ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 Performance Analysis and Optimization of the Coverage Probability in Dual Hop LoRa Networks With Different Fading Channels
Cited 26 time in scopus Download 174 time Share share facebook twitter linkedin kakaostory
저자
Tien Hoa Nguyen, 정우성, Lam Thanh Tu, Trinh Van Chien, 유대승, 노승환
발행일
202006
출처
IEEE Access, v.8, pp.107087-107102
ISSN
2169-3536
출판사
IEEE
DOI
https://dx.doi.org/10.1109/ACCESS.2020.3000600
초록
In this work, the performance evaluation and the optimization of dual-hop LoRa network are investigated. In particular, the coverage probability (Pcov) of edge end-devices (EDs) is computed in closed-form expressions under various fading channels, i.e., Nakagami- m and Rayleigh fading. The Pcov under Nakagami- m fading is computed in the approximated closed-form expressions; the Pcov under Rayleigh fading, on the other hand, is calculated in the exact closed-form expressions. In addition, we also investigate the impact of different kinds of interference on the performance of the Pcov, i.e., intra-SF interference, inter-SF interference (or capture effect) and both intra- and inter-SF interference. Our findings show that the impact of imperfect orthogonality is not non-negligible, along with the intra-SF interference. Moreover, based on the proposed mathematical framework, we formulate an optimization problem, which finds the optimal location of the relay to maximize the coverage probability. Since it is a mixed integer program with a non-convex objective function, we decompose the original problem with discrete optimization variables into sub-problems with a convex feasible set. After that, each sub-problem is effectively solved by utilizing the gradient descent approach. Monte Carlo simulations are supplied to verify the correctness of our mathematical framework. In addition, the results manifest that our proposed optimization algorithm converges rapidly, and the coverage probability is significantly improved when the location of relay is optimized.
KSP 제안 키워드
Closed-form expressions, Coverage probability, Discrete Optimization, LoRa networks, Mixed integer program, Monte-Carlo simulation(MCS), Non-convex, Optimal location, Optimization algorithm, Optimization problem, Performance analysis and optimization
본 저작물은 크리에이티브 커먼즈 저작자 표시 (CC BY) 조건에 따라 이용할 수 있습니다.
저작자 표시 (CC BY)