Joint Beamforming Coordination and User Selection for CoMP-Enabled NR-U Networks

The sixth-generation (6G) era is expected to provide even higher levels of massive connectivity/Internet of Things (IoT), tremendous data rate, and low latency than the 5G communication. Therefore, the future 6G wireless networks would confront with much more severe spectrum scarcity problems, which make the new radio in unlicensed spectrum (NR-U) technology attractive. Meanwhile, the high densely deployed massive IoT devices lead to fearful intercell and intracell interference issues. To address these challenges, a coordinated multipoint (CoMP) technology can be adopted. In this work, we introduce a CoMP-based NR-U network, particularly for 6G-enabled massive IoT scenarios. Under the proposed network, we introduce a spatial listen-before-talk (LBT) scheme to control mobile network operators (MNOs) to coexist with the incumbent WiFi devices orthogonally, which can significantly improve the spectrum efficiency. To suppress the strong co-channel interference among multiple MNOs, we investigate a joint beamforming coordination and user selection problem, which is NP-hard. To deal with this problem, we first adopt a fractional programming and an integer replacement method to transform the objective problem into a tractable one. Then, we introduce a semidistributed alternating direction method of multipliers and block coordinate update (ADMM-BCU) algorithm to find a suboptimal solution, which only requires limited information exchange via a CoMP server and can help reduce energy consumption. Theoretical analysis and numerical results demonstrate the effectiveness of the proposed algorithm for large-scale 6G IoT scenarios.

Automated summary

The sixth-generation (6G) wireless networks are expected to provide even higher levels of connectivity, data rate, and latency than 5G. However, they will also face challenges such as spectrum scarcity and interference. This paper introduces a CoMP-based NR-U network to address these challenges and proposes spatial LBT scheme and ADMM-BCU algorithm to improve spectrum efficiency and reduce energy consumption.