Efficient PHY Layer Abstraction under Imperfect Channel Estimation

TL;DR

This paper enhances PHY layer abstraction techniques by accounting for channel estimation errors, demonstrating that effective SINR remains unaffected in certain configurations, validated through simulations across various OFDM scenarios.

Contribution

It introduces two methods to implement EESM-log-SGN PHY abstraction under imperfect channel estimation, improving reliability in practical systems.

Findings

Effective SINR is unaffected by channel estimation errors in MISO/SISO configurations.

The proposed methods are validated through full PHY simulations.

The methods perform well across different OFDM scenarios.

Abstract

As most existing work investigate the PHY layer abstraction under an assumption of perfect channel estimation, it may become unreliable if there exists channel estimation error in a real communication system. This letter improves an efficient PHY layer method, EESM-log-SGN PHY layer abstraction, by considering the presence of channel estimation error. We develop two methods for implementing the EESM-log-SGN PHY abstraction under imperfect channel estimation. We show that the effective SINR is not impacted by the channel estimation error under multiple-input and single-output (MISO)/single-input and single-output (SISO) configuration, which is also verified by the full PHY simulation. The developed methods are then validated under different orthogonal frequency division multiplexing (OFDM) scenarios.