Energy and Spectral-Efficient Lens Antenna Subarray Design in MmWave MIMO Systems

Lens antenna subarray (LAS) is one of the recently introduced technologies for future wireless networks that significantly improves the energy efficiency of multiple-input multiple-output (MIMO) systems while achieving higher spectral efficiency compared to single-lens MIMO systems. However, a control mechanism for the LAS-MIMO design is considered a challenging task to efficiently manage the network resources and serve multiple users in the system. Therefore, in this paper, a sub-grouped LAS-MIMO architecture along with a hybrid precoding algorithm are proposed to reduce the cost and hardware overhead of traditional hybrid MIMO systems. Specifically, the LAS structure is divided into sub-groups to serve multiple users with different requirements, and an optimization problem based on the achievable sum-rate is formulated to maximize the spectral efficiency of the system. By splitting the sum-rate problem into sub-rate optimization problems, we develop a low-complexity hybrid precoding algorithm to effectively control the proposed architecture and maximize the achievable sum-rate of each subgroup. The proposed precoding algorithm selects the beam of each lens from a predefined set within a subgroup that maximizes the subgroup sum-rate, while the phase shifters and digital precoders in each subgroup are computed independently. The link between subgroups is updated based on successive interference cancelation to minimize interference between users of different subgroups. Our analysis and simulation results show that the proposed precoding algorithm of the sub-grouped LAS-MIMO architecture performs almost as well as traditional fully-connected hybrid MIMO systems in terms of spectral efficiency at low and high signal-to-noise ratio (SNR). It also outperforms traditional fully-connected and sub-connected hybrid MIMO systems in terms of energy efficiency, even when a large number of lenses are employed.

Automated summary

This paper proposes a sub-grouped LAS-MIMO architecture and a hybrid precoding algorithm to improve the energy efficiency and spectral efficiency of wireless networks. The LAS structure is divided into sub-groups to serve multiple users with different requirements, and an optimization problem is formulated to maximize the spectral efficiency. The proposed precoding algorithm effectively controls the architecture and achieves high efficiency in terms of both spectral efficiency and energy efficiency.