Search Results (44)

Free-space optical (FSO) communication systems offer fiber-like bandwidth, high security, and rapid deployment; however, their performance is highly susceptible to atmospheric impairments, such as dust storms, which can cause fading that degrades link reliability. In this study, we analyze the performance of FSO links under a dust-induced fading channel modeled as a Beta distribution channel. We derive an expression for the instantaneous signal-to-noise ratio (SNR) distribution. Using the SNR expression, we construct a general framework that yields closed-form formulas for fundamental performance measures such as outage probability, average bit-error rate (BER), and ergodic capacity. The analysis considers both intensity modulation/direct detection (IM/DD) and coherent detection techniques, encompassing typical modulation schemes including modulation formats such as on–off keying (OOK), M-ary phase-shift keying (M-PSK), and M-ary quadrature amplitude modulation (M-QAM). The results show that dust-induced fading penalizes all modulations, though coherent detection achieves better error performance than IM/DD at equivalent SNR. For example, a coherent receiver requires approximately 4.4 dB lower average SNR than an IM/DD system to achieve the same outage probability. Overall, the proposed unified framework shows that dust-induced fading can severely degrade the performance of FSO links, while also quantifying how network operators can trade off complexity and performance when choosing between coherent and IM/DD detection under realistic dust-storm conditions. Full article

Quantum image transmission is a critical enabler for next-generation communication systems, allowing for the reliable exchange of high-quality visual data over error-prone quantum channels. Existing quantum-encoding schemes, however, often suffer from limited efficiency and reduced robustness under noisy conditions. This work introduces a novel multi-qubit phase-shift keying (PSK) encoding framework to enhance both fidelity and reliability in quantum image transmission. In the proposed system, source-encoded images (JPEG/HEIF) are converted into bitstreams, segmented into varying qubit sizes from 1 to 8, and mapped onto multi-qubit states using quantum PSK modulation. By exploiting multi-qubit superposition and phase modulation, the scheme improves spectral efficiency while maintaining resilience to channel noise. The encoded quantum states are transmitted through noisy channels and reconstructed via inverse quantum operations combined with classical post-processing to recover the original images. Experimental results demonstrate substantial performance improvements, evaluated using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and universal quality index (UQI). Compared to superposition-only approaches, the proposed method achieves up to 3 dB SNR gain for higher qubit sizes, while single-qubit encoding remains limited due to reduced phase utilization. Moreover, relative to classical communication systems, the proposed multi-qubit PSK scheme consistently outperforms across all tested qubit sizes, highlighting its effectiveness for reliable, efficient, and high-fidelity quantum image transmission. Full article

The rapid growth of Internet-connected devices integrating into our everyday lives has no end in sight. As more devices and sensor networks are manufactured, security tends to be a low priority. However, the security of these devices is critical, and many current research topics are looking at the composition of simpler techniques to increase overall security in these low-power commercial devices. Transmission security (TRANSEC) methods are one option for physical-layer security and are a critical area of research with the increasing reliance on the Internet of Things (IoT); most such devices use standard low-power Time-division multiple access (TDMA) or frequency-division multiple access (FDMA) protocols susceptible to reverse engineering. This paper provides a hardware validation of previously proposed techniques for the intentional injection of noise into the phase mapping process of a spread spectrum signal used within a receiver-assigned code division multiple access (RA-CDMA) framework, which decreases an eavesdropper’s ability to directly observe the true phase and reverse engineer the associated PRNG output or key and thus the spreading sequence, even at high SNRs. This technique trades a conscious reduction in signal correlation processing for enhanced obfuscation, with a slight hardware resource utilization increase of less than 2% of Adaptive Logic Modules (ALMs), solidifying this work as a low-power technique. This paper presents the candidate method, quantifies the expected performance impact, and incorporates a hardware-based validation on field-programmable gate array (FPGA) platforms using arbitrary-phase phase-shift keying (PSK)-based spread spectrum signals. Full article

High-frequency (HF) communication is critical for applications such as over-the-horizon positioning and ionospheric detection. However, precise time-delay estimation in complex HF channels faces significant challenges from multipath fading, Doppler shifts, and noise. This paper proposes a Modulation Signal-based Adaptive Time-Delay Estimation (MATE) algorithm, which effectively decouples carrier and modulation signals and integrates phase-locked loop (PLL) and delay-locked loop (DLL) techniques. By leveraging the autocorrelation properties of 8PSK (Eight-Phase Shift Keying) signals, MATE compensates for carrier frequency deviations and mitigates multipath interference. Simulation results based on the Watterson channel model demonstrate that MATE achieves an average time-delay estimation error of approximately 0.01 ms with a standard deviation of approximately 0.01 ms, representing a 94.12% reduction in mean error and a 96.43% reduction in standard deviation compared to the traditional Generalized Cross-Correlation (GCC) method. Validation with actual measurement data further confirms the robustness of MATE against channel variations. MATE offers a high-precision, low-complexity solution for HF time-delay estimation, significantly benefiting applications in HF communication systems. This advancement is particularly valuable for enhancing the accuracy and reliability of time-of-arrival (TOA) detection in HF-based sensor networks and remote sensing systems. Full article

The Automatic Modulation Classification (AMC) for underwater acoustic signals enables more efficient utilization of the acoustic spectrum. Deep learning techniques significantly improve classification performance. Hence, they can be applied in AMC work to improve the underwater acoustic (UWA) communication. This paper is based on the adoption of Hough Transform (HT) and Edge Detection (ED) to enhance modulation classification, especially for a small dataset. Deep neural models based on basic Convolutional Neural Network (CNN), Visual Geometry Group-16 (VGG-16), and VGG-19 trained on constellation diagrams transformed using HT are adopted. The objective is to extract features from constellation diagrams projected onto the Hough space. In addition, we use Orthogonal Frequency Division Multiplexing (OFDM) technology, which is frequently utilized in UWA systems because of its ability to avoid multipath fading and enhance spectrum utilization. We use an OFDM system with the Discrete Cosine Transform (DCT), Cyclic Prefix (CP), and equalization over the UWA communication channel under the effect of estimation errors. Seven modulation types are considered for classification, including Phase Shift Keying (PSK) and Quadrature Amplitude Modulation (QAM) (2/8/16-PSK and 4/8/16/32-QAM), with a Signal-to-Noise Ratio (SNR) ranging from −5 to 25 dB. Simulation results indicate that our CNN model with HT and ED at perfect channel estimation, achieves a 94% classification accuracy at 10 dB SNR, outperforming benchmark models by approximately 40%. Full article

The final goal of this paper is to organize the tools needed to study digital Quantum Communications, where classical information is entrusted to quantum states represented by density operators. A density operator is usually defined starting from a set of kets in the Hilbert space and a probability distribution. A fundamental problem in Quantum Communications is the factorization of such operators of the form $\rho =\gamma {\gamma }^{*}$, where $\gamma$ is a matrix called a density factor (DF). The environments considered are finite dimensional Hilbert space (discrete variables) and infinite dimensional Hilbert space (continuous variables). Using discrete variables, the multiplicity and the variety of DFs are investigated using the tools of matrix analysis, arriving in particular to establish the DF with minimal size. With continuous variables, the target is the closed-form factorization, which is achieved with recent results for the important class of Gaussian states. Finally, an application is carried out in Quantum Communications with noisy Gaussian states. Full article

The limitations of cloning and discriminating quantum states are related to the non-orthogonality of the states. Hence, understanding the collective features of quantum states is essential for the future development of quantum communications technology. This paper investigates the non-orthogonality of different coherent-state signal constellations used in quantum communications, namely phase-shift keying (PSK), quadrature-amplitude modulation (QAM), and a newly defined signal named the sunflower-like (SUN) coherent-state signal. The non-orthogonality index (NOI) and the average probability of correct detection (detection probability) are numerically computed. Results show that PSK NOI increases faster than QAM and SUN as the number of signals increases for a given number of signal photons. QAM and SUN exhibit similar NOI and detection probability, behaving similarly to randomly generated signals for a larger number of signals. Approximation formulas are provided for the detection probability as a function of NOI for each signal type. While similar to QAM, SUN signal offers potential advantages for applications requiring uniform signal-space distribution. The findings provide valuable insights for designing useful quantum signal constellations. Full article

Among the numerous strategies that an attacker can initiate to enhance its eavesdropping capabilities is the Pilot Contamination Attack (PCA). Two promising methods, based on Phase-Shift Keying (PSK) modulation of Nth order—2-N-PSK and Shifted 2-N-PSK, can detect an existing PCA by means of analysis of the constellation that the correlation product of received pilot signals belongs to. The overall efficiency of the methods can be studied by the most commonly used probability metrics—detection probability and false alarm probability. However, this information may be insufficient for comparison purposes; therefore, to acquire a more holistic perspective on the methods’ performances, statistical evaluation metrics can be obtained. Depending on the particular application of the system in which the PCA detection methods are incorporated and the distribution of attack initiation among all samples, different classification parameters are of varying significance in the efficiency assessment. In this paper, 2-N-PSK and Shifted 2-N-PSK are comprehensively studied through their probability parameters. In addition, the methods are also compared by their most informative statistical parameters, such as accuracy, precision and recall, F1-score, specificity, and fall-out. A large number of simulations are carried out, the analyses of which indisputably prove the superior behavior of the Shifted 2-N-PSK compared to the 2-N-PSK detection method. Since a method’s performance is strongly related to the number of antenna elements at the base station, all simulations are conducted for scenarios with different antennae numbers. The most promising realization of Shifted 2-N-PSK improves the receiver operating characteristics results of the original 2-N-PSK by 7.38%, 4.33%, and 5.61%, and outperforms the precision recall analyses of 2-N-PSK by 10.02%, 4.82% and 3.86%, for the respective number of 10, 100 and 300 antenna elements at the base station. Full article

The multifunctionality feature of graphene field-effect transistors (GFETs) is exploited here to design circuit building blocks of high-data-rate modulators by using a physics-based compact model. Educated device performance projections are obtained with the experimentally calibrated model and used to choose an appropriate improved feasible GFET for these applications. Phase-shift and frequency-shift keying (PSK and FSK) modulation schemes are obtained with $0.6$ $\mathrm{G}$$\mathrm{Hz}$ GFET-based multifunctional circuits used alternatively in different operation modes: inverting and in-phase amplification and frequency multiplication. An adequate baseband signal applied to the transistors’ input also serves to enhance the device and circuit performance reproducibility since the impact of traps is diminished. Quadrature PSK is also achieved by combining two GFET-based multifunctional circuits. This device circuit co-design proposal intends to boost the heterogeneous implementation of graphene devices with incumbent technologies into a single chip: the baseband pulses can be generated with CMOS technology as a front end of line and the multifunctional GFET-based circuits as a back end of line. Full article

VLF magneto-electric (ME) antennas have gained attention for their compact size and high radiation efficiency in lossy conductive environments. However, the need for a large DC magnetic field bias presents challenges for miniaturization, limiting portability. This study introduces a self-biased ME antenna with an asymmetric design using two magneto materials, inducing a magnetization grading effect that reduces the resonant frequency during bending. Operating principles are explored, and performance parameters, including the radiation mechanism, intensity and driving power, are experimentally assessed. Leveraging its excellent direct and converse magneto-electric effect, the antenna proves adept at serving as both a transmitter and a receiver. The results indicate that, at 2.09 mW and a frequency of 24.47 kHz, the antenna has the potential to achieve a 2.44 pT magnetic flux density at a 3 m distance. A custom modulation–demodulation circuit is employed, applying 2ASK and 2PSK to validate communication capability at baseband signals of 10 Hz and 100 Hz. This approach offers a practical strategy for the lightweight and compact design of VLF communication systems. Full article

Ultrasonic sensors are inexpensive and provide highly accurate measurements, even with simple hardware configurations, facilitating their use in various fields. When multiple ultrasonic sensors exist in the measurement space, crosstalk occurs due to other nodes, which leads to incorrect measurements. Crosstalk includes not only receiving homogeneous signals from other nodes, but also overlapping by other signals and interference by heterogeneous signals. This paper proposes using frequency sweep keying modulation to provide robustness against overlap and a faster region-based convolutional neural network (R-CNN) demodulator to reduce the interference caused by heterogeneous signals. The demodulator works by training Faster R-CNN with the spectrograms of various received signals and classifying the received signals using Faster R-CNN. Experiments implementing an ultrasonic crosstalk environment showed that, compared to on–off keying (OOK), phase-shift keying (PSK), and frequency-shift keying (FSK), the proposed method can implement CDMA even with shorter codes and is robust against overlap. Compared to correlation-based frequency sweep keying, the time-of-flight error was reduced by approximately 75%. While the existing demodulators did not consider heterogeneous signals, the proposed method ignored approximately 99% of the OOK and PSK signals and approximately 79% of the FSK signals. The proposed method performed better than the existing methods and is expected to be used in various applications. Full article

Wireless energy harvesting (EH) communication has long been considered a sustainable networking solution. However, it has been limited in efficiency, which has been a major obstacle. Recently, strategies such as energy relaying and borrowing have been explored to overcome these difficulties and provide long-range wireless sensor connectivity. In this article, we examine the reliability of a wireless-powered communication network by maximizing the net bit rate. To accomplish our goal, we focus on enhancing the performance of hybrid access points and information sources by optimizing their transmit power. Additionally, we aim to maximize the use of harvested energy, by using energy-harvesting relays for both information transmission and energy relaying. However, this optimization problem is complex, as it involves non-convex variables and requires combinatorial relay selection indicator optimization for decode and forward (DF) relaying. To simplify this problem, we utilize the Markov decision process and deep reinforcement learning framework based on the deep deterministic policy gradient algorithm. This approach enables us to tackle this non-tractable problem, which conventional convex optimization techniques would have difficulty solving in complex problem environments. The proposed algorithm significantly improved the end-to-end net bit rate of the smart energy borrowing and relaying EH system by $13.22\%, 27.57\%,$ and $14.12\%$ compared to the benchmark algorithm based on borrowing energy with an adaptive reward for Quadrature Phase Shift Keying, 8-PSK, and 16-Quadrature amplitude modulation schemes, respectively. Full article

We examine the effects of imperfect phase estimation of a reference signal on the bit error rate and mutual information over a communication channel influenced by fading and thermal noise. The Two-Wave Diffuse-Power (TWDP) model is utilized for statistical characterization of propagation environment where there are two dominant line-of-sight components together with diffuse ones. We derive novel analytical expression of the Fourier series for probability density function arising from the composite received signal phase. Further, the expression for the bit error rate is presented and numerically evaluated. We develop efficient analytical, numerical and simulation methods for estimating the value of the error floor and identifying the range of acceptable signal-to-noise ratio (SNR) values in cases when the floor is present during the detection of multilevel phase-shift keying (PSK) signals. In addition, we use Monte Carlo simulations in order to evaluate the mutual information for modulation orders two, four and eight, and identify its dependence on receiver hardware imperfections under the given channel conditions. Our results expose direct correspondence between bit error rate and mutual information value on one side, and the parameters of TWDP channel, SNR and phase noise standard deviation on the other side. The results illustrate that the error floor values are strongly influenced by the phase noise when signals propagate over a TWDP channel. In addition, the phase noise considerably affects the mutual information. Full article

In this paper, we propose a multi-feature fusion network (MFF-Net) for a modulation format identification (MFI) and optical signal-to-noise ratio (OSNR) monitoring scheme. The constellation map data used in this work comes from five modulation formats, namely 56 Gbit/s 4/8 phase shift keying (PSK) and 16/32/64 quadrature amplitude modulation (QAM). The constellation maps are input to one branch network of the MFF-Net, and then the constellation maps are processed by horizontal projection and used as input to another branch network as a way to fuse the two image features. The results show that the scheme achieves 100% MFI accuracy and 98.82% OSNR monitoring accuracy for the five modulation formats. In addition, the performance of MFF-Net and binarized convolutional neural network (B-CNN), visual geometry group network (VGG-Net), and traditional weighted multi-task learning (EW-MTL) are compared to present the superiority of the method. The effect of model structure on MFF-Net is also discussed. The robustness of the model is also evaluated for different transmission distances and bit rates. Full article

The performance of Low-Density Parity-Check (LDPC)-coded Orthogonal Frequency Division Multiplexing (OFDM) is investigated over turbulence channels in underwater wireless optical communications (UWOC). The relation between the bit error ratio (BER) and parameters such as the scintillation coefficient, signal-to-noise ratio (SNR), length of LDPC code, and order of OFDM is quantified by simulation. Results show that while the OFDM with subcarrier quadrature amplitude modulation (QAM-OFDM) has slightly better anti-turbulence performance than the OFDM with subcarrier phase shift keying modulation (PSK-OFDM), the LDPC-coded QAM-OFDM has a much better performance than the QAM-OFDM and the LDPC-coded PSK-OFDM, and, at SNR = 12, it decreases the BER by four orders of magnitude compared to the 16QAM-OFDM system when the scintillation coefficient ${\sigma }_{\xi }^2$= 0.05. Full article