Considering diverse quality of service (QoS) requirements in the Internet of Things, non-orthogonal multiple access (NOMA) is adopted in this paper to serve a delay-sensitive user (DU) and a broadband user (BU) simultaneously. Short-packet communication is employed by the DU to ensure the low-delay requirement, while the BU conveys long-packet to achieve high data rate transmission. As the reliability of DU is guaranteed by resource allocation schemes, we focus on the transmission efficiency of the BU. General and deep fading scenarios are considered in the communications and the corresponding resource allocation schemes are designed. The closed-form expressions for effective throughput of the BU for the NOMA and orthogonal multiple access (OMA) schemes are derived in the two fading scenarios with the corresponding resource allocation schemes. Numerical results are presented to verify our analysis and give more insights into system performance. The results show that the proposed resource allocation schemes are effective in their corresponding fading scenarios. Moreover, the results also show that NOMA can outperform OMA in both two fading scenarios in terms of effective throughput. Especially when the packet length is short and the reliability constraint is strict, the performance gains of NOMA over OMA become more remarkable.

In this study, we propose a novel pixel-level non-local similarity (PNS)-based reconstruction method for millimeter-wave interferometric synthetic aperture radiometer (InSAR) imaging. Unlike traditional compressed sensing (CS) methods, which rely on predefined sparse transforms and often introduce artifacts, our approach leverages structural redundancies in InSAR images through an enhanced sparse representation model with dynamically filtered coefficients. This design simultaneously preserves fine details and suppresses noise interference. Furthermore, an iterative refinement mechanism incorporates raw sampled data fidelity constraints, enhancing reconstruction accuracy. Simulation and physical experiments demonstrate that the proposed InSAR-PNS method significantly outperforms conventional techniques: it achieves a 1.93 dB average peak signal-to-noise ratio (PSNR) improvement over CS-based reconstruction while operating at reduced sampling ratios compared to Nyquist-rate fast fourier transform (FFT) methods. The framework provides a practical and efficient solution for high-fidelity millimeter-wave InSAR imaging under sub-Nyquist sampling conditions.

A unified-mode analysis method for modeling symmetric networks is proposed in this paper. Adjusting to the characteristics of Marchand balun circuits, a unified-mode circuit model is constructed by introducing virtual impedance. The tenable condition of a Marchand balun with connecting segments is then derived. The parameter constraint of Marchand balun’s input matching is given in a quarter-saddle diagram. Simulated results under different parameter conditions verify the validity of the derived formulas. Based on the derived formulas, the traditional isolation circuit and impedance matching circuit are merged with a Marchand balun to achieve matching for all ports and full-frequency isolation between output ports. A microstrip balun with input and output impedance values of 50 Ω, operating at 1.5 GHz, is simulated, fabricated, and measured. The simulated and measured results of the microstrip balun are in good agreement. When the core parameters remain unchanged, an impedance transformer is inserted in front of the input port of the balun to realize a balun with a topology characterized by flexible impedance transformation. A balun with an input impedance of 35 Ω and different output impedances of 50 Ω and 75 Ω is simulated and fabricated to verify the design concept. Measured results show that an amplitude balance of less than 0.4 dB and a phase balance of less than 3° for a fractional bandwidth of 50%. It should be mentioned that all design equations are closed-form and can be readily employed to design symmetric networks.