Heterogeneous Resource Allocation for Ensuring End-to-End Quality of Service in Multi-hop Integrated Access and Backhaul Network
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866916674194636800 |
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| author | Zhang, Shuaifeng |
| author_facet | Zhang, Shuaifeng |
| contents | Faced with increasing network traffic demands, cell dense deployment is one of significant means to utilize spectrum resources efficiently to improve network capacity. Multi-hop integrated access and backhaul (IAB) architectures have emerged as a cost-effective solution for network densification. Meanwhile, dynamic time division duplex (D-TDD) is a promising solution to adapt to highly dynamic scenarios with asymmetric uplink and downlink traffic. Thus, dynamic resource allocation between backhaul and access links and high spectral efficiency under ensuring reliable transmission are two key objectives of IAB research. However, due to huge solution space, there are some challenges in multi-hop IAB with D-TDD if only an integrated optimization problem (IOP) is considered. To handle these challenges, we decompose the IOP into sub-problems to reduce the solution space. To tackle these sub-problems, we formulate them separately as the non-cooperative games and design the corresponding utility functions to guarantee the existence of Nash equilibrium solutions. Also, to achieve the system-wide solution, we propose a single-leader heterogeneous multi-follower Stackelberg-game-based resource allocation scheme, which can combine the solving results of all the sub-problems to get the IOP approximate solution. Simulation results show that the proposed scheme can improve throughput performance while meeting spectrum energy efficiency constraints. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_03576 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Heterogeneous Resource Allocation for Ensuring End-to-End Quality of Service in Multi-hop Integrated Access and Backhaul Network Zhang, Shuaifeng Neural and Evolutionary Computing Faced with increasing network traffic demands, cell dense deployment is one of significant means to utilize spectrum resources efficiently to improve network capacity. Multi-hop integrated access and backhaul (IAB) architectures have emerged as a cost-effective solution for network densification. Meanwhile, dynamic time division duplex (D-TDD) is a promising solution to adapt to highly dynamic scenarios with asymmetric uplink and downlink traffic. Thus, dynamic resource allocation between backhaul and access links and high spectral efficiency under ensuring reliable transmission are two key objectives of IAB research. However, due to huge solution space, there are some challenges in multi-hop IAB with D-TDD if only an integrated optimization problem (IOP) is considered. To handle these challenges, we decompose the IOP into sub-problems to reduce the solution space. To tackle these sub-problems, we formulate them separately as the non-cooperative games and design the corresponding utility functions to guarantee the existence of Nash equilibrium solutions. Also, to achieve the system-wide solution, we propose a single-leader heterogeneous multi-follower Stackelberg-game-based resource allocation scheme, which can combine the solving results of all the sub-problems to get the IOP approximate solution. Simulation results show that the proposed scheme can improve throughput performance while meeting spectrum energy efficiency constraints. |
| title | Heterogeneous Resource Allocation for Ensuring End-to-End Quality of Service in Multi-hop Integrated Access and Backhaul Network |
| topic | Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2504.03576 |