This study introduces an innovative K-/Ka-band planar active shared-aperture phased array (ASAPA), advancing low earth orbit (LEO) terminal design through synergistic innovations in shared-aperture topology and three-dimensional (3D) integration. Breaking from conventional shared-aperture topologies plagued by cross-band interference and radiation pattern distortion, we propose a partial-element-reuse-based (PER) topology that strategically repurposes 50% of dual-band dual-polarized elements for simultaneous transmit and receive (STAR) operation. This configuration eliminates active element pattern distortion while achieving a reduction in element count, enabling wide-angle beam scanning essential for dynamic satellite tracking. Furthermore, a sandwich-structured printed circuit board (PCB) lamination method is further employed to streamline integration by partitioning functional modules into antenna, coupler, and active circuit layers interconnected via ball grid array (BGA) technology. This 3D integration strategy simplifies vertical interconnects, minimizes PCB layer requirements, and enhances thermal dissipation through embedded air gaps. Experimental results validate robust beamforming performance across ±60° scanning ranges for both transmitting and receiving arrays, achieving high transceiver isolation and signal integrity, which are imperative for high-capacity satellite links. By addressing key bottlenecks in LEO terminal design, the proposed innovations can accelerate the deployment of energy-efficient, cost-effective satellite networks, thus advancing the 6G vision of ubiquitous global connectivity.

An LC-VCO incorporating differentially pumped varactors for$3^{\mathrm {rd}}$order harmonic generation is demonstrated in a 65-nm bulk CMOS process with an$f_{max}$of ~250 GHz. The differentially pumped N-type Accumulation mode MOS varactor pair acting as a symmetric varactor serves as a frequency tuning element, as well as the non-linear reactive elements for harmonic generation. The measurements show that the circuit has a peak radiated power of -15.2 dBm with a frequency tuning range between 361.4 to 383.3 GHz or 5.9 %, and a peak DC-THz efficiency of 0.102 %. Among the CMOS oscillator signal generators with an on-chip antenna and output frequency greater than 300 GHz, the circuit exhibits the state-of-the-art DC-THz efficiency.

This paper proposes a 24-29.5 GHz$2\times 2$transmitter (TX) and receiver (RX) front-end chipset with streamlined intermediate frequency (IF) interfaces for digital beamforming (DBF) systems. An ultra-compact 90° coupler employing a three-dimensional (3-D) coupling structure achieves a 70% reduction in size compared to typical Lange couplers while maintaining excellent performance. This 3-D 90° coupler enables the synthesis/distribution of IF I-Q signals within the transceiver (TRX), enhancing the feasibility of mmWave DBF by reducing the demand for baseband channels and facilitating scalability for multi-beam arrays. To ensure a low-level error vector magnitude (EVM) in the TRX, the chipset employs joint package design for optimal power and noise performance. It utilizes an image-reject mixer to suppress RX image noise and introduces a DC-offset in the single-sideband up-converter for LO leakage regulation. Additionally, a frequency doubler chain is incorporated to enhance phase noise performance. Fabricated using 0.13-$\mu $m SiGe BiCMOS technology and packaged in WLCSP process, the TX achieves an average output 1-dB compression point ($OP_{1dB}$) of 20 dBm per channel. The RX chip features a minimum noise figure (NF) of 3.4 dB. Over-the-air (OTA) measurements conducted over a 1.1-m distance reveal a transmission data rate of up to 8 Gb/s using 16-QAM modulation at 25 GHz. Furthermore, when employing a 400-MHz 64-QAM 5G New Radio (NR) modulation, the system maintains EVM levels below -33 dB at 25 GHz and below -30 dB over 24-29.5 GHz.

As a wideband radar system, spaceborne synthetic aperture radar (SAR) has been widely applied in multiple applications, such as maritime surveillance and terrain observation. However, with the increase of electromagnetic devices, spaceborne SAR suffers from radio frequency interference (RFI) frequently. Many previous methods have been effective in interference mitigation, among which semiparametric methods demonstrate excellent performance and high efficiency. However, as a classic low-rank recovery method, robust principal component analysis (RPCA) usually suffers from the over-penalization problem of large singular values. Although some useful schemes were proposed to address this issue, their performance may still degrade if the low-rank characteristics of interference are not prominent. To overcome these obstacles, we first investigate the characteristics and distributions of different SAR signals and leverage kurtosis to differentiate interference and real echoes. Herein, interference tends to have a low kurtosis while the real echoes tend to have a high kurtosis. Then, we improve the low-rank recovery model with kurtosis and propose the kurtosis-based reweighted nuclear norm (KRNN) model to precisely extract interference components. Then, we derive the closed-form solution of the KRNN model via the alternating direction method of multipliers (ADMM) framework. Through the proposed KRNN method, we can effectively mitigate interference, preserve real echoes, and solve the problems of over-penalization and nonideal low-rank property. Finally, we conduct numerical experiments using the measured Sentinel-1 and LT-1 data to demonstrate the effectiveness and robustness of our proposed method.

Forward-looking multi-input multi-output synthetic aperture radar (FL-MIMO-SAR) is the state-of-the-art technique to achieve the high-resolution image of the front area. However, the performance of FL-MIMO-SAR is primary limited by left-right Doppler ambiguity resolution. To address this issue, a novel space-time cascade imaging framework is proposed. Concretely, the Doppler-division multiplexing MIMO (DDM-MIMO) scheme is adopted to achieve the waveform orthogonality and the back-projection (BP) time-domain algorithm is applied to obtain high-resolution SAR images. Furthermore, the effect of array errors is analyzed and calibrated, which is essential for subsequent Doppler ambiguity resolution using the linearly constrained minimum variance (LCMV) beamforming. Finally, experimental analysis is performed to confirm the effectiveness of the proposal.

Lack of full use of phase information is a common problem in synthetic aperture radar (SAR) automatic target recognition (ATR). In this paper, we propose a complex manifold multi-scale feature fusion network (CMMFF-Net) for SAR image target recognition. Unlike traditional complex-valued networks, we extend SAR complex images to complex manifold space and construct a complex-valued manifold feature extraction module, which can extract manifold features from SAR amplitude and phase images. Moreover, the multiscale feature extraction and fusion module helps to further extract richer and discriminative target features by fusing multiscale information. Experimental results on SAR complex image dataset demonstrate the effectiveness of proposed method.

Human emotions are intricate psychological phenomena that reflect an individual’s current physiological and psychological state. Emotions have a pronounced influence on human behavior, cognition, communication, and decision-making. However, current emotion recognition methods often suffer from suboptimal performance and limited scalability in practical applications. To solve this problem, a novel electroencephalogram (EEG) emotion recognition network named VG-DOCoT is proposed, which is based on depthwise over-parameterized convolutional (DO-Conv), transformer, and variational automatic encoder-generative adversarial network (VAE-GAN) structures. Specifically, the differential entropy (DE) can be extracted from EEG signals to create mappings into the temporal, spatial, and frequency information in preprocessing. To enhance the training data, VAE-GAN is employed for data augmentation. A novel convolution module DO-Conv is used to replace the traditional convolution layer to improve the network. A transformer structure is introduced into the network framework to reveal the global dependencies from EEG signals. Using the proposed model, a binary classification on the DEAP dataset is carried out, which achieves an accuracy of 92.52% for arousal and 92.27% for valence. Next, a ternary classification is conducted on SEED, which classifies neutral, positive, and negative emotions; an impressive average prediction accuracy of 93.77% is obtained. The proposed method significantly improves the accuracy for EEG-based emotion recognition.

This article presents a fully packaged 94-GHz 16-channel local oscillator (LO) phase-shifting transmitter (TX) and a single-channel receiver (RX). The implementation is accomplished using a hybrid integration scheme, combining high-output-power 100 nm GaAs pHEMT front-end chips and highly-integrated 130 nm SiGe BiCMOS beamformer chips. High-accuracy LO phase shifting is achieved with the utilization of a commercial SiGe-based four-channel beamformer chips, offering 7-bit phase control at 24–28 GHz. A 26-to-78 GHz tripler chain using power-enhancing and harmonic-suppression techniques, a 16-to-94 GHz bi-directional mixer, and a 94-GHz power amplifier are designed in the transmitter front-end chip based on the GaAs process. The GaAs transmitter front-ends are wire-bonded to microstrip lines and then converted to low-loss substrate integrated waveguides (SIWs), which directly feed a high-gain TEM horn antenna array. The inter-element spacing of the transmitter array is optimized to 1.6 mm ($0.5 \lambda _{0}$@94 GHz) for a wide scanning range. The 16-channel transmitter achieves a wide scanning range of ±50° and a peak effective isotropic radiated power (EIRP) of 43.6 dBm at 94 GHz. The GaAs receiver chip is packaged with the WR10 waveguide RF interface and connected to a horn antenna. The packaged GaAs receiver module achieves a conversion gain (CG) of 25 dB and a noise figure (NF) of 5.8 dB. Additionally, the 16T1R over-the-air (OTA) measurement supports 5G New Radio 400-MHz 64-QAM signal between 88 and 94 GHz over a 5-meter ±48° scanning range.

This paper presents a monolithically integrated E-band amplifier multiplier chain (AMC) developed in 130 nm SiGe BiCMOS process. This E-band AMC is composed of a 25 GHz 1:1 power divider, two 25 GHz driver amplifiers (DA1,2), a 75 GHz passive frequency tripler, and a 75 GHz power amplifier (PA). By applying a bypass tuning capacitor based power enhancing technique in the single-ended DA and PA, the output power and power-added-efficiency (PAE) of the AMC have been effectively improved. Benefiting from the proposed passive tripler core with second harmonic suppression function, and the impedance matching network with frequency selection characteristics, the AMC presents better harmonic suppression performance compared with the conventional topology. The bias circuits with temperature compensation are applied to the DA and PA to ensure the performance of the AMC when the temperature changes. The AMC has a measured output power exceeding 0 dBm in the entire E-band frequency range with a peak output power of 10.9 dBm at 77 GHz, and exhibits a record PAE of 8.25 %. Within the 3 dB operating frequency range from 69 to 87 GHz, the rejection of fundamental and second harmonics are better than 33.5 dB. The AMC can work properly between −40°C and 125 °C with the proposed temperature compensation bias circuits.

Abstract The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

Millimeter-wave (mmWave) technology has been well studied for both outdoor long-distance transmission and indoor short-range communication. In the recently emerging fiber-to-the-room (FTTR) architecture in the home network of the fifth generation fixed networks (F5G), mmWave technology can be cascaded well to a new optical network terminal in the room to enable extremely high data rate communication (i.e., >10 Gb/s). In the FTTR+mmWave scenario, the rapid degradation of the mmWave signal in long-distance transmission and the significant loss against wall penetration are no longer the bottlenecks for real application. Moreover, the surrounding walls of every room provide excellent isolation to avoid interference and guarantee security. This paper provides insights and analysis for the new FTTR+mmWave architecture to improve the customer experience in future broadband services such as immersive audiovisual videos.

With the rapid development of the Internet of Things and cloud computing technologies, the Internet of Things technology based on comprehensive perception and interconnection and cloud computing based on virtualization, dynamic resources, and parallel computing have become the driving force for the innovation and development of informatization and intelligence. The cloud‐based Internet of Things mobile medical is an ecosystem of health information and medical information, with the medical Internet of Things at its core and highly mobile and highly shared information. Therefore, in the context of in‐depth research on mobile medical care, research on mobile postoperative thyroid monitoring and management systems based on the Internet of Things and cloud computing is a practical tool for promoting the development of mobile medical systems. Monitoring and Management. In this experiment, 48 cases of patients undergoing thyroid surgery were selected from a hospital. The experimental group was informed by the experiment that they need to be equipped with sensors. The control panel and GPS positioning module are used to obtain the exact position of the patient at the first time. The loading of the sensor is agreed by the patient and the patient’s family. Afterward, the control group will not be processed. It will conduct functional tests and software performance tests on the mobile medical monitoring and management system and analyze the satisfaction of medical staff with the mobile medical monitoring and management system. Experiments have proved that the cloud computing medical monitoring and management system is used to obtain the exact location of the patient in the first time, and the response time needs to be shorter. The response time of the system increases with the increase of the number of sensors (P < 0.05), which shows that the mobile medical monitoring and management system is essential for medical care and medical care. Obtaining the exact position of the patient for the first time is of great importance for the successful rescue of the patient.