Design of a Criteria-Based User Scheduling and Precoding Resource Allocation Scheme

A joint design for user scheduling and precoding based on channel state information (CSI) is proposed to tackle limited base station (BS) access in dense user scenarios. Four user scheduling criteria, including exhaustive search, channel gain, orthogonality, and collinearity, are used to optimize user selection. Based on scheduling results, zero-forcing (ZF) and minimum mean square error (MMSE) precoding are applied to reduce interference, and power allocation is optimized with the water-filling method to improve performance. Simulations validate the scheme, showing improved system capacity and service quality under different signal-to-noise ratio (SNR) levels, especially at low and high SNR. Results show MMSE consistently outperforms ZF in system capacity across all scheduling criteria. The method also efficiently allocates power, further boosting system rate and service quality in various user and antenna setups.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/ccpqt64497.2024.00035
Primary Topic
Advanced Wireless Network Optimization
Type
article
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article

Design of a Criteria-Based User Scheduling and Precoding Resource Allocation Scheme

Hongyuan Gao, Al-Azzawi Essa Mohammed, Richard Han, Shiqi Chen
Advanced Wireless Network Optimization
article

Design of a Criteria-Based User Scheduling and Precoding Resource Allocation Scheme

Hongyuan Gao, Al-Azzawi Essa Mohammed, Richard Han, Shiqi Chen
article en

Abstract

A joint design for user scheduling and precoding based on channel state information (CSI) is proposed to tackle limited base station (BS) access in dense user scenarios. Four user scheduling criteria, including exhaustive search, channel gain, orthogonality, and collinearity, are used to optimize user selection. Based on scheduling results, zero-forcing (ZF) and minimum mean square error (MMSE) precoding are applied to reduce interference, and power allocation is optimized with the water-filling method to improve performance. Simulations validate the scheme, showing improved system capacity and service quality under different signal-to-noise ratio (SNR) levels, especially at low and high SNR. Results show MMSE consistently outperforms ZF in system capacity across all scheduling criteria. The method also efficiently allocates power, further boosting system rate and service quality in various user and antenna setups.

Harbin Engineering University (CN)
Openalex Percentile: Top 74%
Advanced Wireless Network Optimization
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