Joint Power Allocation and Rate Control for Rate Splitting Multiple Access Networks with Covert Communications
Nguyen Quang Hieu, Dinh Thai Hoang, Dusit Niyato, Diep N. Nguyen, Dong, In Kim, and Abbas Jamalipour

TL;DR
This paper introduces a stochastic optimization and learning-based approach for joint power and rate control in RSMA networks, enhancing covert communication rates and system fairness under adversarial conditions.
Contribution
It proposes a novel adaptive framework combining stochastic optimization and learning algorithms for secure, efficient power and rate management in RSMA systems.
Findings
Achieves positive covert transmission rates in finite blocklength regimes.
Increases covert rates significantly at high SNR levels (20-40 dB).
Outperforms conventional schemes with non-saturating high SNR rates.
Abstract
Rate Splitting Multiple Access (RSMA) has recently emerged as a promising technique to enhance the transmission rate for multiple access networks. Unlike conventional multiple access schemes, RSMA requires splitting and transmitting messages at different rates. The joint optimization of the power allocation and rate control at the transmitter is challenging given the uncertainty and dynamics of the environment. Furthermore, securing transmissions in RSMA networks is a crucial problem because the messages transmitted can be easily exposed to adversaries. This work first proposes a stochastic optimization framework that allows the transmitter to adaptively adjust its power and transmission rates allocated to users, and thereby maximizing the sum-rate and fairness of the system under the presence of an adversary. We then develop a highly effective learning algorithm that can help the…
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Taxonomy
TopicsWireless Communication Security Techniques · Advanced Wireless Communication Technologies · Cryptography and Data Security
