ARTIFICIAL INTELLIGENCE-DRIVEN OPTIMIZATION OF RESOURCE ALLOCATION IN NEXT-GENERATION WIRELESS COMMUNICATION
Muhammad Ali
Journal
- ISSN / E-ISSN
- 3104-8722 / 3104-8730
- DOI
- 10.68156/ktvyfn77 ↗
- Volume · Issue · Pages
- 3 · 2 · —
- Publisher
- Global Heritage Research Center for Languages and Literature
- Article URL
- https://iijhmss.com/IIJHMSS/index.php/IIJHMSS/article/view/1... ↗
- Article details
- Unverified
Publication date (each date has its type and source)
31 May 2026
Publisher publication date · source: Journal websites (OAI-PMH feeds of Open Journal Systems)
| Type | Date | Source |
|---|---|---|
| Publisher publication date | 31 May 2026 | Journal websites (OAI-PMH feeds of Open Journal Systems) |
Keywords (as given): 6G; 5G-Advanced; Artificial Intelligence; Machine Learning; Network Optimization; Resource Allocation; Wireless Communication
HEC Status at Publication Not the journal's current status
HEC Status at PublicationConclusive
HEC status at publication
Recognized
Y
Based on the recorded HEC dataset applicable to the article's publication date. Listed as Y in the HEC list for HEC 2026-27.
- Journal
- Insights (Bhalwal. Online)
- Publication date used
- 31 May 2026 (Publisher publication date)
- Applicable HEC period
- HEC 2026-27 (version 1) · 01 Apr 2026 – 31 Dec 2027
- Category
- Y
- Recognition status
- Recognized (OK_RECORD_FOUND)
- Source
- HEC Recognized National Research Journals, V 4.0 page 12, row 120
- Verification status
- Verified against source · last verified 21 Sep 2026
Informational only. HJRS.com.pk is independent and is not an official HEC website: confirm with the source document.