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Network Slicing for URLLC and eMBB with Max-Matching Diversity Channel Allocation
IEEE Communications Letters ( IF 4.1 ) Pub Date : 2020-03-01 , DOI: 10.1109/lcomm.2019.2959335
Elco Joao dos Santos , Richard Demo Souza , Joao Luiz Rebelatto , Hirley Alves

This work considers the problem of radio resource sharing between enhanced mobile broadband (eMBB) and ultra-reliable and low latency communications (URLLC), two heterogeneous 5G services. More specifically, we propose the use of a max-matching diversity (MMD) algorithm to properly allocate the channels to the eMBB users, considering both heterogeneous orthogonal multiple access (H-OMA) and heterogeneous non-orthogonal multiple access (H-NOMA) network slicing strategies. Our results indicate that MMD can simultaneously improve the eMBB achievable rate and the URLLC reliability regardless the network slicing strategy adopted.

中文翻译:

具有最大匹配分集信道分配的 URLLC 和 eMBB 网络切片

这项工作考虑了增强型移动宽带 (eMBB) 和超可靠低延迟通信 (URLLC) 这两种异构 5G 服务之间的无线电资源共享问题。更具体地说,我们建议使用最大匹配分集 (MMD) 算法将信道正确分配给 eMBB 用户,同时考虑异构正交多址 (H-OMA) 和异构非正交多址 (H-NOMA)网络切片策略。我们的结果表明,无论采用何种网络切片策略,MMD 都可以同时提高 eMBB 可实现率和 URLLC 可靠性。
更新日期:2020-03-01
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