TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
CA Joint Resource Allocation Algorithm Based on QoE Weight |
| 영문제목(English Title) |
CA Joint Resource Allocation Algorithm Based on QoE Weight |
| 저자(Author) |
LIU Jun-Xia
JIA Zhen-Hong
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| 원문수록처(Citation) |
VOL 12 NO. 05 PP. 2233 ~ 2352 (2018. 05) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
For the problem of cross-layer joint resource allocation (JRA) in the Long-Term Evolution (LTE)-Advanced standard using carrier aggregation (CA) technology, it is difficult to obtain the optimal resource allocation scheme. This paper proposes a joint resource allocation algorithm based on the weights of user’s average quality of experience (JRA-WQOE). In contrast to prevalent algorithms, the proposed method can satisfy the carrier aggregation abilities of different users and consider user fairness. An optimization model is established by considering the user quality of experience (QoE) with the aim of maximizing the total user rate. In this model, user QoE is quantified by the mean opinion score (MOS) model, where the average MOS value of users is defined as the weight factor of the optimization model. The JRA-WQOE algorithm consists of the iteration of two algorithms, a component carrier (CC) and resource block (RB) allocation algorithm called DABC-CCRBA and a subgradient power allocation algorithm called SPA. The former is used to dynamically allocate CC and RB for users with different carrier aggregation capacities, and the latter, which is based on the Lagrangian dual method, is used to optimize the power allocation process. Simulation results showed that the proposed JRA-WQOE algorithm has low computational complexity and fast convergence. Compared with existing algorithms, it affords obvious advantages such as improving the average throughput and fairness to users. With varying numbers of users and signal-to-noise ratios (SNRs), the proposed algorithm achieved higher average QoE values than prevalent algorithms.
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| 키워드(Keyword) |
LTE-Advanced
carrier aggregation
resource allocation
quality of experience
discrete artificial bee colony algorithm
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| 파일첨부 |
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