Smart, Fast, and Low Memory Beam-Steering Antenna Configurations for 5G and Future Wireless Systems

Smart Antennas are important to provide mobility support for many enhanced 5G and future wireless applications and services, such as energy harvesting, virtual reality, Voice over 5G (Vo5G), connected vehicles, Machine-to-Machine Communication (M2M), and Internet of Things (IoT). Smart antenna technology enables us to reduce interference and multipath problems and increase the quality in communication signals. This paper presents a number of nonlinear configurations of dipole arrays for forming a single beam in any desired direction. We propose three, four, six, and eight-element array structures to perform this single beam-steering functionality. The proposed array configurations with multiple axes of symmetry (in the azimuthal plane) decrease the computational repetitions in optimizing respective weight factors for beam-steering. The optimized weight factors are obtained through the Least Mean Square (LMS) method. MATLAB (TM) is used to calculate optimized weight factors as well as to determine the resulting radiation patterns. Since antennas are bidirectional elements, beamforming in one direction means that the antenna will also have high receiving gain in that direction. Performances of differently configured models are compared in terms of their directivity, sidelobe reduction, and computational complexities for beam-steering.

Automated summary

Smart Antennas are crucial for providing mobility support in enhanced wireless applications like 5G and future technologies. They help decrease interference and multipath problems, enhancing signal quality. This paper presents different nonlinear configurations for forming a single beam in any desired direction. The proposed array structures with multiple axes of symmetry reduce computational repetitions and optimize beam-steering functionality. The performance of different array configurations is compared based on directivity, sidelobe reduction, and computational complexities.