Manumula Srinubabu on Muck Rack

Manumula Srinubabu

As seen in: Nature
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Manumula

Contact Manumula, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

MMU-STCNN-BDQ: a deep reinforcement learning framework for secure and energy-efficient beamforming in 6G mMIMO networks

|
By Sivasubramanyam Medasani, Tathababu Addepalli, Manish Sharma, Ashish Pandey, Kama Ramudu, Manumula Srinubabu
| Nature Verified
Abstract To achieve energy-efficient and secure beamforming in 6G massive MIMO networks, especially in millimeter-wave (mmWave) bands. This research work introduces a hybrid framework utilizing the Massive Multi-User Spatiotemporal Convolutional Neural Network (MMU-STCNN) and Bi-Gated Deep Q-Learning (BDQ). The MMU-STCNN extracts secure beamforming prediction vectors from channel state information (CSI) using spatiotemporal and pooling layers enhanced by Multi-User Attention (MUA) mechanisms.
Open in Who Shared Issue with article?
See all 1 articles
 •  Privacy  •  Terms  •  Security and Legal  •   •   •   • 

© 2026 Muck Rack

SOC 2® Certified