Receiver End Research Articles

A robust semi-fragile watermarking system using Pseudo-Zernike moments and dual tree complex wavelet transform for social media content authentication.

With the growing use of mobile devices and Online Social Networks (OSNs), sharing digital content, especially digital images is extremely high as well as popular. This made us convenient to handle the ongoing COVID-19 crisis which has brought about years of change in the sharing of digital content online. On the other hand, the digital image processing tools which are powerful enough to make the perfect image duplication compromises the privacy of the transmitted digital content. Therefore, content authentication, proof of ownership, and integrity of digital images are considered crucial problems in the world of digital that can be accomplished by employing a digital watermarking technique. On contrary, watermarking issues are to triumph trade-offs among imperceptibility, robustness, and payload. However, most existing systems are unable to handle the problem of tamper detection and recovery in case of intentional and unintentional attacks concerning these trade-offs. Also, the existing system fails to withstand the geometrical attacks. To resolve the above shortcomings, this proposed work offers a new multi-biometric based semi-fragile watermarking system using Dual-Tree Complex Wavelet Transform (DTCWT) and pseudo-Zernike moments (PZM) for content authentication of social media data. In this research work, the DTCWT-based coefficients are used for achieving maximum embedding capacity. The Rotation and noise invariance properties of Pseudo Zernike moments make the system attain the highest level of robustness when compared to conventional watermarking systems. To achieve authentication and proof of identity, the watermarks of about four numbers are used for embedding as a replacement for a single watermark image in traditional systems. Among four watermarks, three are the biometric images namely Logo or unique image of the user, fingerprint biometric of the owner, and the metadata of the original media to be transmitted. In addition, to achieve the tamper localization property, the Pseudo Zernike moments of the original cover image are obtained as a feature vector and also embedded as a watermark. To attain a better level of security, each watermark is converted into Zernike moments, Arnold scrambled image, and SHA outputs respectively. Then, to sustain the trade-off among the watermarking parameters, the optimal embedding location is determined. Moreover, the watermarked image is also signed by the owner's other biometric namely digital signature, and converted into Public key matrix Pkm and embedded onto the higher frequency subband namely, HL of the 1-level DWT. The proposed system also accomplishes a multi-level authentication, among that the first level is attained by the decryption of the extracted multiple watermark images with the help of the appropriate decryption mechanism which is followed by the comparison of the authentication key which is extracted using the key which is regenerated at the receiver's end. The simulation outcomes evident that the proposed system shows superior performance towards content authentication, to most remarkable intentional and unintentional attacks among the existing watermarking systems.

Predictive Modeling of Quasi-Static Electromagnetic Interference Effects on Electro-Optic Modulators

Electro-optic modulators (EOMs) are an interface between electrical and optical components, making them susceptible to external electromagnetic interference (EMI). In this article, we investigate the effects of low-frequency ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\sim }$</tex-math></inline-formula> 15 MHz) EMI on lithium niobate (LiNbO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> ) EOMs. A predictive model for low-frequency EMI injection into a commercially available EOM is developed and validated experimentally. Specifically, analytical expressions for eye height and Q-factor are derived that predict the changes in the receiver end eye diagram, when the EOM modulation process is interrupted by the RF injection. The eye diagram gradually closes down as the RF injection power increases, owing to the signal degradation in the receiver end. A simple expression for calculating the maximum peak RF injected voltage that the EOM can tolerate prior to the system experiencing significant bit error rate is also presented. This model can be utilized to assess the survivability of EOMs under EMI.

IoT-Enabled Vacant Parking Slot Detection System Using Inkjet-Printed RFID Tags

It is challenging for motorists to manually search for a parking slot in a crowded parking area. Conventional methods for locating vacant or occupied space are regarded as inefficient and unreliable. In this work, an Internet-of-Things (IoT)-enabled vacant parking slot detection system is developed and tested using low-cost inkjet-printed passive ultrahigh-frequency (UHF) radio frequency identification (RFID) tags. The working principle of the proposed system is to analyze the backscattered signal strength from the tags at the receiver side for vehicle presence/ absence detection in the parking slots. First of all, we propose a low-cost passive tag optimized to work in UHF RFID-band pasted on plastic material display for parking slots. The data collected by the RFID reader from the tags is sent over message queuing telemetry transport (MQTT) protocol via Scotland 5G-network to the MongoDB database using a Python module Pymongo for decision-making and display of vacant parking slots to the motorists. A Python-based web-app extracts data from the database and shows it on a web-app display using the embedded JavaScript template (EJS) for each slot. Experimental observations conducted at parking slots in the presence of vehicles indicate a drastic reduction in the received-signal-strength-index (RSSI) value at the receiver end, which implies that RSSI signal drop can be utilized for the detection of vehicle presence in the parking slot. The suggested approach aims to facilitate the economical and effective location of available parking slots. The test results for the proposed system are recorded and presented, demonstrating its significant performance and showing great accuracy for the tested scenarios.

Simultaneous light emission and detection of an AlGaInP quantum well diode

When a quantum well (QW) diode is biased with a forward voltage and illuminated with an external shorter-wavelength light, the device simultaneously emits and detects light, with the injected current and the induced current mixed inside the wells. Separating these superimposed and dynamic electrical signals is useful for the development of multifunctional displays that can simultaneously transmit and receive light signals. By utilizing the unique overlap between the electroluminescence and detection spectra, we establish a wireless optical communication system using two AlGaInP diodes that have identical QW structures. The communication distance is 25 m, with one diode functioning as the transmitter and the other as the receiver. In particular, at the receiver end, the QW diode demonstrates simultaneous light emission and reception ability, and the mixed signals can be efficiently extracted, suggesting great potential for applications from light communication to advanced displays.

Investigating seismic mode conversions from an ultra-high-velocity caprock by physical modelling, numerical simulations and a Gulf of Mexico salt proximity VSP survey

SUMMARY Salt structures are widely distributed in many basins worldwide and play an important role in understanding tectonic movements, offering underground storage and sealing hydrocarbon traps. In addition to the acknowledged difficulties in mapping complex salt structures through seismic methods, when an evaporitic layer, such as anhydrite, forms over salt, it can introduce strong multimode conversions that can couple with the primary compressional wavefields and generate artefacts in resulting acoustic images. From two well-log suites from the Gulf of Mexico, we identify thin evaporitic caprocks on top of their salt bodies and analyse their elastic properties. Through controlled experiments, including physical and numerical modelling with a vertical seismic profiling survey geometry, we observe significant shear-mode conversions at the top of the ultra-high-velocity caprock, which further result in a family of prominent S and P (converted from S wave) modes across the top of the salt region. Similarly, in a field survey, we identify evident converted S waves and a multimode P wave (converted S wave in the anhydrite layer, and P wave elsewhere) following the primary P transmission inside the salt body. While separating the converted Smodes at the receiver end is more unambiguous, the multimode P waves could behave very similarly to the primary Pmodes and are more difficult to suppress. Under the common acoustic assumption of seismic velocity model building and imaging, complex mode conversions on top of the salt are generally ignored. Through controlled experiments and a field survey, we analyse the pitfalls associated with this omission. We emphasize the importance of understanding the physics of wave partitioning in the presence of a thin ultra-high-velocity layer on the top of the salt.

Fully digital platform for local ultra-stable optical frequency distribution.

This article reports on the use of a Field Programmable Gate Array (FPGA) platform for local ultra-stable optical frequency distribution through a 90 m-long fiber network. This platform is used to implement a fully digital treatment of the Doppler-cancellation scheme required by fiber links to be able to distribute ultra-stable frequencies. We present a novel protocol that uses aliased images of a digital synthesizer output to directly generate signals above the Nyquist frequency. This approach significantly simplifies the setup, making it easy to duplicate within a local fiber network. We demonstrate performances enabling the distribution of an optical signal with an instability below 10-17 at 1s at the receiver end. We also use the board to implement an original characterization method. It leads to an efficient characterization of the disturbance rejection of the system that can be realized without accessing the remote output of the fiber link.

Optimal Rotated M-PSK Signaling for Multi-User Receive Diversity System Over Correlated Rician Fading Channels

In this letter, a two-user receive diversity non-orthogonal multiple-access (NOMA) wireless communication system is considered with the transmitter utilizing a rotated <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -ary phase-shift keying ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -PSK) modulation for data modulation over correlated Rician fading channels. A maximum ratio combining scheme followed by an optimum maximum-likelihood rule is employed for received data detection at each user end. Further, a simple separation scheme is proposed to eliminate the use of successive interference cancellation at the receiver end of the NOMA system. The receiver structure is utilized to derive a closed-form expression for the symbol error probability which is minimized by obtaining the optimal rotation angle of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -PSK constellation. The variations of the optimal rotation angle with system parameters are studied by numerical results which lead to novel modulation schemes for the considered system.

Pro-active Performance Monitoring in Optical Networks using Frequency Aware Seq2Seq Model

Performance Monitoring (PM) and Fault Detection have always been a reactionary approach in Optical Networks for most service providers. Any kind of fault (power surge, ageing issues, equipment faults and failures, natural calamities, etc.) in an optical network is detected only after the fault has occurred and mitigation is performed afterward. The resultant service outages for end-users cause huge financial and reputation losses to the vendors. Therefore, there is a strong need for proactive detection of faults to limit disruption and provide uninterrupted services to clients. We achieve this objective by doing a multi-horizon time series prediction of Bit Error Rate at the receiver end of an optical circuit using our custom designed Frequency aware Sequence to Sequence (FaS2S) Neural Network. The predicted value of BER can be used to notify users of failure scenarios before they occur. Further corrective action, such as automatic re-routing or manual intervention can then be taken by the user. With this model, we can even configure the network properties dynamically during periods of low BER to push the network efficiency to its maximum capacity. See inference Video for BER inference capabilities of FaS2S.

Estimation of bit error rate in 2×2 and 4×4 multi-input multi-output-orthogonal frequency division multiplexing systems

&lt;span lang="EN-US"&gt;Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with multiple input antennas and multiple output antennas in dynamic environments face the challenge of channel estimation. To overcome this challenge and to improve the performance and signal-to-noise ratio, in this paper we used the Kalman filter for the correct estimation of the signal in dynamic environments. To obtain the original signal at the receiver end bit error rate factor plays a major role. If the signal to noise ratio is high and the bit error rate is low then signal strength is high, the signal received at the receiver end is almost similar to the &lt;/span&gt;&lt;em&gt;&lt;span lang="EN-US"&gt;i&lt;sup&gt;th&lt;/sup&gt;&lt;/span&gt;&lt;/em&gt;&lt;span lang="EN-US"&gt; transmitted signal. The dynamic tracking characteristic of Kalman filter is used to establish a dynamic space-time codeword and a collection of orthogonal pilot sequences to prevent interference among transmissions in this paper. Using the simulation, the Kalman filter method can be compared to the other channel estimation method presented in this paper that can track time-varying channels rapidly.&lt;/span&gt;

Dual-carrier multiplexed laser-based hybrid transmitter for high data-rate indoor optical wireless communication

In this paper we experimentally demonstrate dual-carrier modulation scheme to achieve spectrally efficient OFDM transmission in an optical wireless communication link using a hybrid laser-LED transmitter. The hybrid transmitter used in this work consists of two near infrared laser diodes at 785 nm and 808 nm used to separately modulate the real and imaginary components of the complex OFDM waveforms, collinearly combined and subsequently mixed with white LED array at a diffuser surface for indoor illumination. At the receiver end, two separate high-speed photodetectors with spectral filters are used to detect the real and imaginary components and subsequently combined to generate the complex OFDM waveforms. The optical system performance is characterized to quantify the beam spread, spot-size and spectral content of the laser beams and white LED array. The communication performance is also characterized using 16, 32, and 64-QAM/OFDM with 1, 1.25 and 1.5 Giga-samples/second sampling rates. The best communication performance with a net data-rate of 4.2 Gbps for 64-QAM/OFDM at an optimum sampling rate of 1.5 G-Samples/second is demonstrated. The dual-carrier modulation scheme studied in this work helps achieve improved spectral efficiency for OFDM transmission in an OWC link using dual transmitter-receiver pair, while at the same time requiring simplified electronic front-ends and encoding/decoding algorithms.

End-to-end integrated pipeline for underwater optical signal detection using 1D integral imaging capture with a convolutional neural network.

Underwater optical signal detection performance suffers from occlusion and turbidity in degraded environments. To tackle these challenges, three-dimensional (3D) integral imaging (InIm) with 4D correlation-based and deep-learning-based signal detection approaches have been proposed previously. Integral imaging is a 3D technique that utilizes multiple cameras to capture multiple perspectives of the scene and uses dedicated algorithms to reconstruct 3D images. However, these systems may require high computational requirements, multiple separate preprocessing steps, and the necessity for 3D image reconstruction and depth estimation of the illuminating modulated light source. In this paper, we propose an end-to-end integrated signal detection pipeline that uses the principle of one-dimensional (1D) InIm to capture angular and intensity of ray information but without the computational burden of full 3D reconstruction and depth estimation of the light source. The system is implemented with a 1D camera array instead of 2D camera array and is trained with a convolutional neural network (CNN). The proposed approach addresses many of the aforementioned shortcomings to improve underwater optical signal detection speed and performance. In our experiment, the temporal-encoded signals are transmitted by a light-emitting diode passing through a turbid and partial occluded environment which are captured by a 1D camera array. Captured video frames containing the spatiotemporal information of the optical signals are then fed into the CNN for signal detection without the need for depth estimation and 3D scene reconstruction. Thus, the entire processing steps are integrated and optimized by deep learning. We compare the proposed approach with the previously reported depth estimated 3D InIm with 3D scene reconstruction and deep learning in terms of computational cost at receiver's end and detection performance. Moreover, a comparison with conventional 2D imaging is also included. The experimental results show that the proposed approach performs well in terms of detection performance and computational cost. To the best of our knowledge, this is the first report on signal detection in degraded environments with computationally efficient end-to-end integrated 1D InIm capture stage with integrated deep learning for classification.

Transformer-based High-fidelity Modeling Method for Radio over Fiber Link

High-fidelity modeling is of great importance for digital twin (DT) technology. A Transformer-based modeling method for radio over fiber (RoF) link is developed and experimentally demonstrated, in which the Transformer is a kind of deep learning network. The modeling performance of the constructed model by using the proposed method is evaluated, which is better than the ones based on fully connected neural network (FCNN), convolution neural network (CNN), and generative adversarial network (GAN). In addition, the modeling consistency with different laser launch power, fiber length, carrier frequency, and signal-to-noise ratio (SNR) is also investigated. Experimental results show that the fitting waveforms predicted by the proposed method agree well with the actual waveforms at the receiver end. The normalized mean square errors of the fitting waveforms are lower than the acceptable bound of 0.02.

Evaluation of a high-speed hybrid OAM-OFDM-MDM multiplexed coherent FSO system under desert conditions

To meet the needs of future wireless optical networks, this paper introduces a high-speed, hybrid multiplexed, coherent free-space optical (FSO) communication system that integrates an orbital angular momentum (OAM) multiplexed signal with an orthogonal frequency division multiplexing (OFDM) technique. Two independent QAM polarized beams, each carrying in-phase and quadrature (I/Q) phase 16-QAM-OFDM modulated data, are combined using mode division multiplexing (MDM) to increase the capacity of the proposed system. The reason of choosing OFDM is its capability to support higher data rate, and mitigating intersymbol interference (ISI). The signal is detected using a coherent detection-based digital signal processing (DSP) algorithm at the receiver end. The proposed hybrid FSO system is evaluated in low and heavy dust environments using bit error rate (BER), link distance, optical signal-to-noise ratio (OSNR), and received optical power performance matrices. The simulation results demonstrate the successful transmission of a 120 Gb/s single carrier over the longest link ranges of 1.5 and 0.40 km, respectively, under low and heavy dust weather environments below the signal degradation threshold value (forward error correction (FEC) limit) of BER 2.2 × 10–3 in strong turbulent conditions.

Guest Editorial Special Issue on Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications

It is our pleasure to share with you this Special Issue, which brings together a diverse set of articles dealing with various aspects of semantic and goal-oriented communications, providing a snapshot of research activities in this highly active research area. Wireless communications and networking research has traditionally focused on improving the capacity and throughput of the underlying wireless network. However, recent explosion in data-driven machine learning applications and their reliance on huge datasets collected by edge devices have raised legitimate concerns that the increasing data traffic might soon overwhelm the capacity of current networks despite ongoing efforts to increase their capacity and efficiency. Also, most of the edge intelligence applications impose stringent delay constraints, which cannot be met by naive forwarding of data samples for processing at the receiver end. This made it obvious to researchers in both academia and industry that it is essential to analyze the “value” or “relevance” of collected data, and filter and prioritize the delivery of data based on its value/relevance as well as the wireless channel and network conditions. In this context, data value will be closely connected to the underlying signals and processes that generate the data, e.g., text, image, video, or sensor data, and what the receiver intends to do with the received data. This subjectivity of data value makes semantic and goal-oriented communication a rather elusive research topic, which has led to both an increasingly rich and active area of investigation, but also a controversial one, mainly due to the lack of clear and widely agreed-upon definitions of some of the core concepts and formulations. Despite these disagreements, there is almost unanimous consensus on the importance and potential impact of this line of investigation for the design of future communication systems and networks.

Stokes correlation to estimate topological charge from the speckle pattern

The orbital angular momentum (OAM) of the vortex or helical beam, connected with the topological charge (TC) of the beam, has been used as an alternative degree of freedom to encode and decode the information in the optical signals. Many detection schemes have been established to determine the TC configurations and decode the information at the receiver end of the encoded information from the transmitter end for the free space. However, when the helical beam is transmitted through the scattering medium, its wavefront is spatially scrambled without any direct information about the incident helical beam. Here, we propose and experimentally demonstrate a new approach to estimate the TC of the helical beam from the non-imaged randomly scattered pattern. The technique utilizes Stokes parameters (SPs) of the random field to evaluate higher-order SPs fluctuation correlation. A complete theoretical model of the technique is presented and verified with numerical simulation and experimental tests. A good agreement is found between the simulation and experimental results.

Performance investigation and development of 112 gbit/s dual polarization 16 QAM transmission system using differential encoding

This article reports the free space optics (FSO) with generation of a high bit rate transmission link with 16 QAM signals. Optical receiver is proposed to enhance the performance of demodulator under environmental conditions. Also, to resolve the adverse channel effects on the information signal digital signal processing (DSP) techniques at the receiver end is used. The bit error rate (BER) analysis using numerical simulations for different weather conditions is bring out and the results illustrate 112 Gbps transmission link. Further, the comparison is conducted with previous techniques which shows that the system provides better data rate performance and achievable range. The reported work provides a suitable reference towards optical communication under different environmental conditions.

Block based visually secure image encryption algorithm using 2D-Compressive Sensing and nonlinearity

In this paper, a block division based visually secure encryption algorithm is proposed for color images. Each block is sparsified through an optimal orthogonal transformation. Block based 2D-Compressive Sensing is applied to collect the compressed samples which best represent the signal, sampling is done through a measurement matrix (MM) which is generated by a 2D-SLIM map. MM is optimized through the proposed optimization algorithm which minimizes the mutual coherence between sparsified basis and MM. These compressed samples are further encrypted through a DNA XOR operation. The compressed-encrypted information is decomposed into the four sub images which are embedded into the host image through integer wavelet transform. SHA-256 is used to generate the seed value of the chaotic map. At the receiver end, the secret information is extracted with the correct knowledge of the keys. The numerical results and robustness of the proposed work is analyzed and the superiority of the developed algorithm is shown by comparing it with some recent published papers.

Bio-Physical Modeling of Galvanic Human Body Communication in Electro-Quasistatic Regime.

Human Body Communication (HBC) is an alternative to radio wave-based Wireless Body Area Network (WBAN) because of its wide bandwidth leading to enhanced energy efficiency. Designing Modern HBC devices need the accurate electrical equivalent of the HBC channel for energy efficient communication. The objective of this paper is to present an improved lumped element-based detailed model of Galvanic HBC channel which can be used to explain the dependency of the channel behaviour on the internal body dependent parameters such as electrical properties of skin and muscle tissue layers along with the external parameters such as electrode size, electrode separation, geometrical position of the electrodes and return-path or parasitic capacitances. The model considers the frequency-dependent impedance of skin and muscle tissue layers and the effect of various coupling capacitances between the body and Tx/Rx electrodes to the Earth-Ground. A 2D planar structure of skin and muscle tissue layers is simulated using a Finite Element Method (FEM) tool to prove the validity of the proposed model. The effect of symmetry and asymmetry at the transmitter and receiver ends is also explained using the model. The model become very useful for fast calculation of Galvanic channel response without using any FEM tool. Experimental results show that the galvanic response is not only a function of channel length but also depends on the mismatch at the transmitter and receiver end. In case of a very high mismatch scenario, the channel behavior is dominated by the capacitive HBC, even for a galvanic excitation and termination.

Self-Super-Resolution of an MRI Image with Assistance of the DSTTD System.

Motivation. In the modern world of information technology, the need for ensuring the safety of wireless transmissions while transiting through a given network is growing rapidly. The process of transmitting images via a wireless network is fraught with difficulty. There is a possibility that data may be corrupted while being transmitted, which would result in an image with low resolution. Both of these issues were investigated head-on in this research methodology using the aiding double space-time block coding (DSTTD) system and the self-super-resolution (SSR) method. Description. In recent times, medical image transmission over a wireless network has received a significant amount of attention, as a result of the sharing of medical images between patients and doctors. They would want to make sure that the image was sent in a risk-free and protected manner. Arnold cat map, often known as ACM, is a well-known and widely implemented method of image transmission encryption that has been in use for quite some time. At the receiver end, SSR is now being employed in order to view the transmitted medical image in the finest possible resolution. It is anticipated that in the near future, image transmission through wireless DSTTD will be technically feasible. This is performed in order to maximize the benefits that the system has to offer in terms of both spatial diversity and multiplexing as much as is possible. Conclusion. The SSR approach is used in order to represent the image in a document pertaining to human resources. ACM is used so that the image may be sent in a risk-free and protected way. The adoption of a DSTTD-based architecture for wireless communication is suggested. A comparison of the results is provided, and PSNR and SSIM values are detailed towards the results and discussion of the article.

Metasurface aided intelligent reflecting surfaces for indoor GSSK-VLC downlink

To provide high-quality communication in the indoor generalized space shift keying (GSSK) aided visible light communications (VLC) downlink transmission, especially when the line-of-sight (LoS) link is blocked, a metasurface aided intelligent reflecting surfaces (mIRS) scheme is proposed. By controlling the reflection characteristics of incident light in a deliberate manner provided in this paper, the proposed mIRS-assisted indoor GSSK-VLC downlink can significantly enhance the signal quality at the receiver end. Furthermore, the maximum likelihood (ML) and efficient preprocessing enabled sparsity orthogonal matching pursuit (OMP) detectors are respectively presented for the considered system. Finally, simulations are demonstrated to verify the effectiveness of the proposed mIRS-assisted indoor GSSK-VLC downlink transmission.