Name
Title | ||
|---|---|---|
Learning-Based Cooperative Multiplexing Mode Selection and Resource Allocation for eMBB and uRLLC |
Abstract | ||
|---|---|---|
With the commercial application of 5th generation, the coexistence scenario of enhanced Mobile Broadband (eMBB) and ultra-Reliable and Low Latency Communication (uRLLC) is facing significant challenges in utilizing limited resources. The existing scheme of only using puncturing or superposition cannot meet the heterogeneous requirement of eMBB and uRLLC. In this paper, we propose a cooperative multiplexing mode dynamic selection and resource allocation scheme to achieve the trade-off between the transmission quality (the transmission rate and the transmission accuracy ratio) of eMBB and the reliability of uRLLC, which considers power limitation. In the scheme, the multiplexing mode includes puncturing mode and Non-Orthogonal Multiple Access (NOMA) mode. After the multiplexing mode is selected, the resource block and power allocation are carried out. Furthermore, we propose a Co-Dueling Deep Q-learning Network to obtain the expected long-term benefits of the formulated scheme. Simulation results show that the proposed algorithm reduces the computation time by 27.3% and outperforms the compared scheme. Moreover, the proposed scheme improves the overall transmission quality of the coexistence scenario, where both eMBB and uRLLC services do not occupy the resources selfishly. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/WCNC51071.2022.9771973 | 2022 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC) |
Keywords | DocType | ISSN |
uRLLC, eMBB, Multiplexing Mode, Resource Allocation, Reinforcement learning | Conference | 1525-3511 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoyu Chi | 1 | 0 | 0.34 |
| Xiaodong Xu | 2 | 336 | 48.97 |
| Shujun Han | 3 | 0 | 1.01 |
| Jingxuan Zhang | 4 | 0 | 0.34 |