Diverse and Differentiated QoS Provisioning for 6G Communications via Demand-Aware Prioritization and DEI-Based Resource Allocation

To address the challenges of device diversity and service heterogeneity in human and machine-type communications, a predominant approach in future networks is to serve users by differentiated quality-of-service (QoS) categories. However, due to exacerbated conflicts among concurrent services for con...

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Bibliographic Details
Published in:IEEE transactions on wireless communications Vol. 23; no. 12; pp. 18346 - 18362
Main Authors: Han, Wudan, Wang, Xianbin
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
6G mobile communication
Algorithms
Array signal processing
Categories
Demand
Design optimization
diversity
Diversity equity & inclusion
equity
Heterogeneity
inclusion
mean-variance optimization
Measurement
multi-dimensional multiple access
Multiplexing
NOMA
Optimization
Provisioning
QoS provisioning
Quadratic programming
Quality of service
Quality of service architectures
Resource allocation
Resource management
Vectors
Wireless communication
ISSN:1536-1276, 1558-2248
Online Access:Get full text
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Summary:To address the challenges of device diversity and service heterogeneity in human and machine-type communications, a predominant approach in future networks is to serve users by differentiated quality-of-service (QoS) categories. However, due to exacerbated conflicts among concurrent services for constrained resources, 6G networks call for more inclusive and equitable QoS provisioning strategies. This paper proposes a novel service provisioning framework empowered by demand-aware prioritization mechanism and diversity, equity, inclusion (DEI)-based resource allocation. Particularly, the proposed scheme discerns heterogeneous users' resource needs by customized utility models according to specific service categories and requirements. By considering demand-aware priorities for individual users, we propose a DEI-based metric evaluated by the weighted mean-variance tradeoff of network-wide user utilities. Our overall objective is to maximize the long-term DEI value in multi-dimensional multiple-access (MDMA) network. To address this NP-hard problem, we design an alternate optimization framework wherein the subchannel and power allocation are solved by matching theory and sequential quadratic programming (SQP) algorithm. Simulations verify the proposed scheme can inclusively support all users of differentiated service categories with higher average utility and smaller inter-user disparity. Furthermore, the DEI method can adaptively accommodate and prioritize diverse QoS demands based on individualized service requirements and dynamic resource conditions.
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ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2024.3465440