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April 2024, Volume 33, Number 1 [DOI: 10.13164/re.2024-1]

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X. Rao, Z. Y. Sun, H. H. Tao [references] [full-text] [DOI: 10.13164/re.2024.0001] [Download Citations]
Multi-Beam Associated Coherent Integration Algorithm for Weak Target Detection

Weak target detection is a great challenging in radar field. To detect the weak targets with beam migration, a novel tri-dimensional time model (i.e. fast time, slow time, and beam time) and a novel tri-dimensional signal model which based on the time model are set up firstly. Then, according to the presented models, we propose two multi-beam associated (MBA) coherent integration algorithms based on time-shared multi-beam (TSMB) and space-shared multi-beam (SSMB), respectively. The two proposed algorithms could both eliminate beam migration via associating multi-beam and realize coherent integration via discrete Fourier transform. According to different beam scanning modes, the subsequent analyses show that the MBA coherent integration algorithm based on SSMB (MBACIA-SSMB) may have a better detection performance than that based on TSMB (MBACIA-TSMB). Moreover, the capabilities to estimate the target’s radial velocity and tangency velocity are analyzed. Finally, some numerical experiments are given to verify the performances of MBACIA-TSMB and MBACIA-SSMB.

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Keywords: Beam migration, coherent integration, multi-beam, weak target detection

Yu Wang, Xiang Zou, Jiantong Shi, Minhua Liu [references] [full-text] [DOI: 10.13164/re.2024.0012] [Download Citations]
YOLOv5-based Dense Small Target Detection Algorithm for Aerial Images Using DIOU-NMS

With the advancement of various aerial platforms, there is an increasing abundance of aerial images captured in various environments. However, the detection of densely packed small objects within complex backgrounds remains a challenge. To address the task of detecting multiple small objects, a multi-object detection algorithm based on distance intersection over union loss non-maximum suppression (DIOU-NMS) integrated with you only look once version 5 (YOLOv5) is proposed. Leveraging the YOLOv5s model as the foundation, the algorithm specifically addresses the detection of abundantly and densely packed targets by incorporating a dedicated small object detection layer within the network architecture, thus effectively enhancing the detection capability for small targets using an additional upsampling operation. Moreover, conventional non-maximum suppression is replaced with DIOU-based non-maximum suppression to alleviate the issue of missed detections caused by target density. Experimental results demonstrate the effectiveness of the proposed method in significantly improving the detection performance of dense small targets in complex backgrounds.

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Keywords: Object Detection, YOLOv5, DIOU-NMS, Aerial Images, Small Object Detection, Complex Backgrounds.

S. Kawdungta, D. Torrungrueng, H.-T. Chou [references] [full-text] [DOI: 10.13164/re.2024.0024] [Download Citations]
Split-Ring Coupled Low-Cost Antenna with Electromagnetic Bandgap (EBG) Superstrates to Produce Tri-bands and High Gains

In this paper, a novel tri-band low-cost antenna covering the desired frequencies is presented. The architecture is formed by a printed dipole coupled by a split-ring within an electromagnetic bandgap (EBG) structure for high radiation gains. The printed dipole is placed beneath two dielectric superstrates, and the coupling split-ring is placed on its top. The proposed antenna is excited by the printed dipole with a coaxial connector. It is placed in the middle cavity formed by two dielectric superstrates and a metal reflector as the simple EBG structure. The simulation results show three resonant frequencies at 1.42, 2.39 and 5.40 GHz respectively, with uni-directional radiation patterns and high gains enhanced by the EBG structure. Experimental measurements over an antenna prototype validate the results of reflection coefficients and radiation patterns. It is found that the gains are 8.50, 6.00 and 8.10 dBi at 1.42, 2.39 and 5.00 GHz respectively, which are sufficient for L-band and WiFi applications. In addition, simulation and measurement results are in good agreement.

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Keywords: Electromagnetic bandgap, split-ring, superstrates, tri-band

L. J. Ge, S. X. Niu, C. P. Shi, Y. C. Guo, G. J. Chen [references] [full-text] [DOI: 10.13164/re.2024.0034] [Download Citations]
Cascaded Deep Neural Network Based Adaptive Precoding for Distributed Massive MIMO Systems

In time-division duplex (TDD) distributed large-scale multiple input multiple output (DM-MIMO) systems, the traditional downlink channel precoding method is used to resist inter-user interference (IUI). However, when the Channel State Information (CSI) is incomplete, the performance loss is serious, not only the bit error rate is high, but also the complexity of the traditional precoding algorithm is high. In order to solve these problems, this paper proposes an adaptive precoding framework based on deep learning (DL) for joint training and split application deployment. First, we train a channel emulator deep neural network (CE-DNN) to learn and simulate the transmission process of the wireless communication channel. Then, we concatenate an untrained precoding DNN (P-DNN) with a trained CE-DNN and retrain the cascaded neural network to converge. The last step is to obtain the P-DNN, namely the adaptive precoding network, by dismantling the joint trained network. Simulation results show that, when CSI is imperfect, the proposed method is compared with Tomlinson-Harashima precoding (THP) and block diagonalization (BD) precoding. The proposed method has a lower mean square error (MSE) and higher spectrum efficiency, as well as a bit error rate (BER) performance close to the THP. The source codes and the neural network codes are available on request.

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Keywords: Distributed multiple-input multiple-output (D-MIMO), deep neural network, downlink precoding, channel state information (CSI)

W. Abd Alaziz, B. Abood, R. M. Muttasher, M. A. Fadhel, B. A. Jebur [references] [full-text] [DOI: 10.13164/re.2024.0045] [Download Citations]
Exact BER Performance Analysis of an Elementary Coding Techniques for NOMA System on AWGN Channel

Ultra-Reliable Low Latency Communication (URLLC) requirements of modern wireless communication systems have heightened the need for complexity reduction in data processing along with error detection and correction techniques. Motivated by this fact, we introduce a low-complexity coding scheme for Non-Orthogonal Multiple Access (NOMA). Furthermore, this work presents a comprehensive mathematical analysis of the proposed coded NOMA communication system and evaluates its Bit Error Rate (BER) performance in various scenarios. Our study showcases a precise match between practical and theoretical results, underlining the presented mathematical analysis precision. Moreover, we conduct a comparison between the proposed NOMA system and other coded and uncoded NOMA systems. This comparison highlights the superior performance of the proposed system, providing evidence of its potential to achieve the desired complexity reduction without compromising performance. Finally, in the same work environment, it is worth noting that the proposed system demonstrated superior performance compared to typical uncoded NOMA systems. It achieved a minimum improvement of 21 dB for the 1st user and a 17 dB improvement for the 2nd and 3rd users.

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Keywords: NOMA, constructive interference, BER, repetitive code, channel coding

Y. Zhao, F. Yang, C. Wang, F. Ye, F. Zhu, Y. Liu [references] [full-text] [DOI: 10.13164/re.2024.0054] [Download Citations]
Inverse Synthetic Aperture Radar Imaging Based on the Non-Convex Regularization Model

Compressed Sensing (CS) has been shown to be an effective technique for improving the resolution of inverse synthetic aperture radar (ISAR) imaging and reducing the hardware requirements of radar systems. In this paper, our focus is on the l_p 0 p 1 model, which is a well-known non-convex and non-Lipschitz regularization model in the field of compressed sensing. In this study, we propose a novel algorithm, namely the Accelerated Iterative Support Shrinking with Full Linearization (AISSFL) algorithm, which aims to solve the l_p regularization model for ISAR imaging. The AISSFL algorithm draws inspiration from the Majorization-Minimization (MM) iteration algorithm and integrates the principles of support shrinkage and Nestrove's acceleration technique. The algorithm employed in this study demonstrates simplicity and efficiency. Numerical experiments demonstrate that AISSFL performs well in the field of ISAR imaging.

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Keywords: ISAR, compressed sensing, non-convex optimization, AISSFL algorithm

D. Huang, J. Tang, L. Xu, Y. Wu [references] [full-text] [DOI: 10.13164/re.2024.0062] [Download Citations]
Design and Performance Analysis of MCPC and P4 Waveforms for OFDM based Radar System

This study aimed to investigate the performance of Multicarrier Phase Coding (MCPC) and P4-encoded waveforms. Researchers explored the unique properties of these signals, focusing on aspects like phase distribution, autocorrelation, power spectral density for P4 encoding, and aperiodic autocorrelation and ambiguity function for MCPC signals. The findings identified optimal MCPC sequences with reduced peak-to-mean envelope power ratios (PMEPR), improving signal performance. Complementary codes based on permutation were also generated and analyzed for MCPC sequences. The study utilized an improved genetic algorithm to develop new and improved waveforms, underscoring the importance of techniques like optimal sequence permutation, complementary sequences, and classical window frequency weighting in enhancing signal performance.

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Keywords: MCPC, P4 phase code, autocorrelation function, ambiguity function, improved gene algorithm, classical window frequency weighting

C. Chen, F. F. Yang, D. K. Waweru [references] [full-text] [DOI: 10.13164/re.2024.0075] [Download Citations]
Optimized-Goppa Codes Based on the Effective Selection of Goppa Polynomials for Coded-Cooperative Generalized Spatial Modulation Network

This paper proposes a novel optimized-Goppa-coded cooperative generalized spatial modulation (OGCC-GSM) scheme for short-to-medium information block transmission. In the proposed OGCC-GSM scheme, an efficient Goppa polynomial selection approach is designed to ensure that the selected Goppa codes applied in the source and relay nodes both have the largest minimum Hamming distance (MHD) and the optimal weight distribution. Compared to conventional coded cooperation (CC) with a single antenna, the proposed scheme employs the generalized spatial modulation (GSM) technique to achieve more diversity gains, where each node is equipped with multiple antennas and more than one transmit antenna (TA) is activated at each time-instant transmission. As a benchmark comparison, the OGCC spatial modulation (OGCC-SM) scheme is also investigated with a single TA active. Moreover, the reduced-complexity transmit antenna combination (RC-TAC) selection algorithm utilized in GSM is first developed with the aid of the channel state information (CSI) to reconcile computational complexity and system performance. In addition, joint decoding is conducted on the destination terminal to further enhance the performance of the proposed scheme. The simulated results indicate the performance of the proposed OGCC-GSM scheme is superior to that of its benchmark OGCC-SM scheme, with a substantial reduction in the number of TAs. Besides, Monte Carlo simulations demonstrate that the proposed OGCC-GSM scheme prevails over its counterparts by a margin of over 4.2 dB under identical conditions.

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Keywords: Optimized Goppa codes, Goppa polynomials, coded cooperation, generalized spatial modulation (GSM), spatial modulation (SM)

S. B. Harisha, E. Mallikarjun, M. Amit [references] [full-text] [DOI: 10.13164/re.2024.0089] [Download Citations]
Deep Learning Assisted Linear Sampling Method for the Reconstruction of Perfect Electric Conductors

In this study, a linear approach, linear sampling method (LSM) is used to reconstruct the shape of perfectly electric conductors (PEC) with the help of deep learning as a post-processing technique. In microwave imaging, the LSM is a simple and reliable linear inversion technique for determining the morphological features of unknown objects under investigation. However, the output of this method depends on the frequency of operation, the choice of regularization parameter,and it is unable to produce satisfactory results for objects with complex shapes. To overcome this drawback, a deep learning approach is used in this work, which can produce a better output in terms of accuracy, resolution. Here, the rough estimate of the PEC scatterer obtained using LSM is used to train the U-Net based convolutional neural network, which maps this output with the corresponding ground truth profiles. The proposed hybrid model is validated using several examples of synthetic and experimental data.

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Keywords: Deep Learning, linear sampling method, PEC, microwave imaging

X. Guo, M. Wang, C. Cheng, M. Zhou [references] [full-text] [DOI: 10.13164/re.2024.0100] [Download Citations]
Robust and Fair Multi-Objective Power Allocation Problem Based on Efficient and Healthy Cognitive Radio

Cognitive radio networks (CRNs) is a technology that can alleviate the scarcity of radio resources, improve communication efficiency, and reduce electromagnetic radiation pollution. However, traditional research mostly concentrates on a single optimization function, which is too constrained to achieve global consideration. We suggest a multi-objective optimization problem (MOP) with the objectives of transmission rate and power efficiency. Then, we introduce a fairness factor with the minimum protection rate to ensure the quality of data transfer for each secondary user(SU). We use the ellipsoid set to characterize the uncertain parameters under the actual channel state information (CSI). In the worst case, the semi-infinite programming (SIP) problem is transformed into a second-order cone programming (SOCP) problem. The original problem is linearly combined using the weighted-sum method to construct a single objective problem (SOP), which is then turned into a solvable convex optimization problem and resolved using the Lagrange dual algorithm and sub-gradient method. The simulation results demonstrate the ability of our proposed algorithm to balance power and transmission rate optimization by adjusting the weighting values, while maintaining good robustness.

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Keywords: Cognitive Radio Networks (CRNs), multi-objective optimization, robust power allocation, fairness factor, rate constraint, weighting coefficient

D. Chen, X. Xu, L. Guo, S. Xiong [references] [full-text] [DOI: 10.13164/re.2024.0111] [Download Citations]
Research on Locating Tunnel-Lining Defects Using Fast Synthetic Aperture Focusing Imaging Based on GPR

This paper proposes a method based on image processing algorithms for ground penetrating radar (GPR) to locate hidden defects in tunnel linings. Firstly, the fast synthetic aperture focusing imaging (Fast-SAFI) algorithm is used to accurately identify the morphology of tunnel-lining defects. Secondly, an iterative algorithm is used to determine the connected regions on the binary image, exclude background noise interference, and locate the centroid and vertices of the correct target connected regions to achieve the positioning of the depth of tunnel-lining defects. To verify the feasibility of the proposed positioning algorithm, a verification experiment was conducted on the experimental wall of the China Academy of Railway Sciences. The experimental results show that the proposed positioning algorithm is reliable and rapid for identifying and locating the morphology and depth of tunnel-lining defects.

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Keywords: Image processing, ground penetrating radar, fast synthetic aperture focusing imaging, tunnel-lining defects, iterative method

L. Guo, Y. J. Wei, Y. P. Shi, X. J. Zou, G. M. Wang [references] [full-text] [DOI: 10.13164/re.2024.0121] [Download Citations]
A High Directivity Microstrip Coupler Based on Reflective Resistors

In this paper, a novel high-directivity microstrip coupler based on reflective resistors is presented. The proposed coupler consists of three pairs of coupled-line sections and one pair of resistors. Generally, the coupling degree can be controlled by the coupled-lines, while the resistors are employed to adjust the amplitude of the reflected signal to cancel out the leakage signal. The mechanism of high directivity is derived and the S-parameters are presented. To verify the design concept, a 20 dB microstrip coupler operating at 2 GHz is processed and measured. The measured results indicate that the return loss of input and output ports is more than 28.5 dB with a typical insert loss of 0.3 dB, while that of coupled and isolated ports is more than 15 dB. And the directivity is more than 20 dB with a maximum 53.1 dB at 2.01 GHz in a fractional bandwidth of 22.5%.

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Keywords: High directivity, microstrip coupler, S-parameters

V. S. Nguyen, T. V. Chien, D. K. Hoa, D. D. Hung, G. N. Hoai, Q. L. Chi, L. T. Tu [references] [full-text] [DOI: 10.13164/re.2024.0127] [Download Citations]
On the Performance of Multi-Robot Wireless-based Networks

The performance of the multi-robot wireless-based networks is investigated in this paper. Particularly, we derive the outage probability (OP) and potential throughput (PT) of the worst terminal in the closed-form expressions under two scenarios, with and without direct transmission from the centre robot to all terminal robots. The considered system is complicated since it involves many random variables (RVs) and they are correlated owing to the common link from the central robot to the relay one. To overcome such correlations, our approach is to first derive the performance of the considered metric condition on the correlated link, we then take the average over the common link. Numerical results based on the Monte-Carlo method are given to verify the accuracy of the derived framework as well as to identify the behaviors of two metrics with respect to some key parameters such as the transmit power at both central and immediate robots.

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Keywords: Multi-robot networks, Outage probability, Selection combining, Performance analysis, Potential throughput

Z. Guo, Y. Zhou, H. Yang, S. Li, T. Li, X. Cao [references] [full-text] [DOI: 10.13164/re.2024.0136] [Download Citations]
The Design of Broadband Circularly Polarized Multi-beam Antenna with Linearly Polarized Feeding Source and Transmitarray Unit

Among the existing circularly polarized multi-beam transmitarray antennas, circularly or linearly-to-circularly polarized transmitarray units are always required. Naturally, designing circularly polarized units is more challenging than linear polarization. To simplify design and increase operation bandwidth, a novel method using linearly polarized transmitarray units and feeding sources is proposed for designing the circularly polarized multi-beam antenna. Broadband circular polarization is realized by utilizing sequential rotation technology and 1-bit phase compensation of linearly polarized transmitarray units. Meanwhile, beam scanning is achieved by using linearly polarized feeding sources offset. To validate the design, two multi-beam antenna samples are demonstrated. Simulated and measured results show that the designed multi-beam transmitarray antennas can realize beam scanning to 0°, ±10°, and ±20° in E-plane and H-plane. Moreover, two antennas maintain -10-dB impedance bandwidth and 3-dB axial ratio (AR) bandwidth at 8.5-10.4 GHz and 8.5-10.5 GHz, respectively. The proposed circularly polarized multi-beam transmitarray antennas have the advantages of broadband operation, simple design, and low cost.

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Keywords: Circular polarization, multi-beam antenna, spatial feed, transmitarray antenna

A. M. Pereira de Lucena, R. de Lima Florindo [references] [full-text] [DOI: 10.13164/re.2024.0145] [Download Citations]
Modified Costas Loop for Carrier Phase Tracking in GPS Receivers

The carrier phase received at the receivers of the Global Positioning System (GPS) links is used to detect navigation data and to precisely determine the position, speed and time corresponding to the user's equipment. Therefore, subsystems for carrier phase tracking are crucial parts in all GPS receivers. When the propagation conditions are favorable, the method frequently used for phase tracking is based on Digital Phase-Locked Loop (DPLL)) and implemented through the discrete Costas loop operating under the modulated L1 carrier, in the case of a GPS receiver. This technique is quite simple, well known and very suitable for implementation in low-cost receivers. In this article, we revisit the traditional Costas loop design and point out some issues that affect the phase tracking performance of this loop. In order to overcome these problems, we propose some modifications to the traditional Costas loop. The resulting architecture presents better performance and complexity equivalent to the original loop. Another contribution of this work is the mathematical analysis to evaluate the performance of the new architecture when operating on an Additive White Gaussian Noise (AWGN) channel. Various results from computational simulations carried out with the two architectures, in different operating scenarios, including AWGN, dynamic stress and ionospheric scintillation are presented and discussed. We conclude that the new architecture outperforms the traditional Costas loop in terms of the variance of the estimated phase error, root mean squared error of the estimated phase and robustness to cycle-slip and loss of lock.

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Keywords: Carrier phase tracking, GPS receiver, Costas loop, phase recovery

S. Yoon, B. Kim, S. Kim [references] [full-text] [DOI: 10.13164/re.2024.0155] [Download Citations]
A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar

We propose a robust super-resolution algorithm for vital sign radar in a low signal to noise ratio (SNR) environment. Conventional approaches, such as fast Fourier transform and super-resolution based algorithms, suffered to provide reliable results due to the limited data length and high noise level. To overcome these limitations, our proposed algorithm utilizes a low-complexity least mean square (LMS) filter and relaxation (RELAX) techniques to achieve robust performance in low SNR environments. To evaluate the effectiveness of our algorithm, we conducted both simulation and experimental studies. Our results show that the proposed method significantly outperforms conventional methods, with Monte-Carlo simulations of respiration and heartbeat achieving an RMSE approximately 7 and 120 times lower than that of the conventional method, respectively. Overall, our algorithm provides a promising solution for robust vital sign detection in challenging low SNR environments.

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Keywords: Vital sign radar, LMS filter, RELAX, low SNR, low complexity

Y. H. Hu, J. Z. Zhang, Y. X. Liu, G. J. Liu, G. K. Chen [references] [full-text] [DOI: 10.13164/re.2024.0163] [Download Citations]
Spectrum Map Construction Method Based on Dynamic Window Size Tensor Ring Low-rank Factors

Spectrum maps can model the received signal strength over a geographical region and will play a pivotal role in the intended spectrum management scheme. Traditional spectrum map construction methods cannot fully utilize the spatial-temporal correlation characteristics of observed spectrum data in a time-varying spectrum situation. The computational complexity for real-time scenes is unaffordable, and the current spectrum situation cannot be estimated promptly. To address this problem, we first model the spatial-temporal spectrum data by tensors. Then, based on the low-rank statistical characteristic of the spectrum map, we apply the tensor ring low-rank factors (TRLRF) algorithm to recover the missing spectrum data. Finally, a dynamic window mechanism is introduced to reduce the computational complexity further. The simulation results show that the proposed dynamic window size tensor ring low-rank factors (DW-TRLRF) algorithm yields higher accuracy than other state-of-the-art algorithms with significantly lower complexity.

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Keywords: Spatial-temporal spectrum data, spectrum situation construction, spectrum map, mobile radiation source

V. Abbasi, M. G. Shayesteh [references] [full-text] [DOI: 10.13164/re.2024.0173] [Download Citations]
Differential Spatial Modulation Using New Index Bits

Spatial modulation (SM) has the potential to meet the requirements of 5G and beyond communication systems with features such as reduced hardware complexity and good trade-off between spectral efficiency and energy efficiency. In this study, an efficient non-square differential spatial modulation (DSM) scheme is presented in which the number of time slots is one more than the number of transmit antennas. The introduced scheme includes one empty time slot. At the other time slots, the time slots of the conventional DSM (CDSM) are used (the Gray code order (GCO) can also be used). There is one active antenna at each time slot of the proposed scheme. The index of empty time slot conveys information. Thus, in comparison with CDSM (or GCO), for the same number of transmit antennas, the introduced scheme has more energy-free bits (index bits). It is free of pilot overhead, channel estimation complexity, and potential channel state information (CSI) estimation errors. Further, a detector with no error propagation is presented. Analytical expressions for the bit error rate (BER) are derived at high signal-to-noise ratios (SNRs) and high SNRs per bit (SNRbs). Simulation results verify the theoretical evaluation and demonstrate the efficiency of the proposed scheme.

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Keywords: Index modulation, 5G, time index modulation, differential spatial modulation (DSM), single active antenna, error propagation, diversity, signal to noise per bit (SNRb)

A. L. Makara, L. Csurgai-Horvath [references] [full-text] [DOI: 10.13164/re.2024.0182] [Download Citations]
Deep-Learning-Based ModCod Predictor for Satellite Channels

One of the significant challenges for satellite communications is to serve the ever-increasing demand for the use of finite resources. One option is to increase channel utilization, i.e., to transmit as much data as possible in a given frequency range. Since the channel is highly variable, primarily due to the ionosphere and troposphere, this goal can only be achieved by adaptively varying modulation and coding schemes. Most procedures and algorithms estimate the channel characteristics and descriptive quantities (e.g., signal-to-noise ratio). Ultimately, these procedures solve a regression problem. The resulting quantity is used as the basis for a decision process. Since valuation can also be subject to error, the decision mechanisms based on it must compensate and mitigate this error. The main element of the current research is to combine these two steps and solve them together using deep neural networks. The theoretical advantages of the method include that a better result can be achieved by having a joint estimation and decision process with a standard algorithm and cost function. The theoretical approach was tested with an actual protocol -- Digital Video Broadcasting - Satellite - Second Generation -- where we observed a significant improvement in channel utilization on previously recorded Alphasat satellite data.

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Keywords: Satellite links, time series prediction, imbalanced classification, supervised machine learning, fading, ACM, AI, DL, DNN, DVB-S2, Alphasat, satellite channel, Q band, LSTM, DNN, satellite-Earth communication, wireless signal propagation

L. Xiao, X. Rao, W. He, H. Yi, J. Hu [references] [full-text] [DOI: 10.13164/re.2024.0195] [Download Citations]
Weak Target Integration Detection Based on Radar Communication Integrated Signal via Constructed Step-LFM Model

Weak target detection is a great challenging in radar field. To detect weak targets via radar communication integrated signal, a method for constructed step-LFM (CStep-LFM) signal is proposed based on quadrature amplitude modulation-orthogonal frequency division multiplexing (QAM-OFDM) echoes. First, a QAM-OFDM and CStep-LFM model is established, and then a bandpass filters bank is used to transform the QAM-OFDM echo into a Step-LFM signal. Finally, compared with several existing integrated signals, the analyses and the simulation results show that CStep-LFM signal not only improves the detection performance of weak targets but also has a better communication performance.

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Keywords: Weak target detection, CStep-LFM, radar communication integrated signal, QAM-OFDM

X. Zhao, A. Ren [references] [full-text] [DOI: 10.13164/re.2024.0204] [Download Citations]
Mainlobe Interference Suppression Based on Compressive Sensing and Covariance Matrix Reconstruction

When mainlobe interference exists in space, the traditional anti-interference methods have problems such as peak offset and the performance of sidelobe interference suppression reduction. To solve the above problems, this paper proposes a mainlobe interference suppression method based on compressive sensing and covariance matrix reconstruction. Firstly, an improved compressive sensing algorithm is proposed to accurately estimate the Direction Of Arrival of sources, and then the signal steering vectors and signal subspaces can be established. The mainlobe interference can be suppressed by establishing an oblique projection operator through signal subspaces. Meanwhile, the sidelobe-interference-noise covariance matrix can be reconstructed by the steering vectors, and then the adaptive weight vector is obtained. Simulation results show that the proposed method can form a more robust beam pattern and has better output performance. The proposed method is still effective when the desired signal exists in the received signal.

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Keywords: Mainlobe interference suppression, compressive sensing, covariance matrix reconstruction, Direction Of Arrival (DOA)

X. P. Dao, V. S. Nguyen, V. D. Tran, T. T. Vu, T. H. Nguyen, X. L. Dai, N. H. Trong, T. T. Linh [references] [full-text] [DOI: 10.13164/re.2024.0213] [Download Citations]
A Compact Dual Bandpass Filter Using Dual Composite Right-/Left-Handed and Open-Loop Ring Resonators for 4G and 5G Applications

In this paper a very compact design of a dual-band band pass filter (D-BPF) using dual composite right-/left-handed (D-CRLH) and open-loop ring (OLR) resonators is presented. To overcome the frequency ratio limitations of D-CLRH resonators technique, the D-BPF design combines D-CRLH and OLR resonators to finally perform a D-BPF. The filter covers the 2.6 and 3.5 GHz spectrums for 4G and 5G applications, respectively. The reported D-BPF is designed and optimized using ADS software, and is implemented on a Rogers RO5880 substrate with a relative dielectric constant of 2.2 and thickness of 0.787 mm. The overall compact size is 8×8×0.787 mm^3. To our knowledge, this design is considered as the most compact and smallest size dual-bandpass filters.

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Keywords: Band pass filters (BPFs), dual-band band pass filters (D-BPFs), dual composite right-/left-handed (D-CRLH), open-loop ring (OLR), bandwidth (BW), 4G, 5G applications, compact size