Search

A low-profile, compact and efficient antenna is especially desirable for wireless applications, as it can reduce the size and weight of the system and improve its performance. In recent years, flower-shaped antennas have gained popularity due to their low profile, broad bandwidth and good radiation characteristics. In this work, a high-isolated dual-element UWB-MIMO antenna is experimentally verified having size of 32 × 39 × 0.8 mm3. The main radiating element of MIMO setup comprises a Half-Cut Flower-Shaped (HCFS) resonator. A tree-shaped decoupling structure is use to enhance the isolation. The simulated operating band of the proposed 2-port UWB-MIMO antenna ranges from 2.3 to 2.68 GHz and 3.15 to 12.87 GHz which covers Bluetooth, Wi-Fi/WLAN, Wi-MAX and UWB) with inter-element isolation of more than 15 dB and 20 dB, respectively. The measured results are found in close agreement with simulated ones. Furthermore, the diversity parameters such as Envelope Correlation Coefficient (ECC), Channel Capacity Loss (CCL), Mean Effective Gain (MEG), Effective Diversity Gain (EDG) and Total Active Reflection Coefficient (TARC) have also been analysed to ensure its legitimacy for wireless applications. Moreover, the simulation S-parameters characteristic of the proposed 8-element antenna for wireless access point applications has also been showcased. [ABSTRACT FROM AUTHOR]

ABSTRACT The rapid expansion of Internet of Things (IoT) applications presents unprecedented challenges for antenna design, demanding solutions that are versatile, efficient, and capable of operating across multiple frequency bands. This paper addresses these challenges through the development of a design of a multiband antenna using Auxiliary Classifier Wasserstein Generative Adversarial Network for IoT applications (DMA‐ACWGAN‐IoT). Here, the Auxiliary Classifier Wasserstein Generative Adversarial Network (ACWGAN) is employed to generate synthetic data representing electromagnetic field distributions and antenna characteristics across various frequencies. The proposed metamaterial‐based Multiple‐Input Multiple‐Output (MIMO) antenna contains four discrete elements, each provided by a micro strip feed. The structures overall width and length are 60 and 52 mm. The metamaterial is printed on a patch and dispersed from the fields with the most effective coupling. The proposed structures strong impedance bandwidth works at 8.3 GHz, 10.8 GHz, 12.3 GHz, 13.7 GHz, 16.1 GHz, and 18.1 GHz, fabricating the proposed antenna prototype using a substrate made of FR‐4 material. The proposed DMA‐ACWGAN‐IoT design provides 6.5 dB maximum gain and 25.40%, 21.60%, and 20.05% higher efficiency compared to existing dual band antenna design with resonance frequency prediction under machine learning models (DBA‐PRF‐ML), machine learning verification depending on a distinctive SWB multiple slotted four‐port high isolated MIMO antenna loaded with metasurface for the applications of IoT (SWB‐MIMO‐IOT‐ML), and dual‐band miniaturized composite right–left‐handed transmission line ZOR antenna along machine learning method for microwave communication (DB‐ZORA‐MC‐ML). [ABSTRACT FROM AUTHOR]

Summary The performance of millimeter‐wave (mmWave) multiple‐input multiple‐output (MIMO) systems has been significantly enhanced by the incorporation of dynamic reconfigurable intelligent surfaces (RIS). This paper proposes a novel dynamic channel estimation technique that combines dynamic atomic norm minimization with dynamic RIS to optimize RIS‐aided mmWave MIMO systems. Leveraging the dynamic nature of both atomic norm minimization and RIS, the proposed approach efficiently adapts to changing environmental conditions, providing robust and accurate channel estimation. By dynamically optimizing the RIS configuration, the system achieves improved spectral and energy efficiency, enabling high‐speed and reliable communication in challenging mmWave environments. Theoretical analysis and simulation results demonstrate the effectiveness of the proposed dynamic channel estimation technique, highlighting its potential for enhancing the performance of future wireless communication systems. [ABSTRACT FROM AUTHOR]

This paper presents a time-domain adaptive algorithm designed to eliminate harmonics in a Multiple-input Multiple-output (MIMO) system, taking into account its coupling characteristics. The algorithm is an improvement over the X-filtered LMS (FxLMS) algorithm, and is specifically tailored to the triaxial vibration system. The proposed algorithm has been shown to achieve high convergence, even in the presence of identification errors, as confirmed through both theoretical derivation and numerical simulations. To validate the efficacy of the proposed MIMO harmonic cancellation algorithm, it was tested on a genuine triaxial vibration system. The experimental results clearly demonstrate that the algorithm effectively reduces the output harmonic disturbance of the three axes' frequency components. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Multiple-Input Multiple Output (MIMO) systems require Orthogonal Frequency Division Multiplexing (OFDM) for effectively operating in multipath communication. Channel estimation is utilized in channel conditions where time-varying features are needed. However, Inter-Symbol Interference (ISI) occurs in MIMO-OFDM due to multi-path propagation, leading to inaccurate channel impulse response estimation. In this research, Improved Wild Horse Optimization (IWHO) is proposed based on three strategies namely, Random Running Strategy (RRS), Dynamic Inertia Weight Strategy (DIWS), and Competition for Waterhole Mechanism (CWHM) for pilot insertion which helps to estimate the channel accurately. IWHO increases the exploitation behavior and optimizes the global solution using three strategies. The input signal is encoded and decoded using Space Time Block Coding (STBC) to transmit data over noisy channels. Quadrature Phase Shift Keying (QPSK) is performed for modulation and demodulation in MIMOOFDM. The Additive White Gaussian Noise (AWGN) channel is employed to transmit signals from the transmitter to the receiver. When compared to the existing techniques, pilot-based interpolation method, Discrete Fourier Transform-Least Square-Wiener (DFT-LS-Wiener), and Binomial Distribution-based Grey Wolf Optimization (BDGWO), the IWHO achieves a lesser Bit Error Rate (BER) of 0.0025 with (dB) being 15. [ABSTRACT FROM AUTHOR]

Summary: In this manuscript, optimized wireless communication for 6G signals processing using memory‐augmented deep unfolding network (WC‐6G‐SP‐MADUN) is proposed. The aim of this work is to give a memory‐augmented deep unfolding network approach with a focus on belief propagation decoding of error correction codes and multiple‐input multiple‐output (MIMO) wireless systems. In contrast, compares and tabulates the performance of memory‐augmented deep unfolding methodologies with classic principled procedures, which could potentially enable 6G. Here, the wireless communication for 6G signal processing methods was used for a variety of receiver functions, including self‐interference cancelation, signal estimation and detection using memory‐augmented deep unfolding Network (MADUN), and advanced error correction by clouded leopard optimization algorithm (CLOA). Furthermore, outline the general framework of memory‐augmented deep unfolding method for any kind of signal processing application and talk about cutting edge research paths that will make it possible to build communication networks in the future. The proposed approach is implemented in MATLAB; the performance is analyzed with performance metrics such as reliability, complexity, SNR gain, convergence rate, hardware efficiency, and quantization bit width. The proposed approach attains higher SNR gain 17.96%, 24.75%, and 30.09%; lower complexity 17.92%, 23.41%, and 30.13%; and higher convergence 18.01%, 25.41%, and 31.39% when analyzed with existing techniques such as redefined wireless communication for 6G: signal processing meets deep learning and deep unfolding (RWC‐6G‐SP‐DU), lower complication deep unfolded neural network receiver for MIMO under probability data association detector (LC‐DUNN‐MIMO‐PDAD), and deep learning in physical layer communications: evolution with prospects on 5G and 6G networks (DL‐PLC‐6G), respectively. [ABSTRACT FROM AUTHOR]

Decoupling control is a commonly employed technique for achieving high precision in multiple-input multiple-output (MIMO) motion control systems. A static decoupling matrix, which can be determined using geometric construction, is widely used due to its practicality and simplicity. However, inaccurate geometric parameters will lead to a coarse decoupling matrix, and result in interactions among the system axes and performance deterioration. To tackle this challenge, various attempts have been undertaken to calibrate the decoupling matrix. Data-driven on-line approaches have gained considerable attention for their ability to calibrate the decoupling matrix without interrupting the normal operation of the system. This paper presents a data-driven approach to calibrate the decoupling matrix for MIMO and linear time invariant (LTI) systems. Through some reasonable assumptions, a calibrated static decoupling matrix can be derived to improve the performance of the system. Moreover, considering the inevitable presence of measurement noise, the consistency of the proposed method has been analyzed. As a result, the instrument variable is introduced in the improved method to eliminate the impact of the measurement noise. Finally, the effectiveness and practicality of the proposed method are demonstrated through both numerical simulations and experiments carried out on an ultraprecision wafer stage. • The performance of MIMO systems declines if mechanical parameters are inaccurate. • Traditional calibration of these parameters is complicated. • Optimizing the decoupling matrix directly with measurement data. • A calibrated static decoupling matrix with consistency is obtained. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) technologies use multiple antennas at the sender and the receiver to get the high data rate that the next-generation communication system needs. This paper compares MIMO systems using the Quadrature Phase Shift Keying (QPSK) modulation scheme for two-channel distributions of Rayleigh and Weibull types. The performance of the work is far with the Minimum Mean Square Equalizer (MMSE) in terms of Bit Error Rate (BER) for various antenna number situations on the transmitter and receiver sides. The MIMO module is carried out using MATLAB code. The channel noise will be a signal of random noise that is generated. To mitigate the impact of interchannel interference, the MMSE approach employs inverse filtering at the receiver, and BER will be calculated. According to simulation results, the system's performance is primarily influenced by the number of antennas; it decreased as the number of antennas increased, and the BER of the Weibull channel decreased as the two-parameter value increased. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Atmospheric turbulence channels experience quasi-static fading, which makes it relatively straightforward to utilize feedback information for link adaptive transmission. Applying adaptive modulation to MIMO systems can effectively mitigate the degradation of Free-Space Optical (FSO) signals under adverse turbulence conditions. In this paper, the joint influence of pointing error and Malaga distribution turbulence fading on the probability density function (PDF) of the received light intensity of a MIMO channel employing maximal ratio combining (MRC) is considered. The PDF of MRC combined channel is derived based on the moment generation function. Then, using the cumulative density function (CDF)-based method, we analyze the asymptotic spectral efficiency (SE) and average bit error rate (BER) performance of the adaptive MPSK-MIMO system under different turbulence intensities, beam waist radius, jitter standard deviation, and the number of transmit/receive apertures. In addition, we also compare the average BER performance of adaptive and non-adaptive MIMO systems with MRC receivers. Monte Carlo simulation further verifies our analysis. The derived results help quantify the diversity order of the systems we are considering. [ABSTRACT FROM AUTHOR]

Multiple-input multiple-output (MIMO) technologies use multiple antennas at the sender and the receiver to get the high data rate that the next-generation communication system needs. This paper compares MIMO systems using the Quadrature Phase Shift Keying (QPSK) modulation scheme for two-channel distributions of Rayleigh and Weibull types. The performance of the work is far with the Minimum Mean Square Equalizer (MMSE) in terms of Bit Error Rate (BER) for various antenna number situations on the transmitter and receiver sides. The MIMO module is carried out using MATLAB code. The channel noise will be a signal of random noise that is generated. To mitigate the impact of inter-channel interference, the MMSE approach employs inverse filtering at the receiver, and BER will be calculated. According to simulation results, the system's performance is primarily influenced by the number of antennas; it decreased as the number of antennas increased, and the BER of the Weibull channel decreased as the two-parameter value increased

This study explores the problem of maximizing the sum rate in uplink multi-user Multiple-Input Multiple-Output (MIMO) using Rate-Splitting Multiple Access (RSMA) systems. The investigation revolves around the scenario where the Users (UEs) are single-antenna nodes transmitting data to a multi-antenna Base Station (BS) through the RSMA technique. The optimization process encompasses determining parameters such as UEs’ transmit powers, decoding order, and detection vector at the BS. An approach based on Deep Reinforcement Learning (DRL) is introduced to address this challenge. This DRL framework involves an action-refined stage and applies a Deep Deterministic Policy Gradient (DDPG)-based strategy. Simulation outcomes effectively demonstrate the convergence of the proposed DRL framework, where it converges after approximately 1,800 episodes. Also, the results prove the superior performance of the proposed method when compared to established benchmark strategies, where it is up to 45% and 86% higher than the local search and random schemes, respectively.

Owing to the rapid development of the ambient Internet of Things (IoT) industry, Backscatter Communication Systems (BCS) require higher receiver sensitivity for large-scale IoT scenarios than traditional Radio Frequency Identification (RFID) systems. This paper proposes a method of using Multiple-Input Multiple-Output (MIMO) technology to compensate for reflected signals in the 920 MHz backscatter communication systems. The researcher first created a MATLAB model to verify the theoretical feasibility and then built a One-Transmitter Two-Receiver (1T2R) BCS transceiver system compatible with the EPC global protocol for practical verification on LabVIEW. The ITIR and 1T2R tests were conducted using the National Instrument (NI) USRP-2952R device, the directional antennas, and the standard RF electronic tags. Through the process of superimposing and utilizing the phase shift between the two reflected carriers, it has been confirmed that the overall signal strength can be enhanced from 2.2 mV to 4.13 mV and 4.37 mV (nearly reaching 4.70 mV by using two Rx antennas in ideal conditions). After calculation, this advancement increases signal strength from −40.14 dBm (when using a single Rx antenna) to −34.18 dBm (when using two Rx antennas). The improvement in signal strength can provide a gain of 5.96 dB to the backscatter communication systems. Experimental results demonstrate that utilizing MIMO technology to the backscatter communication systems can effectively enhance the sensitivity of the receiver at 920 MHz.

In modern semiconductor manufacturing, optimizing plasma etching processes is key for advancing technology and achieving profitable production. In this study, we propose an efficient process flow to calibrate the etching mechanisms and optimize the etch profile by combining three-dimensional plasma simulations with machine learning (ML). Our proposed workflow speeds up the model calibration process and effectively addresses data scarcity issues by integrating extensive simulation data with TEM and other data sources. We have developed a three-dimensional Cl2/HBr/O2 plasma etching model for shallow trench isolation (STI), which is based on physical and chemical reaction mechanisms and external parameters consistent with actual production requirements, such as gas ratio, time duration, and chamber conditions. Machine learning is employed to tackle both forward and inverse problems. In the forward problem, the model predicts etching profiles under varying process conditions, with accuracy and similarity assessed using multiple criteria, including the structural similarity index (SSIM). Our approach achieves a notable reduction in prediction time, completing forecasts in 0.5 seconds compared to the 6500 CPU seconds required by TCAD. In the inverse problem, the model adjusts physical parameters to match observed results, improving its predictive accuracy. After model calibration, predictions are validated with wafer test outcomes, showing relative errors below 7%, thereby confirming the accuracy and robustness of the model parameters and the effectiveness of the entire process.

Cognitive Radio Networks (CRNs) aim to optimize the limited frequency spectrum by enabling spectrum sharing among different networks and making use of unoccupied frequency bands. The combination of massive multiple-input multiple-output (mMIMO) and CRNs has the potential to greatly improve the efficiency of upcoming wireless communication networks. In our research, we introduce an innovative approach to spectrum sharing in cognitive radio, utilizing 3D spatial data acquisition and Deep Learning for learning and decision-making. We incorporate mMIMO structures into cognitive radio base stations (CRBS) to extract angular information from user equipment (UE) and estimate Direction of Arrival (DoA) using Iterative Hard Thresholding (IHT). Our method involves deploying two base stations per cell for comprehensive 3D spatial spectrum coverage during spectrum prediction. We employ advanced Deep Learning techniques for spectrum sensing instead of reinforcement learning, enhancing CRN performance. Our approach includes a two-fold spectrum scheduling strategy, one focused on maximizing CR coverage and the other on optimizing transmission rates in CRN mMIMO scenarios. By fine-tuning Deep Learning parameters, our model achieves significantly higher Average Aggregate Sum Rate (AASR) compared to previous CRN spectrum sharing methods, without relying on reinforcement learning for spectrum sensing. Our research underscores the effectiveness of integrating Deep Learning into cognitive radio networks, offering the potential for enhanced spectrum utilization and network performance. Additionally, we address energy efficiency using the Nakagami fading channel model and evaluate key metrics, including channel occupancy and energy efficiency, through experimental analysis.

The low-pass characteristics of front-end elements including light-emitting diodes (LEDs) and photodiodes (PDs) limit the transmission data rate of visible light communication (VLC) and Light Fidelity (LiFi) systems. Using multiplexing transmission techniques, such as spatial multiplexing (SMX) and wavelength division multiplexing (WDM), is a solution to overcome bandwidth limitation. However, spatial correlation in optical wireless channels and optical filter bandpass shifts typically limit the achievable multiplexing gain in SMX and WDM systems, respectively. In this paper, we consider a multiple-input multiple output (MIMO) joint multiplexing VLC system that exploits available degrees-of-freedom (DoFs) across space, wavelength and frequency dimensions simultaneously. Instead of providing a new precoder/post-detector design, we investigate the considered joint multiplexing system from a system configuration perspective by tuning system parameters in both spatial and wavelength domains, such as LED positions and optical filter passband. We propose a novel spatial clustering with wavelength division (SCWD) strategy which enhances the MIMO channel condition. We propose to use a state-of-the-art black-box optimization tool: Bayesian adaptive direct search (BADS) to determine the desired system parameters, which can significantly improve the achievable rate. The extensive numerical results demonstrate the superiority of the proposed method over conventional SMX and WDM VLC systems.

Orthogonal time frequency space (OTFS) modulation is strongly considered as a promising solution for high-mobility communications. In contrast to conventional modulation techniques, wherein information symbols are multiplexed in a one-dimensional time or frequency domain, OTFS employs a two-dimensional modulation scheme by multiplexing information symbols in the delay-Doppler domain. This paper presents a comprehensive survey of OTFS. It starts with an overview of OTFS, its advantages over conventional air interface techniques, general block diagrams, and implementations. Subsequently, the paper explores the potential integration of multiple-input multiple-output and OTFS techniques. The paper further discusses the feasibility of integrating OTFS into multiple access techniques as a solution for maintaining acceptable performance in high-mobility scenarios. Then, widespread applications of OTFS in satellite communications are highlighted. Also, the potential utilization of OTFS modulation in integrated sensing and communications paradigm is thoroughly treated. In addition, the survey covers further applications of OTFS in deep learning, index modulation, underwater acoustic, and unmanned aerial vehicle communications. The paper concludes by pointing out numerous challenging and promising directions for future OTFS research.

Maximum-likelihood multiuser detection incurs a large computational complexity, and its low-complexity detection scheme suffers from a performance loss, where this tradeoff is inevitable and inherent in a classical computer. In this paper, we use the Grover adaptive search (GAS) to break the tradeoff, which is a quantum exhaustive search algorithm guaranteed to obtain the optimal solution, achieving a quadratic speedup. Specifically, we design two specific parameters of GAS to achieve the optimal performance with a reduced complexity: the initial threshold and the number of Grover rotations. The initial threshold of GAS can be optimized using a solution of semi-definite programming, and it is possible to calculate the distribution of the number of solutions smaller than the initial threshold in advance, which depends on instantaneous channel coefficients. In addition, we analyze the number of quantum gates required for GAS and show that the gate count can be reduced by bypassing the higher-order terms in the objective function, leading to a reduced circuit runtime. Our analysis and simulation results demonstrate that the proposed approach achieves the same performance as the optimal maximum-likelihood detection while reducing the query complexity of GAS, implying that the large constant overhead of quadratic speedup can be further reduced.

This work explores water-to-air optical wireless communication (W2A-OWC) transmission schemes and realizes a prototype of real-time W2A-OWC system based on field programmable gate array. This prototype comprises underwater nodes, aerial nodes, and transmitter-receiver hardware circuits. The real-time system employs multiple-input multiple-output technique and the low density parity check (LDPC) code of 5G-new radio for dynamic W2A-OWC. Additionally, the impact of background radiation is mitigated through spatial optical filtering. To validate the practical feasibility of the system, experiments are conducted in both indoor water tank and outdoor deep pool under strong background radiation. The frame error rate of the real-time system is tested under different LDPC code rates and transmitter-receiver configurations. The experimental results verify the feasibility of the realized W2A-OWC system.

This paper introduces a low-complexity multiple-input multiple-output (MIMO) detection method based on dimension-reduction-soft-demodulation (DRSD) with iterative soft minimum-mean-squared-error parallel interference cancellation (ISMMSE-PIC). The conventional ISMMSE-PIC detection method exhibits several drawbacks, such as inordinate dependence on decoder performance and modulation-order sensitivity. Therefore, a DRSD-based strategy is presented to search over a part of the set of transmitted symbols for calculating log-likelihood ratio (LLR) values, such as maximum likelihood detection, to improve detection performance. The scheme for the rest of the symbols directly utilizes ISMMSE-PIC detection for computing the corresponding LLR values. The computational complexity of the proposed scheme is similar to that of ISMMSE-PIC, whereas its bit error rate performance is comparatively higher. The complexity analysis and simulation results validate the proposed algorithm.

Due to its ability to reconfigure the optical channel, intelligent reflecting surface (IRS) has revealed its great potential for enhancing the performance of visible light communication (VLC) systems. In this paper, we apply a mirror array-based IRS in typical multiple-input multiple-output based VLC (MIMO-VLC) systems and optimize the IRS configuration to minimize the system bit error rate (BER). By utilizing the tight analytical BER upper bound, a BER minimization problem is formulated subject to the IRS configuration constraints. To solve this problem, an optimization algorithm is proposed which decomposes the original problem into three sub-problems, and the complexity of the algorithm is analyzed. The superiority of the obtained optimal IRS configuration scheme over the baseline scheme in terms of BER performance has been successfully verified through simulations in an indoor IRS-aided $4\times 4$ MIMO-VLC system applying different MIMO techniques.

Open Radio Access Networks (Open-RANs) require cost- and energy-efficient solutions to facilitate their large-scale deployment. A significant concern in multiple-input multiple-output (MIMO) systems employing traditional linear processing is the substantial number of radio frequency (RF) chains at the base station (BS), which is required to ensure accurate decoding of the spatially multiplexed streams. Recently, however, practical non-linear approaches, which facilitate near-optimal parallelizable tree searches, have been successfully implemented on actual systems and have demonstrated the capability to considerably reduce the required RF chains without affecting user performance. Similar to QR decomposition (QRD), which is used to perform channel inversion in linear systems, these non-linear approaches employ a sorted QRD (SQRD) to curtail the search complexity. However, this can be a significant bottleneck for general software-based non-linear solutions, preventing them from fully exploiting their gains. To address the latency limitations of SQRD, this work presents a high-throughput hardware accelerator based on reformulating the underlying Modified Gram Schmidt process (MGS) to extract further parallelism than previous designs. Implementations of the proposed architecture demonstrate at least 2-fold improvements in the achievable throughput and processing latency over existing $4\times 4$ and $8\times 8$ field-programmable gate array (FPGA) implementations and can be scaled up to $16\times 16$ MIMO systems. Furthermore, the proposed accelerator was integrated with a software framework that can considerably offload the processing burden for a higher number of streams under strict latency conditions.

This paper presents a miniaturized Quad-Port MIMO antenna for UWB application. Employing Characteristic Mode Analysis, the single element UWB antenna is analysed to achieve a compact design. Using the Theory of Characteristic Mode, the significant modes and their current distribution are analysed, which helps to modify the radiator and ground plane to generate more significant modes to yield a wider frequency band. Four circular-shaped radiators with tapered feeds are placed orthogonally on the FR4 substrate to improve isolation, and partial ground planes are located on the opposite surface. Furthermore, a modified Pattee-cross-shaped parasitic element is introduced between the antenna elements and shorted with the ground planes via metallic shorting pins. This novel technique improves isolation compared to the conventional integration method of the partial ground planes through strip lines. The proposed antenna achieves less than −20 dB mutual coupling over most of the frequency band ranging from 2.51–18 GHz. [ABSTRACT FROM AUTHOR]

Summary: In this study, we propose a novel transmission technique for multiple‐input multiple‐output (MIMO) systems as a partial response to ever‐growing demand for the increased spectral efficiency. The introduced scheme, called adaptive power permutation modulation (APPM), relies on the distinct power allocations on the conventionally modulated symbols to convey a certain number of additional information bits. Unlike the traditional power allocation strategies which generally aim to combat the channel fading and entail some form of channel state information (CSI) at the transmit side, APPM utilizes different power levels to convey additional information and does not necessitate any kind of CSI at the transmitter. The proposed approach is applied to two well‐known MIMO configurations, Alamouti space‐time block coding and zero‐forcing beamforming, by embracing a general frequency‐selective fading scenario under digital phase modulation. Both the modulation order and the power allocation levels on the modulated symbols are adaptively determined based on a set of additional information bits. It is shown that in addition to the conventionally modulated symbols, an extra sequence of N bits can be conveyed without any significant additional complexity where N equals the number of subcarriers. Also, it is demonstrated that considerable transmit power savings can be attained when compared with the standard schemes under a certain target spectral efficiency. [ABSTRACT FROM AUTHOR]

This manuscript presents a 50 Ω microstrip-fed quad-element high isolated ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna with band-notched characteristics. The overall area of the proposed structure is 0.33 λ o × 0.33 λ o mm2 (where λ o depicts the free space wavelength corresponding to the lower cutoff frequency, i.e. 2.54 GHz), etched on an FR-4 substrate of thickness 0.8 mm. The top layer has four semicircular disc-shaped radiating elements that are identical and orthogonal to obtain better inter-element isolation and compactness. A reverse two-shaped slot is etched onto the radiating patches to attain a band-rejection capability. Moreover, a decoupling structure is also placed at the top layer to suppress the unwanted surface waves. The bottom layer consists of a ground plane, which is further modified with quasi-self complementary and meandered line slots. A rectangular slot is also etched below the feed line to better match the impedance near the lower cutoff frequencies. The simulated reflection coefficients (S 11) of the proposed antenna are less than −10 dB over 2.54 to 10.74 GHz frequencies except at 3.37 to 4.15 GHz (WiMAX/C band), and the simulated inter-port isolation (S 21) is greater than −15 dB over the entire UWB range of frequencies (3.1 to 10.6 GHz). Also, the measured S -parameter results well agreed with the simulated ones. Furthermore, the simulation study of the 20-element UWB-MIMO antenna is also investigated using the proposed quad-element structure. [ABSTRACT FROM AUTHOR]

In spatial domain signal processing, it is necessary to equip more antennas at the receiver to improve spatial demultiplexing capability. However, increasing the number of antennas under restricted space will reduce antenna spacing and raise the channel correlation, making the number of signal streams spatially demultiplexed much smaller than that of antennas. This paper proposes a method to design a space-time-isomeric (SPATIO) array based on metasurface antennas under wireless multipath conditions. Each antenna in this array has a different pattern and varies independently with time, reducing the channel correlation by superposing multipath at distinct positions and moments. Based on the SPATIO array, we present an array parameter design scheme based on infinity norm minimization, which can maximize the received energy of each stream while separating multi-stream received signals. Simulation results illustrate the performance of the SPATIO array for multi-stream signal reception. Compared with conventional multiple-input multiple-output arrays, the proposed array can reduce the bit error rate by one order of magnitude under the same simulation conditions. [ABSTRACT FROM AUTHOR]

To solve the problems of low spectral efficiency and poor performance of physical layer security (PLS) in single-input single-output (SISO) wireless systems with adaptive modulation in the presence of an active eavesdropper, multiple-input multiple-output (MIMO) wireless systems with secure adaptive modulation (SAM) were proposed.The design idea was to improve the spectral efficiency of the main channel by antenna diversity technology, which used the transmit antenna selection (TAS) at the transmitter and the maximal ratio combining (MRC) at the legitimate receiver to improve the signal-to-noise ratio.Simultaneously, the PLS of the legitimate receiver was guaranteed by limiting the bit error rate of the active eavesdropper so that it could not demodulate the confidential information from the main channel.With the joint constraints of the average transmission power and PLS, the optimal switching thresholds and the analytical expressions of spectral efficiency and the eavesdropper’s average bit error rate of the SAM-MIMO systems were derived.Numerical and simulation results show that SAM systems using TAS/MRC technology can not only improve the spectral efficiency of the main channel, but also ensure the PLS against the active eavesdropper, compared with the SAM-SISO systems.

Fifth-generation (5G) wireless systems increased the bandwidth, improved the speed, and shortened the latency of communications systems. Various channel models are developed to study 5G. These channel models reproduce the stochastic properties of multiple-input multiple-output (MIMO) antennas by generating wireless multipath components (MPCs). The MPCs with similar properties in delay, angles of departure, and angles of arrival form clusters. The multipaths and multipath clusters serve as datasets to understand the properties of 5G. These datasets generated by the Cooperation in Science and Technology 2100 (COST 2100), International Mobile Telecommunications-2020 (IMT-2020), Quasi Deterministic Radio Channel Generator (QuaDRiGa), and Wireless World Initiative New Radio II (WINNER II) channel models are tested for their homoscedasticity based on Johansen's procedure. Results show that the COST 2100, QuaDRiGa, and WINNER II datasets are heteroscedastic, while the IMT-2020 dataset is homoscedastic. [ABSTRACT FROM AUTHOR]

Now a days, huge amount of data is communicated through channels in wireless network. It requires an efficient parallel operation for the optimal utilization of frequency, time allocation and coding model for signal subspace factorization in smart antenna. In view of this requirement, an efficient reconfigurable optimal source detection and beam allocation algorithm (RoSDBA) is proposed. The proposed algorithm is able to allocate desired signal to the user space to reduce the noise and also for efficient allocation of subspace to remove disturbance in all directions. The proposed method efficiently utilizes the antenna array elements by accurate identification and allocation of antenna array elements such as individual radiators, radiation beam, signal strength, and disturbance factor. With respect to simulation analysis, the proposed method shows better performance for the resolution, radiation beam allocations, identification bias, distribution factor and time taken for the detection of various array arrangements and source numbers. [ABSTRACT FROM AUTHOR]

Copyright of Frontiers of Information Technology & Electronic Engineering is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: Multiple‐input multiple‐outputs (MIMOs) have eminent quality in maximizing the throughput of wireless communication models. In MIMO, the antenna arrays can be utilized for fulfilling the needs of 5G by utilizing various spatial signatures of users. Even though 5G communication is imminent, there exist issues, like network interference that arise due to reused frequency spectrum resources. This delving presents an optimized deep model for suppressing interference occurring in the Rayleigh channel in the multiple‐user MIMO (MU‐MIMO) model. Here, an MU‐MIMO model is employed with correlated interference wherein there exist various users around the base station (BS) with several antennas at the transmitter and receiver. Here, a deep neuro‐fuzzy network (DNFN) is used to upgrade the performance of detectors underneath correlated interference. Here, the model comprises zero forcing‐maximum likelihood detection (ZF‐MLD) that assists to generate an initial estimate of broadcasted signals in a particular time slot. The DNFN is used to capture latent correlation among several symbols. Here, the DNFN training is performed using developed autoregressive Henry gas spider monkey optimization (RHGSMO), which is the combination of conditional autoregressive value at risk (CAViaR), Henry gas solubility optimization (HGSO), and spider monkey optimization (SMO). With the lowest symbol error rate (SER), bit error rate (BER), and signal to interference and noise ratio (SINR), the suggested RHGSMO‐based DNFN performed better than existing approaches. [ABSTRACT FROM AUTHOR]

For optical wireless communication systems with restricted bandwidth, combining multiple-input multiple-output (MIMO) transmission with orthogonal frequency division multiplexing (OFDM) modulation was found to be a highly effective method of boosting system capacity. This paper presents and analyzes two optical OFDM-based MIMO schemes for visible light communications, namely OFDM-based time domain general spatial modulation (TD-GSM) and OFDM-based time domain general spatial multiplexing (TD-GSMP), which utilize general-numbered MIMO configurations of light-emitting diodes (LEDs). These schemes exhibit reduced complexity and provide enhanced spectral efficiency (SE) in comparison to conventional frequency-domain (FD) GSM and GSMP schemes, achieved by transmitting twice the spatial information. Previous research in this area typically employed an even number of LEDs for spatial-based MIMO transmission, represented as 2 l a , where l a is the number of spatial bits. However, to enhance SE, this paper introduces schemes that can accommodate a general number of LEDs without the constraint of an even-numbered LED configuration. In indoor environments, several LEDs are already used for illumination purposes, so incorporating additional LEDs for communication does not introduce complexity to the system. To detect both spatial and radiated information, a maximum-likelihood estimation algorithm is proposed. Simulation results demonstrate that, depending on the user's position, selecting the optimal MIMO configuration is crucial for achieving desired bit error rate (BER) performance and SE requirements. Moreover, as the total number of LEDs increases relative to the active number of LEDs, the modulation order required to transmit signals decreases in order to support a specified SE, resulting in improved BER performance. When all LEDs are active during communication, TD-GSMP outperforms TD-GSM in terms of BER performance. The results also show the superiority of TD schemes over FD schemes in terms of BER performance. [ABSTRACT FROM AUTHOR]

This paper first describes a binary Low-Density Parity-Check (LDPC)-coded Probabilistic Shaping (PS) scheme for Multiple-Input Multiple-Output (MIMO) systems based on Signal Space Diversity (SSD). Second, a Nonbinary (NB) LDPC-coded PS scheme for MIMO systems based on SSD is proposed. The first scheme can be used to obtain a shaping gain, whereas the second can also realize a coding gain. The theoretical average mutual information of the optimized rotated quadrature amplitude modulation constellations is analyzed and the simulated error performance with 2 ​× ​2 and 4 ​× ​4 MIMO schemes is investigated. The theoretical average mutual information analysis and simulation results show that the proposed NB LDPC-coded PS scheme for MIMO systems based on SSD is reliable and robust, and is therefore suitable for future wireless communication systems.

Underwater wireless optical communication (UWOC) has been widely used in the construction of underwater communication network for the advantages of high data rates, small latency, high flexibility and scalability.However, due to the absorption and scattering effects of seawater, the spatial characteristics of UWOC links have not been studied extensively, especially in multiple-input multiple-output (MIMO) scenario.A linear array MIMO UWOC link geometry was considered and a weighted exponential function polynomial (WEFP) model was proposed to characterize the photon irradiance distribution at the receiving plane of general MIMO UWOC links with arbitrary numbers of light sources.Numerical results suggest that the proposed WEFP model fits well with the results of Monte Carlo simulations in turbid water environment.

This paper investigates two novel polarization- and pattern-diversity glass dielectric resonator antennas (DRAs), both of which are for tri-band (2.4, 5.2, and 5.8 GHz) wireless fidelity (WiFi) applications. It also investigates what type of diversity antenna is most suitable for WiFi router applications by comparing the two DRAs, along with a new space-diversity glass DRA. These three diversity glass DRAs are also compared with a commercial space-diversity monopole pair to benchmark the performance of the glass DRA in WiFi router applications. In our polarization-diversity antenna, a double-port feeding scheme is developed to excite different DRA modes. The frequencies of the DRA modes are tuned by using a stepped DRA. For the pattern-diversity design, a stacked DRA is introduced to broaden the bandwidth for both the conical and broadside radiation modes. All three of the new diversity antennas were fabricated and measured to verify the simulations. In our experiment, the bit error rate (BER) of the three diversity glass antennas and the reference space-diversity monopole antenna was also measured, and the results are compared and discussed. It is found that the polarization-diversity omnidirectional DRA has the most stable BER among the three.

In this paper, channel estimation for Millimeter Wave (mmWave) Multiple Input Multiple Output (MIMO) communication system is presented. In the frequency domain, the Sparse Bayesian Learning-based Kalman Filter (SBL-KF) scheme is developed to estimate the sparse channel vector of hybrid mmWave MIMO architecture. The mmWave MIMO hybrid architecture provides reduced power loss and achievable data rates at mmWave frequencies. Frequency-selective channels are sparse at mmWave frequencies. The recovery of the sparse channel is estimated using different channel estimation methods. The hybrid precoding technique achieves both multiplexing gain and array gain in mmWave channels. Simulation results of the proposed SBL-KF scheme show low estimation error over the existing Orthogonal Matching Pursuit, Simultaneous Orthogonal Matching Pursuit, Simultaneous Weighted Orthogonal Matching Pursuit algorithm and SBL scheme. The complexity of the online estimation SBL-KF algorithm is low and it is ideally suited for implementation in an efficient mmWave MIMO system. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The downlink (DL) of a reconfigurable intelligent surface (RIS)-aided multi-user (MU) millimeter wave (mmWave) multiple-input multiple-output (MIMO) system relying on a non-diagonal RIS (NDRIS) phase shift matrix is considered. A max-min fairness (MMF) problem is formulated under the total transmit power constraint while employing joint active hybrid beamforming (HBF) both at the base station (BS) as well as at each user equipment (UE), and passive beamforming at the NDRIS. To solve this non-convex problem, a sequential optimization method is conceived, wherein the UE having the poorest channel is identified first, which is termed as the worst-case UE. Then the phase shifter coefficients of the NDRIS are optimized using the alternating direction method of multipliers (ADMM) followed by the hybrid transmit precoder (TPC) and receiver combiner (RC) design using the Karcher mean, the least squares and the regularized zero forcing (RZF) principles. Finally, the optimal power allocation is computed using the path-following algorithm. Simulation results show that the proposed NDRIS-HBF system yields an improved worst-case UE rate in comparison to its conventional diagonal RIS (DRIS)-HBF counterpart, while approaching the half-duplex relay (HDR)-HBF benchmark for large values of the number of reflecting elements (REs). Furthermore, the energy efficiency (EE) of the NDRIS structure is significantly higher than that of the DRIS, HDR systems, while being higher than that achieved by the full-duplex relay (FDR) system at high SNR.

It is well-known that the availability of transmit and receive arrays in colocated multiple-input multiple-output radar systems can be exploited to detect multiple targets, and estimate their range and angular coordinates. Unluckily, the accuracy achieved in the estimation of target parameters can be severely affected by hardware nonidealities. The impact of these nonidealities can be mitigated through the adoption of specific methods explicitly developed to estimate and compensate for them, i.e., briefly, of calibration methods. As far as we know, until now, most of the calibration techniques proposed in the technical literature for colocated multiple-input multiple-output radars are based on the idea of placing one or more reference targets in front of the considered radar device at perfectly known and fixed locations, and quantifying the difference between the expected radar image and the measured one. In this manuscript, two novel calibration methods are proposed. Both exploit the measurements captured by a colocated multiple-input multiple-output radar device at multiple positions; for this reason, the acquisition of such measurements involves the movement of the radar. The first one does not require any knowledge about the nature, number, position or radar cross section of the reference targets, provided that all these are in far-field; the second one, instead, needs a single reference target in near-field conditions, with the only constraints for it to be pointwise and isolated from stray targets in the range domain. This drastically simplifies the experimental setup to be employed for radar calibration. The proposed methods are tested on a commercial radar device and compared with a traditional method for radar calibration.

The energy efficiency (EE) of the reconfigurable intelligent surface (RIS) aided multiuser (MU) millimeterwave (mmWave) multi-input multi-output (MIMO) downlink is maximized by jointly optimizing the transmit power and number of active radio frequency (RF) chains. The base band (BB) transmit precoder (TPC) of this system is derived first by using the zero-forcing (ZF) technique for a given RF TPC and combiner at the base station (BS) as well as the phase shift matrix at the RIS. Furthermore, the ergodic sum-rate of the system is derived assuming a large number of antennas at the BS and users, followed by formulating the EE maximization problem subject to specific constraints imposed on the transmit power and on the number of RF chains. Then a low complexity sequential method is proposed for solving the above optimization problem, thus determining both the optimal transmit power and the number of active RF chains. Finally, simulation results are presented for demonstrating the improved EE performance of an RIS-aided mmWave MIMO system for a limited number of RF chains and transmit power at the BS.

In this work, we investigate a practical secure multiple-input single-output (MISO) wireless transmission of information from a source to a destination assisted by cooperative devices. In the first phase, a space-time block code (STBC) is employed; thus, the source does not require any channel state information (CSI). In the second phase, the cooperative devices are divided into two groups, depending on whether they serve for relaying or jamming. Based on the imperfect CSI toward the destination, the devices allocated to the relay group assist the source in forwarding information, whereas those within the jamming group send artificial noise (AN) so as to prevent the eavesdropper from receiving information. Furthermore, the system utilizes two grouping strategies, referred to as random and adaptive. In the former case the role (relaying or jamming) of each device is predetermined randomly, whereas in the latter case it is determined autonomously depending on the decoding results. We analyze the outage probability of our proposed system with and without power allocation optimization under the assumption of imperfect CSI at the cooperative devices, and their accuracy is verified by Monte-Carlo simulations.

For several years, mobile edge computing (MEC) has been highlighted as a promising technique to support emerging computation-intensive applications in cellular networks, e.g., 5G and 6G. Most previous studies have mainly focused on jointly optimizing communication (i.e., radio) and computation resources to improve offloading performance without considering specific communication protocols required for operating the MEC systems in practice. In this article, we newly design a contention-based access reservation protocol (ARP) for efficiently supporting simultaneous task offloading requests from a number of edge devices (EDs), and further define necessary signalings required to determine an optimal offloading factor. Thereafter, we formulate an optimization problem to find the optimal offloading factor that minimizes the task-completion latency. Through simulations, we mainly evaluate the task-completion latency performance of the MEC system incorporated with our proposed access reservation protocol under a multiple-input multiple-output (MIMO) environment. Particularly, we thoroughly investigate several practical aspects such as the effect of the number of edge devices attempting to join the task offloading, the number of antennas equipped at the edge device, and the amount of reserved radio resources required for configuring access reservation protocol on the optimal offloading decision. From the results, we verify the validity of our approach, and provide meaningful insights regarding how the network should be configured to fruitfully exploit the offloading with the MEC systems.

Validating RF applications is traditionally time consuming, even for relatively simple systems. We developed the WISCA Software-Defined Radio Network (WISCANet) to accelerate the implementation and validation of radio applications over-the-air (OTA). WISCANet is a hardwareagnostic control software that automatically configures and controls a software-defined radio (SDR) network. By abstracting the hardware controls away from the user, WISCANet allows a non-expert user to deploy an OTA application by simply defining a baseband processing chain in a high level language. This technology reduces transition time between system design and OTA deployment, accelerates debugging and validation processes, and makes OTA experimentation more accessible to users that are not radio hardware experts. WISCANet emulates real-time RF operations, enabling users to perform real-time experiments without the typical restrictions on processing speed and hardware capabilities. WISCANet also supports multiple RF front-ends (RFFEs) per compute node, allowing sub-6 and mmWave systems to coexist on the same node. This coexistence enables simultaneous baseband processing that simplifies and enhances advanced algorithms and beyond-5G applications. In this study, we highlight the capabilities of WISCANet in several sub-6 and mmWave over-the-air demonstrations. The open source release of this software may be found on the WISCA GitHub page.