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December 2023, Volume 32, Number 4 [DOI: 10.13164/re.2023-4]

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R. Cheng, J. Zhang, J. Deng, Y. Zhu [references] [full-text] [DOI: 10.13164/re.2023.0469] [Download Citations]
Lightweight Spectrum Prediction Based on Knowledge Distillation

To address the challenges of increasing complexity and larger number of training samples required for high-accuracy spectrum prediction, we propose a novel lightweight model, leveraging a temporal convolutional network (TCN) and knowledge distillation. First, the prediction accuracy of TCN is enhanced via a self-transfer method. Then, we design a two-branch network which can extract the spectrum features efficiently. By employing knowledge distillation, we transfer the knowledge from TCN to the two-branch network, resulting in improved accuracy for spectrum prediction of the lightweight network. Experimental results show that the proposed model can improve accuracy by 19.5% compared to the widely-used LSTM model with sufficient historical data and reduces 71.1% parameters to be trained. Furthermore, the prediction accuracy is improved by 17.9% compared to Gated Recurrent Units (GRU) in the scenarios with scarce historical data.

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  23. WELLENS, M. Empirical Modelling of Spectrum Use and Evaluation of Adaptive Spectrum Sensing in Dynamic Spectrum Access Networks. [Online] Cited 2010-05-14. Available at:
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Keywords: Spectrum prediction, knowledge distillation, temporal convolutional network, lightweight networks, few-shot learning

B. Jovanovic, S. Milenkovic [references] [full-text] [DOI: 10.13164/re.2023.0479] [Download Citations]
IQ Imbalance Correction in Wideband Software Defined Radio Transceivers

A method for compensation of frequency-selective (FS) in-phase/quadrature (IQ) imbalance of a wideband transceiver is proposed in the paper. It is dedicated for implementation in software defined radio (SDR) cellular base stations. Both transmitter (TX) and receiver (RX) IQ impairments are corrected by complex valued finite impulse response (FIR) filters which are designed based on previously found imbalance correction models. The compensation performance is assessed after the method was implemented in the SDR platform capable of transmitting signals at different central frequencies. At frequencies higher than 3 GHz measured IQ gain and phase error functions exhibit asymmetrical characteristic. In order to reduce the level of asymmetry, adopted IQ gain correction model incorporates odd polynomial elements while the phase correction model includes even polynomial parts. Regardless of utilized central frequency IQ impairments are efficiently compensated. The advantage of the proposed method is low complexity. The method doesn't require specialized hardware for calibration, instead, it uses the RF loopback. At central frequency of 3.5 GHz, transmitter image rejection ratio (IRR) is increased from 20 dBc to 45-50 dBc by applying the proposed method. After receiver imbalance is compensated, the improvement in IRR of more than 25 dBc is achieved.

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Keywords: Frequency selective IQ imbalance, transmitter, receiver, software defined radio, IQ calibration

F. Titel, M. Belattar [references] [full-text] [DOI: 10.13164/re.2023.0492] [Download Citations]
Optimization of NOMA Downlink Network Parameters under Harvesting Energy Strategy Using Multi-Objective GWO

Non-orthogonal multiple access technique (NOMA) is based on the principle of sharing the same physical resource, over several power levels, where user’s signals are transmitted by using the superposition-coding scheme at the transmitter and these users signals are decoded by the receiver by means of successive interference cancellation technique (SIC). In this work, performance of NOMA Downlink network under Rayleigh fading distribution is studied, in the power domain where a power beacon (PB) is used to help a base station (BS) to serve distant users, by Wireless Power Transfer (WPT). The harvested energy permits by the BS, supports information signal transmission to NOMA users. This concept can be an effective way to power Internet of Things (IoT) devices, reduce battery dependency, and promote energy sustainability and may be used in SWIPT systems and vehicular networks. To improve the key performance indicators of the system expressed by the outage performance of NOMA users and system throughput, a Multi-Objective Grey Wolf Optimizer algorithm (MOGWO) is used to find optimal values of several influencing parameters. These parameters are partition time expressing the harvesting energy time, the power conversion factor and power allocation coefficients.

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Keywords: Base station, outage probability, power beacon, throughput, wireless power transfer, multi-objective optimization, Grey Wolf Optimizer (GWO), Multi-Objective Grey Wolf Optimizer (MOGWO), Pareto optimal solutions

W. Jlassi, R. Haddad, R.Bouallegue [references] [full-text] [DOI: 10.13164/re.2023.0502] [Download Citations]
Energy-Efficient Path Construction for Data Gathering Using Mobile Data Collectors in Wireless Sensor Networks

Energy is seen as a significant factor in wireless sensor networks (WSNs). It is a challenge to balance between battery lifetime of the different sensors and network lifetime. The main contribution of the proposed approach is to decrease the energy consumption of each sensor node, overcome unbalanced energy usage among sensor nodes, reduce the data gathering time and enhance the network lifetime. To achieve these goals, we combine the Hierarchical Agglomerative algorithm and an optimal path selection method. First, the suitable cluster heads (CHs) are elected based on the Euclidean distance and the residual energy of each sensor node. Then, the base station is situated at the center of the field, which will be partitioned into equal subareas, one for every mobile data collector (MDC). Second, the Kruskal algorithm is used to create an optimal data gathering path from each subset of elected cluster heads. Finally, each mobile data collector travels the optimal path to collect the data from the set of cluster heads of each subarea and returns periodically to the base station to upload gathered data. Computer simulation proves that the proposed approach outperforms existing ones in terms of data gathering time, residual energy and network lifetime

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Keywords: Wireless sensor network (WSN), optimal path, clustering, Mobile Data Collector (MDC), Cluster Head (CH)

R. Lu, H. Natiq, A. M. A. Ali, H. R. Abdolmohammadi, S. Jafari [references] [full-text] [DOI: 10.13164/re.2023.0511] [Download Citations]
Synchronization of Dissipative Nose–Hoover Systems: Circuit Implementation

The synchronization of dynamical systems has been extensively studied across various scientific disciplines, including secure communication, providing insights into the collective behavior of complex systems. This paper investigated the synchronization of diffusively coupled dissipative Nose-Hoover (DNH) systems analytically and experimentally. This system exhibits a variety of fascinating dynamical phenomena, including multistable or monostable chaotic solutions and attractive torus. The DNH circuit is implemented in OrCAD-PSpice, focusing on chaotic dynamics. The DNH system is thus said to be diffusively coupled by considering a passive resistor to link the corresponding states of two DNH circuits. The coupling scheme and strength (resistor value) under which two circuits can be synchronized are attained using the master stability function method and are then confirmed by computing the synchronization error. The correlation of coupled circuits' outputs (time evolutions) demonstrates complete synchronization, which is consistent with the analytical and experimental results

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Keywords: Synchronization, dissipative Nose–Hoover system, master stability function, chaotic circuit

M. Rujzl, M. Sigmund [references] [full-text] [DOI: 10.13164/re.2023.0523] [Download Citations]
Depersonalization of Speech Using Speaker-Specific Transform Based on Long-Term Spectrum

This paper introduces a novel approach for hiding personal information in speech signals. The proposed approach applied a transform warping function, which is obtained from a long-term linear prediction spectrum individually for each speaker. The depersonalized speech was compared with the often used technique based on vocal tract length normalization. The proposed approach performs wider manipulation of fundamental frequency and provides higher intelligibility by 5% in clean speech and by 8% for signal-to-noise ratio 5 dB. It also significantly alters the derived glottal pulses, making them difficult to use for personality analysis. Speech intelligibility index and glottal pulse distortion are new aspects in the field of voice depersonalization.

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Keywords: Speech depersonalization, long-term spectrum, voice transformation, depersonalized speech evaluation

K. Tamizhelakkiya, S. Gauni, P. Chandhar [references] [full-text] [DOI: 10.13164/re.2023.0531] [Download Citations]
Transfer Learning based Location-Aided Modulation Classification in Indoor Environments for Cognitive Radio Applications

Modulation classification is a crucial technique to utilize the unconsumed spectrum in Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) systems to meet the required traffic demands for future-generation cellular networks. This paper presents an end-to-end experimental setup as a generic methodology to implement various Transfer Learning (TL) models in an indoor environment. This allows us to learn the features from multiple modulation signals to train and test the model. The performance evaluation of proposed TL models such as Convolutional Neural Network-Random Forest (CNN-RF), and Convolutional Long Short Term Deep Neural Network (CLDNN) -Random Forest (CLDNN-RF) have been thoroughly discussed. The result shows that the proposed TL models yield more than 90% classification accuracy for various modulation types. A proposed framework for location-specific TL model selection based on the maximum classification accuracy has been investigated.

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Keywords: Deep Learning (DL), modulation classification, CNN, Software Defined Radio (SDR), Transfer Learning (TL)

Y. V. Pershin [references] [full-text] [DOI: 10.13164/re.2023.0542] [Download Citations]
SPICE Modeling of Memcomputing Logic Gates

Memcomputing logic gates generalize the traditional Boolean logic gates for operation in the reverse direction. According to the literature, this functionality enables efficient solution of computationally intensive problems, including factorization and NP-complete problems. To approach the deployment of memcomputing gates in hardware, this paper introduces SPICE models of memcomputing logic gates following their original definition. Using these models, we demonstrate the behavior of single gates as well as small self-organizing circuits. We have also corrected some inconsistencies in the prior literature. Notably, the correct schematics of the dynamic correction module is reported here for the first time. Our work makes memcomputing more accessible to those interested in this emerging computing technology.

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Keywords: Memristors, SPICE, nonlinear dynamical systems, computing technology

V. Kral [references] [full-text] [DOI: 10.13164/re.2023.0557] [Download Citations]
Design of Multi-bit Pulsed Latches with Scan Input in CMOS ONK65 Technology

This paper presents a new multi-bit pulse latch design that places innovative emphasis on the integration of scan input for automatic test pattern generation (ATPG). Two different designs have been developed in ONK65 technology (65 nm process): the first with standard threshold voltage (SVT) tailored for consumer products and the second with high threshold voltage (HVT) for automotive, each addressing specific aspects of process, voltage, and temperature (PVT). Multi-bit pulse latches offer a more efficient alternative to multi-bit flip-flop circuits and promise significant power and area savings. However, the efficiency of these latches depends on the technology, library type and customer requirements. A multi-bit pulse latch consists of a pulse generator and a pulsed latch. Each component is carefully designed for its specific purpose and the most appropriate topology is selected. Furthermore, the paper serves as a comprehensive guide to the design of low-power digital cells. It rethinks the topology design approach by emphasizing the scan input and presents simulation results for both components of the multi-bit pulse latch, highlighting their advantages. The results show that a less strict PVT offers greater benefits than a strict PVT.

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Keywords: 5G chips, area-friendly design, automotive, consumer flip-flops, digital standard cell, dynamic power, leakage, low power chips, multi-bit pulsed latch, pulsed latch, saving area, scan mode, serial shifter, static power

M. Tatovic, P. B. Petrovic [references] [full-text] [DOI: 10.13164/re.2023.0568] [Download Citations]
Single Active Block-Based Emulators for Electronically Controllable Floating Meminductors and Memcapacitors

This paper introduces two novel emulator circuits that employ a single active block. The first circuit utilizes a Voltage Differencing Transconductance Amplifier (VDTA) to emulate the behavior of a floating/grounded incremental/decremental flux-controlled meminductor. The second circuit, based on a Voltage Differencing Current Conveyor (VDCC), emulates the characteristics of memcapacitance. Both emulation circuits are constructed using capacitors as the only type of grounded passive element. Notably, these circuits possess electronic tunability, enabling control over the realized inverse meminductance/memcapacitance. The theoretical analysis of the proposed emulators includes an investigation into potential non-idealities and parasitic effects. By carefully selecting the passive circuit elements, efforts were made to minimize the impact of these unwanted effects. In comparison to existing designs documented in the literature, the proposed circuits demonstrate remarkable simplicity. Additionally, they exhibit wide frequency operability (up to 50 MHz) and successfully pass the non-volatility test. Simulation results conducted using 0.18 μm CMOS technology and a ±0.9 V supply voltage align closely with the theoretical predictions. Furthermore, Monte Carlo simulations and corner analysis are employed to evaluate the circuit's robustness. To validate the feasibility of the proposed solution, experimental tests are performed using commercially available components.

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Keywords: Meminductor, memcapacitor, emulator, VDTA, VDCC, grounded passive components, electronic controller, simulation

S. Meng, C. Meng, C. Wang, Q. Wang [references] [full-text] [DOI: 10.13164/re.2023.0583] [Download Citations]
Optimization of Bipolar Toeplitz Measurement Matrix Based on Cosine-Exponential Chaotic Map and Improved Abolghasemi Algorithm

In compressive sensing theory, the measurement matrix plays a crucial role in compressive observation of sparse signals. The bipolar Toeplitz measurement matrix constructed based on chaotic map has advantages such as generating fewer free elements and supporting fast algorithms, making it widely used. While optimizing the measurement matrix can effectively improve its compressive sensing reconstruction performance, existing optimization algorithms are not suitable for the bipolar Toeplitz measurement matrix due to its structural and bipolar properties. To address this issue, this paper proposes an optimization method for the bipolar Toeplitz measurement matrix based on cosine-exponential (CE) chaotic map sequences and an improved Abolghasemi algorithm. Using an enhanced CE chaotic map to generate chaotic sequences with greater chaos and randomness, we construct the measurement matrix and optimize it using the structure matrix and the improved Abolghasemi algorithm, which preserves the matrix's bipolarity without altering its structure. We also introduce constraints on the generated sequence values during the optimization process. Through simulation experiments, the effectiveness of our optimization algorithm is verified, as the optimized bipolar Toeplitz measurement matrix significantly reduces reconstruction error and improves reconstruction probability.

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Keywords: Chaotic map, measurement matrix, bipolar Toeplitz matrix, optimization

P. Kavitha, K. Kavitha [references] [full-text] [DOI: 10.13164/re.2023.0594] [Download Citations]
Hybrid NOMA for Latency Minimization in Wireless Federated Learning for 6G Networks

Wireless Federated Learning (WFL) is an innovative machine learning paradigm enabling distributed devices to collaboratively learn without sharing raw data. WFL is particularly useful for mobile devices that generate massive amounts of data but have limited resources for training complex models. This paper highlights the significance of reducing delay for efficient WFL implementation through advanced multiple access protocols and joint optimization of communication and computing resources. We propose optimizing the WFL Compute-then-Transmit (CT) protocol using hybrid Non-Orthogonal Multiple Access (H-NOMA). To minimize and optimize latency for the transmission of local training data, we use the Successive Convex Optimization (SCA) method, which efficiently reduces the complexity of non-convex algorithms. Finally, the numerical results verify the effectiveness of H-NOMA in terms of delay reduction, compared to the benchmark that is based on Non-Orthogonal Multiple Acces (NOMA).

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  27. DURSUN, Y., GOKTAS, M. B., DING, Z. Green NOMA based MUMIMO transmission for MEC in 6G Networks. Computer Networks, 2023, vol. 228, p. 1–7. DOI: 10.1016/j.comnet.2023.109749

Keywords: WFL, NOMA, SCA, latency, Compute-then-Transmit (CT)

L. Tan, J. Liu, Y. Zhou, R. Chen [references] [full-text] [DOI: 10.13164/re.2023.0603] [Download Citations]
Coverless Steganography Based on Low Similarity Feature Selection in DCT Domain

Coverless image steganography typically extracts feature sequences from cover images to map information. Once the extracted features have high similarity, it is challenging to construct a complete mapping sequence set, which places a heavy burden on the underlying storage and computation. In order to improve database utilization while increasing the data-hiding capacity, we propose a coverless steganography model based on low-similarity feature selection in the DCT domain. A mapping algorithm is presented based on an 8000-dimensional feature termed CS-DCTR extracted from each image to convert into binary sequences. The high feature dimension leads to a high capacity, ranging from 8 to 25 bits per image. Furthermore, scrambling is employed for feature mapping before building an inverted index tree, considerably enhancing security against steganalysis. Experimental results show that CS-DCTR features exhibit high diversity, averaging 49.3% complete mapping sequences, which indicates lower similarity among CS-DCTR features. The technique also demonstrates resistance to normal operations and benign attacks. The information extraction accuracy rises to 96.7% on average under typical noise attacks. Moreover, our technique achieves excellent performance in terms of hiding capacity, image utilization, and transmission security.

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Keywords: Coverless, steganography, feature collision, DCTR, JPEG

T. Teng, A. He [references] [full-text] [DOI: 10.13164/re.2023.0616] [Download Citations]
Performance of Satellite UWOC Network with Generalized Boresight Error and AWGGN

This paper investigates a dual-hop satellite-marine communication network that employs mixed radio-frequency/underwater wireless optical communication (RF/UWOC). The study focuses on investigating the impacts of non-zero pointing errors and the additive white generalized Gaussian noise (AWGGN) on the dual-hop system. To address the challenge of computing the probability density function (PDF) for the UWOC system with non-zero boresight error, we apply the Laplace transformation and the generalized integro exponential function. Next, we utilize the generalized Gaussian noise to calculate the signal-to-noise ratio (SNR) and the conditional bit error rate (BER). Then, we present system performance metrics such as the outage probability (OP) and BER. We also calculate the asymptotic analysis of the OP and BER by considering poles coinciding, resulting in the proposal of four asymptotic formulas to gain additional insights into the diversity gain. Finally, we provide simulation results that analyze the performance of the proposed satellite-marine network with different system parameters, such as boresight displacements and bubble levels, and validate the accuracy of the numerical results.

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Keywords: Dual-hop RF/UWOC transmission, decode-and-forward relay, performance analysis, satellite-marine communication network

H. L. Sun, Z. H. Liao, W. D. Shen [references] [full-text] [DOI: 10.13164/re.2023.0625] [Download Citations]
A Random Access Scheme for Aggregate Traffic Based on Deep Fusion of Supermartingale and Improved SSA

The network services present diversity as the continuous evolution of communication scenarios, which brings a great challenge to the efficient utilization of resources. The ALOHA access mechanism is considered as an effective solution to deal with multi services for its feature of shared bandwidth. However, the collision problem of ALOHA degrades the quality of service (QoS) seriously. The multi packet reception (MPR) technology could mitigate collision and improve network performance. Considering ALOHA mechanism with MPR capability, we propose a novel random access scheme for aggregate traffic based on deep fusion of supermartingale and improved sparrow search algorithm (SSA) to provide delay QoS guarantee. Firstly, we construct a complicated queuing model with heterogeneous arrivals and ALOHA-type service. Secondly, we derive the tighter delay-violation probability bound relying on supermartingale theory, and the optimization problem is constructed with the goal of minimizing the service rate and the constraint of supermartingale bound. Finally, we improve the SSA by combining Circle chaotic map, nonlinear inertia weight and Levy flight strategy, then the scheme is designed by applying the improved SSA and supermartingale constraint. Simulation results show that the proposed algorithm has faster convergence speed and the scheme is more bandwidth-saving.

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Keywords: Supermartingale, improved sparrow search algorithm, quality of service, multi packet reception, aggregate traffic.

X. Zhao, B. Shi, J. Bai, F. Shu, Y. Chen, X. Zhan, W. Cai, M. Huang, Q. Jie, Y. Li, J. Wang, X. You [references] [full-text] [DOI: 10.13164/re.2023.0634] [Download Citations]
Machine-Learning-Aided Massive Hybrid Analog and Digital MIMO DOA Estimation for Future Wireless Networks

Due to a high spatial angle resolution and low circuit cost of massive hybrid analog and digital (HAD) multiple-input multiple-output (MIMO), it is viewed as a valuable green communication technology for future wireless networks. Integrating the massive HAD-MIMO with direction of arrival (DOA) will provide an even ultra-high performance of DOA measurement, which can the fully-digital (FD) MIMO. However, phase ambiguity is a challenge issue for a massive HAD-MIMO DOA estimation. In this paper, we consider three parts: detection, estimation, and Cramer-Rao lower bound (CRLB). First, a multi-layer-neural-network (MLNN) detector is proposed to infer the existence of emitters. Then, a two-layer HAD (TLHAD) MIMO structure is proposed to estimate the DOA and eliminate phase ambiguity using only one time block. Simulation results show that the proposed MLNN detector is much better than both the existing generalized likelihood ratio test (GRLT) and the ratio of maximum eigen-value (Max-EV) to minimum eigen-value (R-MaxEV-MinEV) in terms of detection probability. Additionally, the proposed TLHAD structure can achieve the corresponding CRLB.

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Keywords: DOA, hybrid analog and digital, MIMO, green technologies, CRLB, multi-layer-neural-network