Department of Computer Science and Information Systems
Permanent URI for this collectionhttp://localhost:4000/handle/123456789/1928
Browse
3 results
Search Results
Item Secrecy capacity and efficiency outage analysis of cooperative phy-secure wireless systems and secrecy capacity-based RIS design(IEEE, 2025-03) Bitragunta, Sainath; Bhatia, AshutoshPhysical layer (PHY) security (PLS) leverages the inherent randomness of wireless fading channels to provide enhanced secrecy capacity. In this work, we consider a four-node, dual hop, eavesdropper-aware cooperative PHY-security model. Considering probabilistic relay selection and relaying in the presence of hybrid fading channels, we develop an insightful analysis for the probability of PHY-secrecy capacity outage (PSCO) and PHY-secrecy efficiency outage (PSEO). Specifically, we derive closed form expressions for these performance measures and evaluate them numerically to obtain valuable qualitative insights. We also develop an insightful comparative study to show that the cooperative PLS relay model having a destination node equipped with multiple antennas and performing selection combining delivers superior PHY-secrecy outage performance. We extend the analysis to the reconfigurable intelligent surface (RIS)-assisted cooperative PLS system. Specifically, we address the design problem of N, the number of reflecting elements in RIS. We develop insightful criteria based on secrecy capacity to derive a closed form lower bound on N. This insightful result provides the values of N that could achieve superior PHY-secrecy capacity than the relay-assisted cooperative PLS system. Our analysis of the former cooperative PLS model and its extension to RIS design is useful for next generation cooperative PLS relay and RIS-assisted wireless systems and networks.Item Relay Selection, Eavesdropper-Aware Relaying, PHY-Secrecy Capacity Analysis of Cooperative Wireless System over Hybrid Fading Channels(IEEE, 2023) Bhatia, Ashutosh; Bitragunta, SainathPhysical layer (PHY) security (PLS) exploits the randomness of wireless fading channels and offers better secrecy capacity. Cooperative and eavesdropper-aware relays are useful in establishing reliable and energy-efficient communication links between the source transmitter and destination receiver and enhancing PHY secrecy. We consider a four-node, two-hop cooperative PHY-security model with one eavesdropper node. For it, we propose relay selection probabilistically and relaying in the presence of hybrid fading channels. We derive closed-form expressions for probabilities with which the regenerative relay is selected. Further, we develop an analysis of PHY-secrecy capacity and gain useful insights. We evaluate and validate the performance of the proposed strategy and present different numerical results. The proposed model with the relay selection and energy-efficient relaying strategy is a useful potential benchmark for more complex power-adaptive cooperative PHY-secure systems and networks.Item Fuzzy Logic and AI-Powered, SDR Relay for Secure and Efficient Cooperative Radio Communication(IEEE, 2024) Bitragunta, Sainath; Bhatia, AshuthoshIn this article, we develop a novel approach that leverages the capabilities of fuzzy logic and artificial intelligence (AI) to develop an intelligent, efficient cooperative RCN. Software defined radio (SDR) is flexible, scalable, and reconfigurable. Considering heterogeneous radio communication networks (RCNs), conventional relays do not perform well due to their limitations (security vulnerabilities in cooperative Internet-of-Things (IoT), inefficiencies in half-duplex relaying, etc.). We propose an AI-powered, fuzzy logic-based SDR relay to address these issues. These intelligent relays could be useful and outperform conventional relays due to their adaptability and reconfigurabilty, with added intelligence based on AI and fuzzy logic. The proposed next generation SDR relays offer significant advantages over traditional relays and have the potential to revolutionize the field of radio communication. Specifically, we analyze the decimation technique in SDR signal-to-interference plus noise ratio (SINR) resampler, Mamdani fuzzy logic controller, and use a machine learning (ML) model that uses RADIOML data set. Based on the simulation results, we show that applying fuzzy logic with an ML-enabled SDR relay could improve energy efficiency and reliability performance in advanced radio networks.