Robust Precoding Weights for Downlink D-MIMO in 6G Communications

Point-to-point MIMO and massive MIMO techniques have played significant roles in the success of 4G and 5G radio networks, and in 6G we believe that distributed MIMO will play a similar critical role. The performance of downlink phase coherent distributed MIMO transmission relies on tight phase alignment between the serving access points (APs) in the system. In realistic scenarios, there will always be some level of phase misalignment between APs due to e.g., differences in the local clocks of the APs, which can severely degrade the performance. One main contribution of this paper is that we propose the use of a Linear Quadratic Regulator (LQR) based solution for
calculating downlink precoding weights in D-MIMO systems. The optimal LQR based precoding solution is numerically stable and computationally efficient, and it can easily utilise parallel computing in distributed or centralised hardware processors. Furthermore, we also show how the LQR based solution can be modified to include differently sized subsets of serving APs for each UE, which enables a scalable tradeoff between performance and complexity.
Another main contribution of the paper is that we identify a new phase misalignment problem in D-MIMO. The proposed LQR-based precoding method is the first solution that takes not only the channel estimation phase errors, but also the relative phase errors between serving APs into account when designing the downlink D-MIMO transmission precoder. By this, some of the performance lost due to different causes of phase misalignment can be regained. In the scenarios studied in this paper we observe 20-70% performance increase of the proposed method compared to a reference case where residual phase errors are ignored when determining the downlink precoding weights.