View in EDS

Intelligent Wireless Spectrum Sharing Framework for LAA‐LTE/WiFi Coexistence Systems.

Saved in:
Bibliographic Details
Title: Intelligent Wireless Spectrum Sharing Framework for LAA‐LTE/WiFi Coexistence Systems.
Authors: Kim, Sungwook1 (AUTHOR) swkim01@sogang.ac.kr
Source: International Journal of Communication Systems. 3/10/2026, Vol. 39 Issue 4, p1-14. 14p.
Subjects: Dynamic spectrum access, Wireless communications, Negotiation, Mathematical programming, Reinforcement learning
Abstract: Utilizing licensed assisted access (LAA) for cellular long‐term evolution (LTE) presents a viable solution to address the growing issue of limited wireless spectrum. Nevertheless, realizing the advantages of LTE‐LAA requires a fair coexistence framework to ensure harmonious operation alongside existing WiFi networks. This study explores how collaborative and coexistent strategies between WiFi and cellular technologies in unlicensed bands can enhance the capacity of heterogeneous wireless networks. To this end, we focus on optimizing spectrum allocation to boost the performance of systems where LAA‐LTE and WiFi networks operate together. By using the carrier aggregation technology, the unlicensed bands can be appropriately distributed to individual mobile devices. Our approach integrates a distributional reinforcement learning algorithm and three distinct one‐to‐many bargaining solutions, enabling adaptive responses to various wireless environments. Based on the learning and bargaining methodologies, cellular and WiFi access points act cooperatively with each other to enhance conflicting performance criteria. The core innovation of our method lies in leveraging hybrid optimization strategies to their fullest potential while simultaneously achieving mutual agreement among different network entities through collaborative mechanisms. The simulation results confirm the efficiency of the proposed hybrid control strategy and validate its overall effectiveness. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Communication Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Description
Abstract:Utilizing licensed assisted access (LAA) for cellular long‐term evolution (LTE) presents a viable solution to address the growing issue of limited wireless spectrum. Nevertheless, realizing the advantages of LTE‐LAA requires a fair coexistence framework to ensure harmonious operation alongside existing WiFi networks. This study explores how collaborative and coexistent strategies between WiFi and cellular technologies in unlicensed bands can enhance the capacity of heterogeneous wireless networks. To this end, we focus on optimizing spectrum allocation to boost the performance of systems where LAA‐LTE and WiFi networks operate together. By using the carrier aggregation technology, the unlicensed bands can be appropriately distributed to individual mobile devices. Our approach integrates a distributional reinforcement learning algorithm and three distinct one‐to‐many bargaining solutions, enabling adaptive responses to various wireless environments. Based on the learning and bargaining methodologies, cellular and WiFi access points act cooperatively with each other to enhance conflicting performance criteria. The core innovation of our method lies in leveraging hybrid optimization strategies to their fullest potential while simultaneously achieving mutual agreement among different network entities through collaborative mechanisms. The simulation results confirm the efficiency of the proposed hybrid control strategy and validate its overall effectiveness. [ABSTRACT FROM AUTHOR]
ISSN:10745351
DOI:10.1002/dac.70407