Frequency and time domain packet scheduling based on channel prediction with imperfect CQI in LTE

TL;DR

This paper proposes a novel packet scheduling algorithm for LTE that uses a Kalman filter-based channel predictor and a combined PF and M-LWDF approach to improve throughput and reduce packet loss under imperfect CQI conditions.

Contribution

It introduces a frequency domain Kalman filter predictor and a joint time domain scheduling method to enhance LTE performance with imperfect channel feedback.

Findings

Improved system throughput in simulations.

Reduced packet loss ratio.

Effective handling of imperfect CQI feedback.

Abstract

Channel-dependent scheduling of transmission of data packets in a wireless system is based on measurement and feedback of the channel quality. To alleviate the performance degradation due to simultaneous multiple imperfect channel quality information (CQI), a simple and efficient packet scheduling (PS) algorithm is developed in downlink LTE system for real time traffic. A frequency domain channel predictor based on Kalman filter is first developed to restore the true CQI from erroneous channel quality feedback. Then, a time domain grouping technique employing the joint of Proportional Fair (PF) and Modified Largest Weighted Delay First (M-LWDF) algorithms is used. It was proved this proposal achieves better performance in terms of system throughput and packet loss ratio by simulation results.