This article reviews the application and technology advancement of gallium (Ga)-based liquid metal (LM) in high-frequency circuits and antennas. It discusses the material properties of common LMs, the fluidic channels used to contain LM and their manufacturing techniques, and the actuation techniques, which are all critical for the design and implementation of LM-based devices. LM’s fluidic and pliable nature, together with its excellent electrical, thermal, and rheological (i.e., fluid flow) properties, provides some unique and innovative solutions to flexible/wearable electronics, reconfigurable circuits, and antennas. This article provides a comprehensive review of a wide range of LM-enabled high-frequency circuits and antennas, including interconnects and transitions, reconfigurable passive circuits (such as resonators, filters, and couplers), switches, phase shifters, reconfigurable antennas, flexible and wearable antennas, and metamaterials (i.e., periodic materials with properties not found in nature). This article presents various design concepts and implementation techniques, highlights key capabilities, and discusses the challenges and opportunities with the use of Ga-based LM materials.

This paper proposes a joint iterative optimization based hybrid beamforming technique for massive MU-MIMO systems. The proposed technique jointly and iteratively optimizes the transmitter precoders and combiners, aiming to approach the global optimum solution for the system sum-rate maximization problem. The proposed technique develops an adaptive algorithm exploiting the stochastic gradients (SG) of the local beamformers and provides low-complexity closed-form solutions. Furthermore, an efficient adaptive scheme is developed based on the proposed adaptive algorithm and the closed-form solutions. The proposed algorithm requires the signal-to-interference-plus-noise ratio (SINR) feedback from each user and a limited size transition vector to be exchanged between the transmitter and receivers at each step to update beamformers locally. Analytic result shows that the proposed adaptive algorithm achieves low-complexity when the array size is large and is able to converge within a small number of iterations. Simulation result shows that the proposed technique is able to achieve superior performance comparing to the existing state-of-art techniques. In addition, the knowledge of instantaneous channel state information (CSI) is not required as the channels are also adaptively estimated with each coherence time which is a practical assumption since the CSI is usually unavailable or have time-varying nature in real-time applications.

This paper investigates the impact of intelligent reflecting surface (IRS) enabled wireless secure transmission. Specifically, an IRS is deployed to assist multiple-input multiple-output (MIMO) secure system to enhance the secrecy performance, and artificial noise (AN) is employed to introduce interference to degrade the reception of the eavesdropper. To improve the secrecy performance, we aim to maximize the achievable secrecy rate, subject to the transmit power constraint, by jointly designing the precoding of the secure transmission, the AN jamming, and the reflecting phase shift of the IRS. We first propose an alternative optimization algorithm (i.e., block coordinate descent (BCD) algorithm) to tackle the non-convexity of the formulated problem. This is made by deriving the transmit precoding and AN matrices via the Lagrange dual method and the phase shifts by the Majorization-Minimization (MM) algorithm. Our analysis reveals that the proposed BCD algorithm converges in a monotonically non-decreasing manner which leads to guaranteed optimal solution. Finally, we provide numerical results to validate the secrecy performance enhancement of the proposed scheme in comparison to the benchmark schemes.