Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
98%
921
2 minutes
20
This paper provides an accurate target cell's RSRP (received signal received power) prediction technique for cellular handovers, ensuring robust connectivity for autonomous vehicles (AVs). We propose an extreme gradient boosting (XGBoost)-based mechanism to predict channel state information (CSI) in advance prior to a cell handover request due to lower RSRP. Our test results indicate that for speeds ranging from 0 to 120 km/h, the proposed prediction technique improves the handover success rate (HSR) by up to 4%. In particular, the average achieved success rate with the proposed algorithm is 97% compared to the conventional algorithm providing only 93% success rate. The proposed solution can work for any frequency pair and wireless technology.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12217501 | PMC |
http://dx.doi.org/10.1038/s41598-025-04183-1 | DOI Listing |