TY - JOUR
T1 - 面向异构网络的可重构智能表面辅助资源优化方法
AU - Shen, Xianhao
AU - Zeng, Ziling
AU - Niu, Shaohua
N1 - Publisher Copyright:
© 2022 Editorial Board of Journal on Communications. All rights reserved.
PY - 2022/11/25
Y1 - 2022/11/25
N2 - For reconfigurable intelligent surface (RIS)-assisted heterogeneous network slicing, a resource optimization method with joint resource allocation and phase shift optimization was proposed. A joint optimization problem with different objectives was constructed for different services in heterogeneous networks. For enhanced mobile broadband (eMBB) services, the resource block allocation, power allocation and RIS phase shift matrix were jointly optimized based on the alternating optimization algorithm to maximize the total traversal capacity of eMBB users. For ultra-reliable low-latency communication (URLLC) services, a pre-configured RIS-based heuristic URLLC allocation algorithm was proposed with the objectives of maximizing the URLLC packet reception rate and minimizing the amount of eMBB rate loss. Simulation results demonstrate that the proposed algorithm achieves about 99.99% URLLC packet reception rate using only 80 RISs compared to 95.95% URLLC packet reception rate when no RISs are deployed, while the total eMBB rate is increased by 86.24%.
AB - For reconfigurable intelligent surface (RIS)-assisted heterogeneous network slicing, a resource optimization method with joint resource allocation and phase shift optimization was proposed. A joint optimization problem with different objectives was constructed for different services in heterogeneous networks. For enhanced mobile broadband (eMBB) services, the resource block allocation, power allocation and RIS phase shift matrix were jointly optimized based on the alternating optimization algorithm to maximize the total traversal capacity of eMBB users. For ultra-reliable low-latency communication (URLLC) services, a pre-configured RIS-based heuristic URLLC allocation algorithm was proposed with the objectives of maximizing the URLLC packet reception rate and minimizing the amount of eMBB rate loss. Simulation results demonstrate that the proposed algorithm achieves about 99.99% URLLC packet reception rate using only 80 RISs compared to 95.95% URLLC packet reception rate when no RISs are deployed, while the total eMBB rate is increased by 86.24%.
KW - URLLC
KW - eMBB
KW - heterogeneous network
KW - reconfigurable intelligent surface
KW - resource optimization
UR - http://www.scopus.com/inward/record.url?scp=85147251167&partnerID=8YFLogxK
U2 - 10.11959/j.issn.1000-436x.2022217
DO - 10.11959/j.issn.1000-436x.2022217
M3 - 文章
AN - SCOPUS:85147251167
SN - 1000-436X
VL - 43
SP - 171
EP - 182
JO - Tongxin Xuebao/Journal on Communications
JF - Tongxin Xuebao/Journal on Communications
IS - 11
ER -