Patents by Inventor Kemal Davaslioglu

Kemal Davaslioglu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • SYSTEMS AND METHODS FOR DEEP REINFORCEMENT LEARNING FOR OPTIMAL POWER CONTROL IN WIRELESS NETWORKS
    Publication number: 20250184911
    Abstract: Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.
    Type: Application
    Filed: January 31, 2025
    Publication date: June 5, 2025
    Inventors: Ziad El-Jamous, Yalin Evren Sagduyu, Kemal Davaslioglu
  • Systems and methods for deep reinforcement learning for optimal power control in wireless networks
    Patent number: 12267787
    Abstract: Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.
    Type: Grant
    Filed: November 9, 2023
    Date of Patent: April 1, 2025
    Assignee: BLUEHALO LABS, LLC
    Inventors: Ziad El-Jamous, Yalin Evren Sagduyu, Kemal Davaslioglu
  • SYSTEMS AND METHODS FOR DEEP REINFORCEMENT LEARNING FOR OPTIMAL POWER CONTROL IN WIRELESS NETWORKS
    Publication number: 20240089863
    Abstract: Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.
    Type: Application
    Filed: November 9, 2023
    Publication date: March 14, 2024
    Inventors: Ziad El-Jamous, Yalin Evren Sagduyu, Kemal Davaslioglu
  • Systems and methods for deep reinforcement learning for optimal power control in wireless networks
    Patent number: 11856524
    Abstract: Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.
    Type: Grant
    Filed: December 7, 2021
    Date of Patent: December 26, 2023
    Assignee: INTELLIGENT AUTOMATION, LLC
    Inventors: Ziad El-Jamous, Yalin Evren Sagduyu, Kemal Davaslioglu
  • SYSTEMS AND METHODS FOR DEEP REINFORCEMENT LEARNING FOR OPTIMAL POWER CONTROL IN WIRELESS NETWORKS
    Publication number: 20230180138
    Abstract: Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.
    Type: Application
    Filed: December 7, 2021
    Publication date: June 8, 2023
    Inventors: Ziad El-Jamous, Yalin Evren Sagduyu, Kemal Davaslioglu