Power Minimization of Downlink Spectrum Slicing for eMBB and URLLC Users

被引:16
|
作者
Saggese, Fabio [1 ]
Moretti, Marco [2 ]
Popovski, Petar [1 ]
机构
[1] Aalborg Univ, Dept Elect Syst, DK-9220 Aalborg, Denmark
[2] Univ Pisa, Dept Informat Engn, I-56126 Pisa, Italy
关键词
NOMA; Receivers; Multiplexing; RAN slicing; eMBB; URLLC; power saving; RESOURCE-MANAGEMENT; OUTAGE PROBABILITY; 5G; NOMA;
D O I
10.1109/TWC.2022.3189396
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
5G technology allows heterogeneous services to share the wireless spectrum within the same radio access network. In this context, spectrum slicing of the shared radio resources is a critical task to guarantee the performance of each service. We analyze a downlink communication serving two types of traffic: enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC). Due to the nature of low-latency traffic, the base station knows the channel state information (CSI) of the eMBB users while having statistical CSI for the URLLC users. We study the power minimization problem employing orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) schemes. Based on this analysis, we propose a lookup table-based approach and a block coordinated descent (BCD) algorithm. We show that the BCD is optimal for the URLLC power allocation. The numerical results show that NOMA leads to lower power consumption than OMA, except when the average channel gain of the URLLC user is very high. For the latter case, the optimal approach depends on the channel condition of the eMBB user. Even when OMA attains the best performance, the gap with NOMA is negligible, showing the capability of NOMA to reduce power consumption in practically every condition.
引用
收藏
页码:11051 / 11065
页数:15
相关论文
共 50 条
  • [21] A Downlink Puncturing Scheme for Simultaneous Transmission of URLLC and eMBB Traffic by Exploiting Data Similarity
    Almekhlafi, Mohammed
    Chraiti, Mohaned
    Arfaoui, Mohamed Amine
    Assi, Chadi
    Ghrayeb, Ali
    Alloum, Amira
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (12) : 13087 - 13100
  • [22] eMBB-URLLC Multiplexing: A Preference-Based Method of Ensuring eMBB Reliability and Improving Users' Satisfaction
    Li, Mengge
    Du, Jiarong
    Wang, Liang
    2021 IEEE INTERNATIONAL WORKSHOP TECHNICAL COMMITTEE ON COMMUNICATIONS QUALITY AND RELIABILITY (CQR 2021), 2021,
  • [23] URLLC-eMBB Slicing to Support VR Multimodal Perceptions over Wireless Cellular Systems
    Park, Jihong
    Bennis, Mehdi
    2018 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2018,
  • [24] URLLC-eMBB hierarchical network slicing for Internet of Vehicles: An AoI-sensitive approach
    Cui, Yaping
    Yang, Xisheng
    He, Peng
    Wang, Ruyan
    Wu, Dapeng
    VEHICULAR COMMUNICATIONS, 2023, 43
  • [25] eMBB-URLLC Resource Slicing:A contract-based pre-scheduling mechanism
    Qiu, Ziqiang
    Zhao, Chenggui
    2024 5TH INTERNATIONAL CONFERENCE ON COMPUTING, NETWORKS AND INTERNET OF THINGS, CNIOT 2024, 2024, : 359 - 363
  • [26] Joint Power and User Allocation in Coexistence of eMBB and URLLC Services
    Rahim, Muddasir
    Nguyen, Thanh Luan
    Do, Tri Nhu
    Kaddoum, Georges
    IEEE COMMUNICATIONS LETTERS, 2024, 28 (09) : 2186 - 2190
  • [27] Energy-Efficient Optimization in Distributed Massive MIMO Systems for Slicing eMBB and URLLC Services
    Liu, Bo
    Zhu, Pengcheng
    Li, Jiamin
    Wang, Dongming
    You, Xiaohu
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (08) : 10473 - 10487
  • [28] Network Slicing for eMBB, URLLC, and mMTC: An Uplink Rate-Splitting Multiple Access Approach
    Liu, Yuanwen
    Clerckx, Bruno
    Popovski, Petar
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (03) : 2140 - 2152
  • [29] Deep Reinforcement Learning Based Dynamic Resource Slicing for eMBB and URLLC Traffic Considering Puncturing
    Zhang Wenqi
    Pan Zhiwen
    Liu Nan
    You Xiaohu
    2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING, 2024,
  • [30] Rate-Splitting Multiple Access for URLLC Uplink in Physical Layer Network Slicing With eMBB
    Santos, Elco Joao Dos, Jr.
    Souza, Richard Demo
    Rebelatto, Joao Luiz
    IEEE ACCESS, 2021, 9 : 163178 - 163187