Limited Feedforward for Channel Estimation in Massive MIMO With Cascaded Precoding

Abstract

In this paper, we propose a novel channel estimation technique for frequency-division duplex (FDD)-based massive multiple-input multiple-output (MIMO) systems. Cascaded precoding has been adopted in FDD massive MIMO systems in order to reduce the dimension of physical channels so that the traditional channel estimation can be employed over a low-dimensional effective channel. However, due to the lack of a priori knowledge of the downlink channels, traditional channel estimation approaches can hardly achieve the minimum mean-square-error (MMSE) performance. To this end, we propose a limited feedforward strategy for downlink channel estimation based on the parametric model. In the parametric model, the channel frequency responses are represented by the path delays and the corresponding complex amplitudes. The path delays of uplink channels are first estimated and quantized at the base station, then fed forward to the user equipment (UE) through a dedicated feedforward link. In this way, the UE can obtain the a priori knowledge of the downlink channel under the assumption of the reciprocity between downlink and uplink path delays. Our analysis and simulation results show that the limited feedforward method can achieve near-MMSE performance.

Keywords

• Massive MIMO
• channel estimation
• parametric model
• limited feedforward
• cascaded precoding