Fully-Decoupled RAN for Feedback-Free Multi-Base Station Transmission in MIMO-OFDM System

Yunting Xu, Zongxi Liu, Bo Qian, Hongyang Du, Jiacheng Chen, Jiawen Kang, Haibo Zhou, Dusit Niyato

Abstract: Coordinated multi-base station (BS) transmission has emerged as a fundamental access technology to augment network capability and improve spectrum efficiency. However, the computation-intensive feedback of channel state information (CSI) poses significant challenges in determining physical-layer parameters for coordinated BSs. In this paper, we investigate a feedback-free mechanism that leverages fixed precoding matrix indicator (PMI), rank indicator (RI), and channel quality indicator (CQI) for coordinated BS transmission over a fully-decoupled radio access network (FD-RAN). Aiming to maximize user equipment (UE) throughput without CSI feedback, we calculate an optimal feedback-free parameter across spatial, frequency, and time domains only through UE geolocations. First, to determine MIMO transmission layer and precoding strategy in the spatial domain, we introduce a hierarchical reinforcement learning (HRL) framework to jointly select PMI and RI for coordinated BSs. Subsequently, for designing a more fine-grained subband transmission, transformer module is employed to capture the subcarrier correlations within OFDM symbols. Finally, given the unpredictable channel variations, we leverage a diffusion model to generate representative channel for fixed PMI, RI, and CQI over time-varied networks. Simulations demonstrate that 2 BSs feedback-free transmission can enhance 13% throughput compared with 1 BS CLSM transmission, which provides a design principle for next-generation transceiver technologies.