Reducing Latency by Eliminating CSIT Feedback: FDD Downlink MIMO Transmission for Internet-of-Things Communications

TL;DR

This paper introduces a low-latency FDD MIMO transmission framework for IoT that eliminates the need for downlink CSIT feedback by reconstructing it from uplink signals, using robust precoding to handle imperfections.

Contribution

It proposes a novel approach to reduce latency in FDD MIMO IoT systems by reconstructing CSIT from uplink signals and designing a robust precoder with rate-splitting, avoiding explicit feedback.

Findings

Outperforms baseline methods in minimum spectral efficiency.

Significantly reduces communication latency.

Effectively handles imperfect CSIT with robust precoding.

Abstract

This paper presents a novel framework for low-latency frequency division duplex (FDD) multi-input multi-output (MIMO) transmission with Internet of Things (IoT) communications. Our key idea is eliminating feedback associated with downlink channel state information at the transmitter (CSIT) acquisition. Instead, we propose to reconstruct downlink CSIT from uplink reference signals by exploiting the frequency invariance property of channel parameters. Nonetheless, the frequency disparity between the uplink and downlink makes it impossible to get perfect downlink CSIT, resulting in substantial interference. To address this, we formulate a max-min fairness problem and propose a rate-splitting multiple access (RSMA)-aided efficient precoding method. In particular, to fully harness the potential benefits of RSMA, we propose a method that approximates the error covariance matrix and incorporates it into the precoder optimization process. This approach effectively accounts for the impact of imperfect CSIT, enabling the design of a robust precoder that efficiently handles CSIT inaccuracies. Simulation results demonstrate that our framework outperforms other baseline methods in terms of the minimum spectral efficiency when no direct CSI feedback is used. Moreover, we show that our framework significantly reduces communication latency compared to conventional CSI feedback-based methods, underscoring its effectiveness in enhancing latency performance for IoT communications.