Multi-Cell 6DMA: Cooperative Interference Management and Antenna Rotation Optimization

TL;DR

This paper proposes a distributed, scalable method for optimizing multi-cell 6DMA antenna rotations and precoders to improve downlink performance amid inter-cell interference, using a two-timescale approach.

Contribution

It introduces a novel distributed two-timescale design for joint antenna rotation and precoding optimization in multi-cell 6DMA networks, with limited inter-BS communication.

Findings

Distributed design achieves near-centralized performance.

Proposed method scales well with network size.

Effective interference management under practical constraints.

Abstract

In this paper, we investigate a multi-cell six-dimensional movable antenna (6DMA) network for enhancing downlink communication performance under inter-cell interference (ICI). Each base station (BS) is equipped with multiple 6DMA surfaces, and the 6DMA rotations affect both the desired-signal enhancement for in-cell users and the interference leakage toward neighboring cells, which makes the antenna-rotation design and transmit precoding intrinsically coupled across BSs. To address this issue, we formulate an average weighted sum-rate maximization problem for the multi-cell system by jointly optimizing the short-term downlink precoders and long-term 6DMA rotations under practical antenna geometric constraints. To tackle the resulting nonconvex problem, we propose a distributed two-timescale design based on inter-cell interference power constraint (IPC) coordination among neighboring BSs, under which each BS performs local short-term precoder optimization based on instantaneous channel state information (CSI) and long-term 6DMA rotation update according to statistical CSI with limited inter-BS information exchange. In particular, an edge-wise IPC coordination mechanism based on two-stage one-dimensional grid search and random maximal matching is developed to enable scalable distributed implementation. A centralized offline benchmark is also provided for performance comparison. Numerical results show that the proposed distributed design achieves performance close to the centralized benchmark under different interference conditions, while maintaining favorable scalability as the network size increases.