Second-generation beamforming refers to advanced designs using more sophisticated signal processing algorithms, larger antenna arrays, and the ability to generate higher quality, more focused beams that dynamically adapt to user movement and changing environments.
This article looks at how basic beamforming works and how second-generation beamforming contributes to improved network efficiency. It closes by considering the possibility of using metamaterials for holographic beamforming.
Beamforming uses multiple antennas to focus a wireless signal toward a specific user (Figure 1). It precisely controls the phase and amplitude of the transmitted signal from each antenna in the array to create a directional beam that enhances data reception for the target and minimizes interference with other users. It improves network efficiency and reduces energy consumption.

What’s new?
Second-generation beamforming is a well-established technology that continues to be refined and improved. Advanced channel estimation techniques have been developed to improve beam optimization and signal quality. In some advanced designs, the base station can use information from the user device regarding signal strength and channel conditions, allowing it to adjust the beam direction accordingly.
Machine learning algorithms are being used to implement adaptive beamformers that dynamically adjust to changing channel conditions and user locations, improving performance in complex environments. More energy-efficient algorithms are being deployed to improve the sustainability of 5G beamforming systems.
Hybrid beamforming combining analog and digital beamforming techniques is increasingly used in 5G networks. It can improve spectral efficiency and reduce power consumption in massive MIMO systems. It can also support sub-connected architectures that simplify the design of beamforming systems.
Sub connected improvements
Hybrid beamforming MIMO systems can be either fully connected or sub-connected. All RF chains are connected to all antenna elements in a fully connected system. While that can deliver high throughput, it’s also power-hungry.
In a sub-connected architecture, the array is divided into sub-arrays, and each RF chain is connected to a sub-array of antennas. A sub-connected architecture is simpler and more energy efficient but may have fewer degrees of freedom for beamforming.
The sub-arrays can have different geometries, like vertical, horizontal, and rectangular (Figure 2). In one case, a square type 64-element uniform rectangular array and 4 sub-connected RF chains have demonstrated 91.46% sum-rate performance of fully connected implementation with only 25% complexity when serving randomly positioned users. Beamforming sub-rate performance is a key metric and refers to the total data rate that can be achieved by combining the throughput to all users in a multiuser environment.

Holographic beamforming
An alternative to sub-connected architectures using traditional antennas is to replace the antennas with reconfigurable holographic surfaces (RHSs), possibly improving the throughput in MIMO systems further.
Holographic beamforming can potentially create highly directional beams with precise control over signal propagation. Using metamaterials and software-defined antennas, these systems enhance spectral efficiency, improve signal isolation, and support more flexible beam shaping.
The RHSs in an antenna array are composed of feeds, a waveguide, and sub-wavelength metamaterial radiation elements (Figure 3). The RHSs can be used to construct a holographic pattern on the surface of the metamaterial. Each metamaterial element can control the radiation amplitude to the generated beam patterns based on the holographic pattern.

Summary
Second-generation beamforming offers significantly improved spectral and power efficiency compared with initial designs. It’s an evolving technology that continues to be refined. In the future, using reconfigurable holographic surfaces using metamaterials may provide further performance enhancements.
References
Beamforming Antennas –How they work and are tested, Verkotan
Contextual beamforming: Exploiting location and AI for enhanced wireless telecommunication performance, APL Machine Learning
Holographic Beam Forming and MIMO, Pivotal Commware
Holographic Beamforming for Ultra Massive MIMO with Limited Radiation Amplitudes: How Many Quantized Bits Do We Need?, IEEE Communications Letters
Hybrid Beamforming in Massive MIMO for Next-Generation Communication Technology, MDPI sensors
Sub-Connected Hybrid Precoding Architectures in Massive MIMO Systems, IEEE Global Communications Conference (GLOBECOM) 2020
What is Beamforming?, JEM Engineering
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