The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 17, 2024

Filed:

May. 04, 2022
Applicant:

Tata Consultancy Services Limited, Mumbai, IN;

Inventors:

Garima Mishra, Bangalore, IN;

Nikita Trivedi, Bangalore, IN;

Hemant Kumar Rath, Bhubaneswar, IN;

Bighnaraj Panigrahi, Bangalore, IN;

Shameemraj Nadaf, Bangalore, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04W 24/02 (2009.01); H04B 1/715 (2011.01); H04W 16/14 (2009.01); H04W 72/541 (2023.01); H04W 84/12 (2009.01);
U.S. Cl.
CPC ...
H04W 24/02 (2013.01); H04B 1/715 (2013.01); H04W 16/14 (2013.01); H04W 72/541 (2023.01); H04W 84/12 (2013.01);
Abstract

This disclosure relates to method and system for improving Wi-Fi performance in co-existing communication networks using learning methodologies. In recent times, most of telecom operators have expressed interest in deploying LTE (Long-Term Evolution) over the unlicensed spectrum. However, simultaneous use of unlicensed band (by operators using LTE and other Wi-Fi) presents coexistence challenges in terms of network performance especially for the Wi-Fi. The disclosed techniques enable improving the Wi-Fi performance in the co-existing communication networks based on learning methodologies. The disclosed techniques improve Wi-Fi performance based on several steps that includes detecting an interfering channel, and further identifying an optimal channel to mitigate the interference caused by the detected interfering channel. The optimal channel is identified based on an optimization technique, wherein the optimization technique is a reinforcement learning technique based on a Q-learning.


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