This inventor holds 1 USPTO granted patent. Top assignee: Telefonaktiebolaget Lm Ericsson (Publ). Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: The Innovations of Saad Al-ahmadi
Introduction
Saad Al-ahmadi is a notable inventor based in Dhahran, Saudi Arabia. He has made significant contributions to the field of communications, particularly in the area of deep learning and user clustering. His innovative work has led to the development of a patented method that enhances communication efficiency in advanced networks.
Latest Patents
Saad Al-ahmadi holds a patent titled "Deep learning-based user clustering in millimeter wave non-orthogonal multiple access communications." This patent discloses a method and network node for deep learning-based user clustering in millimeter wave (mmWave) non-orthogonal multiple access (NOMA). The method involves determining a minimum number of clusters to be served by the network node, subject to constraints that limit the total number of wireless devices (WDs) in each cluster. Additionally, it includes assigning WDs to each cluster based on the determined minimum number of clusters and their spatial distribution.
Career Highlights
Saad Al-ahmadi is currently employed at Telefonaktiebolaget LM Ericsson (Publ), a leading company in telecommunications. His work at Ericsson focuses on advancing communication technologies and improving network performance through innovative solutions. His expertise in deep learning and communications has positioned him as a valuable asset in the industry.
Collaborations
Saad has collaborated with talented individuals such as Aditya Sriram Rajasekaran and Omar Maraqa. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.
Conclusion
Saad Al-ahmadi's contributions to the field of communications through his innovative patent demonstrate his commitment to advancing technology. His work not only enhances communication efficiency but also showcases the potential of deep learning in modern networks.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
