Reinforcement Learning based Routing in Urban Vehicular Communication using mmWave Beamforming Techniques

Abstract

Abstract: The present invention is a reinforcement learning based routing in urban vehicular communication using mmWave beamforming techniques herein, vehicular communication using machine learning approaches are involved in vehicle to vehicle (V2V) routing, in this scenario mmWave (millimetre Wave) beamforming techniques integrated reinforcement learning based routing is proposed, where it adjust its beam patterns based on its learned policies. Machine learning algorithm is used for prediction of vehicle mobility and mmWave technique is used for carrying the signal towards a specific area with higher rate of signal strength using beamforming technique.

Specification

Description:Title of the invention:
Reinforcement Learning based Routing in Urban Vehicular Communication using mmWave Beamforming Techniques

Field of the invention:
The present invention relates to the field of a learning system and particularly relates to a reinforcement learning based routing in urban vehicular communication using mmWave beamforming techniques.

Prior art to the invention:
Patent document number with application "US20220169267" titled "signal detection method and apparatus based on reinforcement learning for vehicular MIMO communication" describes "The present exemplary embodiments provide a reinforcement learning based signal detection apparatus and method for vehicular MIMO communication which flexibly adjust the performance and the complexity by applying the reinforcement learning during the MIMO signal detecting process, improving a trade-off relationship between the performance and the complexity of the MIMO signal detection, and controlling the number of episodes of the reinforcement learning in accordance with the speed of the vehicle".

wherein, the present invention is a reinforcement learning based routing in urban vehicular communication using mmWave beamforming techniques.

Objects of the invention:
The primary object of the present invention is a reinforcement learning based routing in urban vehicular communication using mmWave beamforming techniques.

Summary of the invention:
It is an aspect of the invention that a reinforcement learning based routing in urban vehicular communication using mmWave beamforming techniques.






DETAILED DESCRIPTION:
The present invention is a vehicular communication facing lot of entanglements for effective and reliable data transmission between two vehicles in an urban area. Various machine learning approaches are involved in vehicle to vehicle (V2V) routing, in this scenario mmWave (millimetre Wave) beamforming techniques integrated Reinforcement Learning based routing is proposed, where it adjust its beam patterns based on its learned policies. Here machine learning algorithm is used for prediction of vehicle mobility and mmWave technique is used for carrying the signal towards a specific area with higher rate of signal strength using beamforming technique. Proposed algorithm optimizes wireless transmission and routing path between two vehicle nodes in intelligent transportation system. This algorithm ensures reliable and adaptive system for vehicular communication in dynamic environments.
, Claims:Claims:

1) We claim,
A reinforcement learning based routing in urban vehicular communication using mmWave beamforming techniques, as a method claim, vehicular communication using machine learning approaches are involved in vehicle to vehicle (V2V) routing, in this scenario mmWave (millimetre Wave) beamforming techniques integrated reinforcement learning based routing is proposed, where it adjust its beam patterns based on its learned policies,
wherein, machine learning algorithm is used for prediction of vehicle mobility and mmWave technique is used for carrying the signal towards a specific area with higher rate of signal strength using beamforming technique.

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