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Deep Reinforcement Learning for Backscatter Communications: Augmenting Intelligence in Future Internet of Things
Backscatter communication (BC) technology offers sustainable solutions for next-generation Internet-of-Things (IoT) networks, where devices can transmit data by reflecting and adjusting incident radio frequency signals.
LSTM-Based Distributed Conditional Generative Adversarial Network For Data-Driven 5G-Enabled Maritime UAV Communications
Secondly, to enhance the applications for the proposed trained channel model for the spatial domain, we have designed an LSTM-DCGAN based UAV network, where each one will learn mmWave CSI for all the distributions.
Opportunities for Physical Layer Security in UAV Communication Enhanced with Intelligent Reflective Surfaces
Unmanned Aerial Vehicles (UAVs) are an important component of next-generation wireless networks that can assist in high data rate communications and provide enhanced coverage. Their high mobility and aerial nature offer deployment flexibility and low-cost infrastructure support to existing cellular networks and provide many applications that rely on mobile wireless communications.
Joint Optimization for Secure Ambient Backscatter Communication in NOMA-enabled IoT Networks
Non-orthogonal multiple access (NOMA) has emerged as a novel air interface technology for massive connectivity in sixth-generation (6G) era.
Backscatter Sensors Communication for 6G Low-powered NOMA-enabled IoT Networks under Imperfect SIC
In this paper, we introduce a BSC in multi-cell IoT network, where a source in each cell transmits superimposed signal to its associated IoT devices using NOMA.
