TY  - CONF
KW  - Millimeter waves; Urban planning; 28 GHz; Accurate estimation; Distance estimation; LOS; Mm waves; NLOS; Path loss; Received signal strength; Strength models; Urban environments; Ray tracing
ID  - scholars20454
SN  - 979-835033454-8
N2  - In the recent years, mm-wave bands have become popular in the modern wireless communication and vehicular positioning. However, accurate estimation of the distance between the base station and the vehicle is very important to improve localization accuracy. In this work, we evaluated the accuracy of the distance estimation based on the received signal strength (RSS) model for 28 GHz mm-wave in urban environments with LOS and NLOS scenarios. Ray tracing method have been used to predict the RSS of the aforementioned frequency band. The parameters of path loss model, i.e., Close In Log-Distance (CILD) Model, are derived based on linear regression of predicted RSS. The results showed that, RSS model have provided an acceptable level of distance estimation. It provided more accurate estimation in the LOS scenario compared to NLOS scenario. The correlation coefficients (R2) between the actual distance and the estimated distance were 0.76 and 0.73 for LOS and NOLS scenarios respectively. The mean absolute error for distance estimation was 3. S23m in LOS, while 4. SS7m was obtained for NLOS. © 2022 IEEE.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149141758&doi=10.1109%2fICFTSC57269.2022.10040059&partnerID=40&md5=2e45cc18d7c15cdf20fd4c784c7c4846
N1  - Cited by: 0
AV  - none
Y1  - 2022///
TI  - Mm-Wave RSS Evaluation for Distance Estimation in Urban Environments
PB  - Institute of Electrical and Electronics Engineers Inc.
A1  - Bakhuraisa, Yaser A.
A1  - Abd.aziz, Azlan B.
A1  - Geok, Tan K.
A1  - Bakar, Norazhar B. Abu
A1  - Jamian, Saifulnizan B.
ER  -