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Journal Article Spectral Efficient Resource Allocation for URLLC in Distributed Antenna Systems
Cited 6 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Jun-Pyo Hong, Jaehyun Park, Wooram Shin, Seungkwon Baek
Issue Date
2020-12
Citation
IEEE Transactions on Vehicular Technology, v.69, no.12, pp.15057-15067
ISSN
0018-9545
Publisher
IEEE
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1109/TVT.2020.3032697
Abstract
In this paper, we propose novel resource allocation algorithms for ultra-reliable and low-latency communication (URLLC) in distributed antenna systems (DASs) and discuss the effectiveness of the receive antenna deployment and multiple access strategies in fulfilling the stringent reliability and latency requirements. We analyze achievable rates and reliabilities of the DASs with orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) by taking into account the influence of the latency constraint and the non-identical channel distributions of the distributed antennas. Based on the performance analysis, we propose novel resource allocation algorithms for fulfilling the stringent performance requirement in OMA and NOMA. The numerical simulation results provide insightful information for understanding the impacts of multiple access strategy and antenna deployment on the spectral efficiency under the reliability and latency constraints. In particular, NOMA makes it possible to deal with more transmit nodes than OMA, and more dispersed antenna deployment facilitates to achieve a target URLLC performance with less spectrum resource as the ratio of transmit nodes to receive antennas increases. Consequently, the analysis and simulation results provide the meaningful information on the network design for mission-critical applications.
KSP Keywords
Achievable rate, Analysis and simulation, Antenna deployment, Efficient resource allocation, Latency Constraint, Low-Latency Communication, Meaningful information, Non-orthogonal multiple access(NOMA), Numerical simulations, Performance analysis, Resource allocation algorithm