KSC 2018
Current Result Document : 10 / 10
| 한글제목(Korean Title) |
Radio Resource Allocation in 5G New Radio: A Neural Networks Approach |
| 영문제목(English Title) |
Radio Resource Allocation in 5G New Radio: A Neural Networks Approach |
| 저자(Author) |
Madyan Alsenwi
Choong Seon Hong
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| 원문수록처(Citation) |
VOL 45 NO. 02 PP. 1073 ~ 1075 (2018. 12) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The minimum frequency-time unit that can be allocated to a User Equipment (UE) in the fifth generation (5G) cellular networks is a Resource Block (RB). An RB is a channel composed of a set of OFDM subcarriers for a time slot duration. 5G New Radio (NR) permits a large number of block shapes varying from 15 kHz to 480 kHz. In this paper, we tackle the problem of RBs allocation to UEs. The RBs are allocated at the beginning of each time slot based on the channel state of each UE. The problem is formulated based on the Generalized Proportional Fair (GPF) formulation. We model the problem as a 2-Dimensions Hopfield Neural Networks (2D-HNN). Then, the energy function of 2D-HNN is investigated to solve the problem. Simulation results show efficiency of the proposed approach. |
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