This article presents the design theory and implementation of a fully integrated octave-bandwidth monolithic microwave integrated circuit (MMIC) power amplifier (PA). While continuous-mode PA design theory provides a wide impedance design space for fundamental and harmonic frequencies, it faces limitations in octave-bandwidth scenarios, since the second harmonic frequency ($2f_{low}$) overlaps with the fundamental frequency ($f_{high}$). To address this challenge, we propose a novel design methodology that utilizes hybrid impedance selection based on the continuous-mode impedance trajectory at the fundamental frequency and the load-pull-based selection of feasible second harmonic impedance, addressing the octave-bandwidth challenge. A coupled-line-based matching network is introduced to simultaneously realize fundamental and harmonic impedance matching in an MMIC process. To validate the proposed approach, an octave-bandwidth gallium nitride (GaN) MMIC PA operating from 3.6-7.4 GHz (69.1% fractional bandwidth) is designed using a 0.25-$\mu m$GaN HEMT process. The fabricated PA achieves a measured drain efficiency (DE) of 40-54% from 3.6-7.4 GHz, with a peak output power of 35.5 dBm. When driven by a 100-MHz 5G New Radio (NR) 64 quadrature amplitude modulation (64-QAM) signal with a peak-to-average power ratio (PAPR) of 7.0 dB, the PA achieves an average DE of 27% at 4.0 GHz, and 25% at 5.0 GHz, respectively.

The connectivity-aware path design is crucial in the effective deployment of autonomous unmanned aerial vehicles (UAVs). Recently, reinforcement learning (RL) algorithms have become the popular approach to solving this type of complex problem, but RL algorithms suffer slow convergence. In this article, we propose a transfer learning (TL) approach, where we use a teacher policy previously trained in an old domain to boost the path learning of the agent in the new domain. As the exploration processes and the training continue, the agent refines the path design in the new domain based on the subsequent interactions with the environment. We evaluate our approach considering an old domain at sub-6 GHz and a new domain at millimeter-wave (mmWave). The teacher path policy, previously trained at the sub-6 GHz path, is the solution to a connectivity-aware path problem that we formulate as a constrained Markov decision process (CMDP). We employ a Lyapunov-based model-free deep$Q$-network (DQN) to solve the path design at sub-6 GHz that guarantees connectivity constraint satisfaction. We empirically demonstrate the effectiveness of our approach for different urban environment scenarios. The results demonstrate that our proposed approach is capable of reducing the training time considerably at mmWave.

This article presents a wide-band suppression technique of flicker phase noise (PN) by means of a gate–drain phase shift in a transformer-based complementary oscillator. We identify that after naturally canceling its second-harmonic voltage by the complementary operation itself, third-harmonic current entering the capacitive path is now the main cause of asymmetry in the rising and falling edges, leading to the$1/f$noise upconversion. A complete$1/f^{3}$PN analysis for the transformer-based complementary oscillator is discussed. By tuning gate–drain capacitance ratio, a specific phase-shiftrangeis introduced at the gate and drain nodes of the cross-coupled pair to mitigate the detrimental effects of ill-behaved third-harmonic voltage, thus lowering the flicker PN. To further reduce the area and improve the PN in the thermal region, we introduce a new triple-8-shaped transformer. Fabricated in 22-nm FDSOI, the prototype occupies a compact area of 0.01mm2and achieves$1/f^{3}$PN corner of 70kHz, PN of −110dBc/Hz at 1MHz offset, figure-of-merit (FoM) of −182dB at 9GHz, and 39% tuning range (TR). It results in the best FoM with normalized TR and area (FoMTA) of −214dB at 1MHz offset.

This paper presents a simple yet effective$G_{m}$-boosting technique for improving gain and noise performance of millimeter-wave (mm-wave) low-noise amplifiers (LNAs) comprising triple-well transistors typically found in the modern bulk CMOS processes. The proposed technique uses a resistor that connects the p-well and deep n-well terminals of the triple-well transistor, leaving the terminals floating instead of conventionally connecting them to the ground and supply voltage. This arrangement exploits a leakage current through a diode formed between the drain/source and p-well of each transistor, thus autonomously setting its bulk potential for increased transconductance, while ensuring its robustness to the process variation. The improved isolation between the p-well and the substrate further improves the gain and noise performance. We provide a theoretical analysis of this floating resistor-based body biasing method and support it with simulation results. For experimental validation, a two-stage cascode LNA was designed and fabricated in 28-nm bulk CMOS. The measurement results show that 3.3–4dB noise figure (NF) and 19.1–16.1dB gain are achieved at 24.7–29.5GHz. To ensure a fair comparison, another identical LNA with the normally expected triple-well biasing was also fabricated. The proposed method reveals a 0.6dB improvement in minimum NF and an additional ~3.5dB gain without any significant linearity degradation.

In this article, we propose a broadband fully integrated power amplifier (PA) using a waveform shaping harmonic matching network. A comprehensive theory is developed for the proposed multi-resonance harmonic matching network to derive design criteria for achieving wide bandwidth, low insertion loss, and optimum load impedances in the second- and third-harmonic frequency bands. Furthermore, it is shown that this network can be realized using a lower total inductance compared to a standard bandpass network which is an important feature in reducing chip area and fabrication cost. A fully integrated PA prototype is implemented using a 250-nm GaN-on-SiC process with 28-V supply. The PA provides 33.9–36.1dBm output power (at 2–3dB gain compression), 42–51% drain efficiency (DE), 38–48% power-added efficiency (PAE), and 10–12.2dB power gain, across 4.0–6.0GHz. The output-power 1-dB bandwidth is 3.6–5.6GHz (44.5%). For a 64-QAM signal with 8dB peak-to-average power ratio (PAPR) at 5.0GHz, the PA can provide 30.2dBm average output power and 32% average PAE with RMS error vector magnitude (EVM) of −34.0/−32.4/−28.4dB (2.0/2.4/3.8%) for 50/100/200MHz modulation bandwidth, without using digital predistortion (DPD). The maximum average output power and average PAE, under the linearity constraint EVM <−28dB, are respectively 32.1/32.0/30.2dBm and 39/38/32%, for modulation bandwidth of 50/100/200 MHz.

The choice of the transmitting frequency to provide cellular-connected Unmanned Aerial Vehicle (UAV) reliable connectivity and mobility support introduce several challenges. Conventional sub-6 GHz networks are optimized for ground Users (UEs). Operating at the millimeter Wave (mmWave) band would provide high-capacity but highly intermittent links. To reach the destination while minimizing a weighted function of traveling time and number of radio failures, we propose in this paper a UAV joint trajectory and band switch approach. By leveraging Double Deep Q-Learning we develop two different approaches to learn a trajectory besides managing the band switch. A first blind approach switches the band along the trajectory anytime the UAV-UE throughput is below a predefined threshold. In addition, we propose a smart approach for simultaneous learning-based path planning of UAV and band switch. The two approaches are compared with an optimal band switch strategy in terms of radio failure and band switches for different thresholds. Results reveal that the smart approach is able in a high threshold regime to reduce the number of radio failures and band switches while reaching the desired destination.

This paper demonstrates a wideband 2.4 GHz$2\times 9$-bit Cartesian radio-frequency digital-to-analog converter (RFDAC). Active-under-coil integration is introduced in the physical implementation, where all key active circuitry is located underneath the matching-network transformer, achieving a core area of merely 0.35 mm2. An$8\times $analog linear interpolation at the RF rate is proposed to suppress replicas close to the carrier while avoiding any high-order and high-speed digital filters in digital processing back-end. The multi-port transformer is adopted in the matching network to improve the back-off efficiency. The measured peak output power and drain efficiency at the center frequency of 2.4 GHz are 17.47 dBm and 17.6% respectively, while the peak efficiency is 19.03%. Moreover, the 6-dB back-off efficiency is at 66% of that at the peak output power. The active-under-coil integration helps this RFDAC to achieve the smallest area among comparable prior arts.

Networked flying platforms can be used to provide cellular coverage and capacity. Given that 5G and beyond networks are expected to be always available and highly reliable, resilience and reliability of these networks must be investigated. This paper introduces the specific features of airborne networks that influence their resilience. We then discuss how machine learning and blockchain technologies can enhance the resilience of networked flying platforms.

In this paper, we investigate traits and trade-offs of a system combining Unmanned Aerial Vehicle (UAV)s with Base Station (BS) or Cloud Radio Access Networks (C-RAN) for extending the terrestrial wireless coverage over the sea in emergency situations. Results for an over the sea deployment link budget show the trade-off between power consumption and throughput to meet the Search and Rescue targets.

One of the major drawbacks of OFDM is high peak-to-average power ratio (PAPR) which can result in poor power efficiency and serious distortion in the transmitter amplifier. Tone reservation (TR) is a technique designed to combat this problem by reserving a number of carriers (tones) in the frequency domain to generate a cancellation signal in the time domain to remove high peaks. However TR can have a high associated computational cost due to the difficulties in finding an effective cancellation signal in the time domain by using only a few tones in the frequency domain. In this paper, we propose a novel approach to overcoming this problem by creating a Gaussian pulse as the cancellation signal from only a small number of reserved tones. This facilitates a simple and effective algorithm for reducing peak values while minimizing the occurrence of secondary peaks, the latter being a key factor in contributing to the high computational complexity of tone reservation algorithms.