference still exists in the system and it has significant impact to the LS channel estimator. The proposed technique suppresses the residual intrinsic interference and channel noise effects in the estimated optical channel impulse response by adaptive optimal channel energy criterion. Simulation results show that, the improved channel estimator is capable of estimating the channel that includes attenuation and chromatic dispersion, and suppressing the residual intrinsic interference and channel noise more effectively than the conventional LS-based channel estimator. The proposed approach is an appropriate alternative for optical FBMC/OQAM system with good trade-off between complexity and performance.

Robustness Analysis of Iterative Learning Control for a Class of Mobile Robot Systems With Channel Noise

This paper considers the robust tracking problem of a unicycle type mobile robot, which is controlled remotely by an iterative learning controller over the wireless network. First, taking the effect of the channel noise into account, the nonlinear system model is formulated to describe the mobile robot controlled by a differential-type iterative learning controller. After that, the relation between the input error at the controller side and the channel noise is derived. Based on this relation, the norm of output error is derived and analyzed theoretically. The analysis reveals that the effect of channel noise is accumulated in both the iteration and time domains, and is ruled simultaneously by the sampling time in the nonlinear function of the system. Due to the sampling time that is far less than one, the accumulated effect of channel noise on the robustness of the system is suppressed significantly by the sampling time, which means that the mobile robot can track the desired trajectory without any processing. Finally, the simulation results are given to corroborate the theoretical analysis.

Deep clipping noise mitigation using ISTA with the specified observations for LED‐based DCO‐OFDM system

Deep clipping is beneficial for the optical orthogonal frequency division multiplexing (O-OFDM) system, since it can lower the peak-to-average power ratio, reduce the direct current requirement in light emitting diodes (LEDs), and relax the bit-resolution requirement in digital-to-analogue converters (DACs). However, it is accompanied by more signal distortions. In this study, a deep clipping noise mitigation scheme using iterative shrinkage/thresholding algorithm (ISTA) with three steps is proposed to improve bit error rate (BER) performance of the LED-based DCO-OFDM systems. In the first step, the estimated observation interference is eliminated from the received symbols to minimise the negative effect of channel noise. In the second step, two strategies are presented to generate the specified observations thus reduce the component of measurement noise in the whole observation vector. In the last step, combining the generalised cross validation and the estimation of observation interference, the appropriate regularisation parameter are calculated for ISTA to improve the robustness of the sparse recovery performance. They use simulations to show that the proposed scheme can correct the deep clipping noise with favourable reconstruction quality, which significantly improves the BER performance and therefore assist the LED non-linearity mitigation.

Performance Investigation of Channel Noise Effect in Data Transmission Medium Using Signal to Noise Ratio (SNR)

<p>The noise introduced in the channel obviously affects the bit error rate of the communication system and this has direct impact in the security. Here the main problem is that the receiver terminal decoding techniques can lead to wrong interpretation even if the Bit Error Rate (BER) is acceptable. So the main idea here is to introduce high values of Signal to Noise Ratio (SNR) that can improve the bit error rate which exists due to the noise introduced in the wireless channel.</p>

Channel Noise-Enhanced Synchronization Transitions Induced by Time Delay in Adaptive Neuronal Networks with Spike-Timing-Dependent Plasticity

In this paper, we numerically study the effect of channel noise on synchronization transitions induced by time delay in adaptive scale-free Hodgkin–Huxley neuronal networks with spike-timing-dependent plasticity (STDP). It is found that synchronization transitions by time delay vary as channel noise intensity is changed and become most pronounced when channel noise intensity is optimal. This phenomenon depends on STDP and network average degree, and it can be either enhanced or suppressed as network average degree increases depending on channel noise intensity. These results show that there are optimal channel noise and network average degree that can enhance the synchronization transitions by time delay in the adaptive neuronal networks. These findings could be helpful for better understanding of the regulation effect of channel noise on synchronization of neuronal networks. They could find potential implications for information transmission in neural systems.

Temporal Coherence Transitions Induced by Channel Noise in Scale-Free Neuronal Networks with Time Delay

In this paper, we study the effect of channel noise on the temporal coherence of scale-free Hodgkin–Huxley neuronal networks with time delay. It is found that the temporal coherence of the neuronal networks changes as channel noise intensity is varied in different ways depending on the range of channel noise intensity. The temporal coherence monotonically decreases with the increase of channel noise intensity for too small or too big channel noise intensity. However, for intermediate channel noise intensity it intermittently and rapidly becomes high and low as channel noise intensity is varied, exhibiting temporal coherence transitions. Moreover, this phenomenon is dependent on coupling strength and network average degree and becomes strongest when they are optimal. This result shows that channel noise has a regulation effect on the temporal coherence of the delayed neuronal networks by inducing temporal coherence transitions. This provides a new insight into channel noise for the information processing and transmission in neural systems.

Channel noise-induced temporal coherence transitions and synchronization transitions in adaptive neuronal networks with time delay

Using spike-timing-dependent plasticity (STDP), we study the effect of channel noise on temporal coherence and synchronization of adaptive scale-free Hodgkin-Huxley neuronal networks with time delay. It is found that the spiking regularity and spatial synchronization of the neurons intermittently increase and decrease as channel noise intensity is varied, exhibiting transitions of temporal coherence and synchronization. Moreover, this phenomenon depends on time delay, STDP, and network average degree. As time delay increases, the phenomenon is weakened, however, there are optimal STDP and network average degree by which the phenomenon becomes strongest. These results show that channel noise can intermittently enhance the temporal coherence and synchronization of the delayed adaptive neuronal networks. These findings provide a new insight into channel noise for the information processing and transmission in neural systems.

Audio-Speech Watermarking Using a Channel Equalizer

Currently, the use of telephone systems is highly popular in speech telecommunication and also they have a wide presence in transmission of digital signals. In recent years, audio-speech watermarking as a modern technique makes use of the telephone channel to transmit the watermark data, but addressing the watermark’s vulnerability to noise in the telephone channel is a difficult problem in digital audio-speech watermarking. This paper presents a robust audio-speech watermarking scheme that operates against channel noise according to audio-speech specifications, the channel coding and channel equalizer technique. The proposed scheme is based on the spread spectrum technique and a psychoacoustic model with use of the channel equalizer to remove or minimize the effects of channel noise over the watermark signal. The simulation results for imperceptibility of the watermark, voice quality, and robustness against channel noise are presented in this study. The results indicate that the proposed scheme is highly satisfactory for the cases mentioned above.