Pathloss determination using Okumura-Hata model and spline interpolation for missing data for Oman

被引:0
|
作者
Nadir, Z. [1 ]
Elfadhil, N. [1 ]
Touati, F. [1 ]
机构
[1] Sultan Qaboos Univ, Dept Elect & Comp Engn, Muscat, Oman
关键词
Okumura Hata model; pathloss; propagation models; spline interpolation;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Imprecise propagation models lead to networks with high co-channel interference and a waste of power. In this paper, we aim to adapt a propagation model for Salalah (OMAN) as we examine the applicability of Okumura-Hata model in Oman in GSM frequency band. The study was carried out for urban area, since measurements provided from Oman Mobile were about the urban areas. The study helped to design better GSM network for the city area. We will accomplish the modification by investigating the variation in pathloss between the measured and predicted values, according to the Okumura-Hata propagation model for a cell in Salalah city and then finding the missing experimental data with spline interpolation. Then, we intend to modify the Okumura-Hata model according to the results obtained in our investigation. We will then verify our modified model by applying it for other cells and conclude the results. For the purpose the mean square error (MSE) was calculated between measured path loss values and those predicated on basis of Okumura-Hata model for an open area. The MSE is up to 6dB, which is an acceptable value for the signal prediction. Therefore, the model gave a significant difference in an open area that allowed necessary changes to be introduced in the model. That error was minimized by subtracting the calculated MSE (15.31dB) from the original equation of open area for Okumura-Hata model. Modified equation was also verified for another cell in an open area in Oman and gave acceptable results. Theoretical simulation by Okumura Hata Model and the obtained experimental data Is compared and analyzed further using a piece-wise cubic spline to interpolate on the set of the experimental data and finding the missing experimental data points.
引用
收藏
页码:422 / 425
页数:4
相关论文
共 50 条
  • [41] Using trend clusters for spatiotemporal interpolation of missing data in a sensor network
    Appice, Annalisa
    Ciampi, Anna
    Malerba, Donato
    Guccione, Pietro
    JOURNAL OF SPATIAL INFORMATION SCIENCE, 2013, (06): : 119 - 153
  • [42] INTERPOLATION OF MISSING DATA USING NONLINEAR AND CHAOTIC SYSTEM-ANALYSIS
    AMRITKAR, RE
    KUMAR, PP
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 1995, 100 (D2) : 3149 - 3154
  • [43] Interpolation of Missing Precipitation Data Using Kernel Estimations for Hydrologic Modeling
    Lee, Hyojin
    Kang, Kwangmin
    ADVANCES IN METEOROLOGY, 2015, 2015
  • [44] Missing data interpolation by using local-global neural networks
    Fariñas, MS
    Pedreira, CE
    ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS, 2002, 10 (02): : 85 - 91
  • [45] Estimation of Missing Rainfall Data Using Spatial Interpolation and Imputation Methods
    Radia, Noor Fadhilah Ahmad
    Zakaria, Roslinazairimah
    Azman, Muhammad Az-Zuhri
    2ND ISM INTERNATIONAL STATISTICAL CONFERENCE 2014 (ISM-II): EMPOWERING THE APPLICATIONS OF STATISTICAL AND MATHEMATICAL SCIENCES, 2015, 1643 : 42 - 48
  • [46] Interpolation of Missing Data in Sensor Networks Using Nonnegative Matrix Factorization
    Suyama, Takayuki
    Kishino, Yasue
    Shirai, Yoshinari
    Mizutani, Shin
    Sawada, Hiroshi
    PROCEEDINGS OF THE 2018 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'18 ADJUNCT), 2018, : 263 - 266
  • [47] Spatial interpolation of daily potential evapotranspiration for New Zealand using a spline model
    Tait, Andrew
    Woods, Ross
    JOURNAL OF HYDROMETEOROLOGY, 2007, 8 (03) : 430 - 438
  • [48] B-Spline Curve Interpolation Model by using Intuitionistic Fuzzy Approach
    Zulkifly, Mohammad Izat Emir
    Wahab, Abd. Fatah
    Zakaria, Rozaimi
    IAENG International Journal of Applied Mathematics, 2020, 50 (04): : 1 - 7
  • [49] Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network
    Zhao, Lingyun
    Wang, Zhuoyu
    Chen, Tingxi
    Lv, Shuang
    Yuan, Chuan
    Shen, Xiaodong
    Liu, Youbo
    GLOBAL ENERGY INTERCONNECTION-CHINA, 2023, 6 (05): : 517 - 529
  • [50] Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network
    Lingyun Zhao
    Zhuoyu Wang
    Tingxi Chen
    Shuang Lv
    Chuan Yuan
    Xiaodong Shen
    Youbo Liu
    Global Energy Interconnection, 2023, 6 (05) : 517 - 529