Low Complexity Hybrid Precoding Designs for Multiuser mmWave/THz Ultra Massive MIMO Systems

TL;DR

This paper introduces a hybrid precoding algorithm for multiuser mmWave and THz MIMO systems that balances spectral efficiency and implementation simplicity across various hardware architectures.

Contribution

The proposed hybrid design algorithm is adaptable to multiple architectures and structures, enabling low-complexity, energy-efficient ultra-massive MIMO systems at high frequencies.

Findings

Achieves good spectral efficiency with low complexity

Supports various hardware architectures and array structures

Effective for systems with many users and data streams

Abstract

Millimeter-wave and terahertz technologies have been attracting attention from the wireless research community since they can offer large underutilized bandwidths which can enable the support of ultra-high-speed connections in future wireless communication systems. While the high signal attenuation occurring at these frequencies requires the adoption of very large (or the so-called ultra-massive) antenna arrays, in order to accomplish low complexity and low power consumption, hybrid analog/digital designs must be adopted. In this paper we present a hybrid design algorithm suitable for both mmWave and THz multiuser multiple-input multiple-output (MIMO) systems, which comprises separate computation steps for the digital precoder, analog precoder and multiuser interference mitigation. The design can also incorporate different analog architectures such as phase shifters, switches and inverters, antenna selection and so on. Furthermore, it is also applicable for different structures namely, fully connected, arrays of subarrays (AoSA) and dynamic arrays of subarrays (DAoSA), making it suitable for the support of ultra-massive MIMO (UM-MIMO) in severely hardware constrained THz systems. We will show that, by using the proposed approach, it is possible to achieve good trade-offs between spectral efficiency and simplified implementation, even as the number of users and data streams increases.)