Work

Extreme Value Theory-Based Robust Minimum-Power Precoding for URLLC

Year: 2024

Type: article

Abstract: Channel state information (CSI) is crucial for achieving ultra-reliable low-latency communication (URLLC) in wireless networks. The main associated problems are the CSI acquisition time, which impacts the latency requirements of time-critical applications, and the estimation accuracy, which degrades the signal-to-interference-plus-noise ratio, thus, reducing communication reliability. In this work, we formulate and solve a minimum-power precoding design problem simultaneously serving multiple URLLC users in the downlink with imperfect CSI. Specifically, we develop an algorithm that exploits state-of-the-art precoding schemes such as maximal ratio transmission and zero-forcing, and adjust the power of the precoders to compensate for the channel estimation error uncertainty based on the extreme value theory framework. Finally, we evaluate the performance of our method and show its superiority with respect to a worst-case robust precoding benchmark.

Source: IEEE Transactions on Wireless Communications

DOI: 10.1109/twc.2024.3396496

Authors: Dian Echevarría Pérez, Onel L. Alcaraz López, Hirley Alves

Institution: University of Oulu

Language: English

Topic: Advanced MIMO Systems Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,495