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A novel architecture of reconfigurable, flat metalens is proposed with an electrically tunable focal length for applications in wireless communication systems working at the frequencies of millimeter waves (i.e., 60 GHz). In this approach, a reflective metalens made of silicon bricks is distributed on a grounded multilayer hosting films of a phase-transition material, namely, vanadium dioxide. The multilayer, acting as a ground plane with a controllable position, provides different phase profiles in the same metalens and, therefore, different focal lengths. Our numerical investigation of thermal and electromagnetic effects shows that the metasurface can reversibly tune the focal length at 27, 31, and 33 mm. In addition, in the operating frequency range between 58 and 62 GHz, the tunability of the metalens remains unaltered. Dynamically controlling the focal point of millimeter waves is highly desirable in wireless communications, especially for 5G and 6G cellular systems applications.

Reconfigurable Matching Networks (RMN) have found a wide range of applications, such as antenna impedance matching (Antenna Tuning Units -ATU-), the design of reconfigurable power amplifiers, applications in Magnetic Resonance Imaging (MRI), adjustable low noise amplifier design, etc. In this paper, we propose the experimental design and verification of a reconfigurable impedance synthesis network that can simultaneously work in three different bands and is completely independent so that the impedance variations in a frequency band are approximately transparent to the rest. The variable elements used in this paper are varactors. To verify its operation, it is applied to a process of matching a laser modulator in three different frequency bands for C-RAN (Cloud Radio Access Networks) applications. Experimental results demonstrate, as expected, that losses may depend on the state in which they are driven. Consequently, a state that can guarantee a good match could also imply greater losses, leading to a certain trade-off. The application of genetic algorithms in this context points out that it may be convenient to optimize the insertion losses of the complete chain instead of the return losses.