Efficient Security Enhancement Techniques for Ultra-reliable Low Latency Communication in 5G and 6G Wireless Networks

Abstract

The fifth generation (5G) wireless networks have revolutionized the current communication landscape by enabling many futuristic and smart applications. This brings 5G to introduce an innovative service like Ultra-reliable Low Latency communication (URLLC) to facilitate mission-critical 5G applications such as industrial automation, autonomous driving, smart healthcare, and smart grid operations. Most importantly, URLLC enables ultra-high reliability (i.e., up to 99.999%) and low latency (i.e., < 1ms) data transmission to achieve the desired Quality-of-Service (QoS) of these mission-critical applications. To ensure the stringent QoS requirement, URLLC uses short packet finite block length signals. However, the exponential rise in wireless data traffic generated from billions of smart Internet-of-Things (IoT) devices utilizing URLLC service is highly vulnerable to external eavesdropping and security threats. Moreover, the finite block length constraint and low latency criteria eliminate the possibility of utilizing complex cryptography-based security techniques for URLLC. In this regard, Physica layer security (PLS) has emerged as a potential technique for providing lightweight security enhancement for URLLC by exploiting the randomness of wireless channel characteristics. Therefore, this dissertation proposes the development of efficient security enhancement techniques utilizing PLS for URLLC mission-critical 5G applications. The first contribution of this dissertation is to ensure the security of URLLC signal transmission to the cell edge users in an IoT network. In this regard, the cooperative non-orthogonal multiple access (CNOMA) has emerged as a promising 5G technology that ensures the reliability of signal transmission by cooperatively transmitting the information of cell edge users through near users or relay networks in a multi-user scenario. However, the absence of a direct communication link between the base station (BS) and the cell edge URLLC user hugely degrades the reliability of data transmission and increases the chance of information leakage due to eavesdropping. Therefore, a coordinated direct and relayed transmission (CDRT) scheme is proposed for the CNOMA system to ensure the reliability and security of URLLC data transmission. A dedicated half duplex (HD) relay node is used to transmit an artificial noise (AN) signal along with the URLLC information intended for the cell edge user to confuse the eavesdroppers and decrease the information leakage. However, employing HD relay nodes in CNOMA may suffer from imperfect decoding and low throughput levels for legitimate users. Moreover, the large separation distance between the transmitter and the cell edge URLLC introduces challenges for ensuring the security and reliability of signal transmission. Therefore, the second contribution of the dissertation proposes an efficient PLS enhancement scheme for URLLC users at the cell edge by utilizing the CNOMA technique. An AN-assisted jamming, and full-duplex (FD) communication utilizing the near user to the BS as relay is proposed to improve the PLS of cell-edge URLLC users. The efficient resource optimization framework is proposed to improve the PLS performance for URLLC while managing the residual self-interference (RSI) at the FD relay and the intercept capabilities of the eavesdroppers. A large number of low-power IoT devices are deployed in an industrial IoT (IIoT) scenario where critical control information is exchanged among these devices in the form of short packets to facilitate URLLC. However, such confidential information transmission is vulnerable to information leakage and security threats due to the openness of wireless medium. Additionally, the presence of a large number of low-power devices in the system requires efficient utilization of system resources to achieve energy-efficient communication. Therefore, the third contribution of this dissertation is the development of an efficient PLS scheme for improving the secure energy efficiency of URLLC signal transmission in a multi-user and multi-eavesdropping scenario of the mission-critical IIoT application. The proposed PLS technique jointly optimizes the URLLC blocklength and pilot signal length to improve the secrecy throughput and optimizes the power allocation to ensure the secure energy efficiency of the system. In a large-scale IoT network ensuring the security of URLLC signal transmission is challenging because of centralized computing of confidential user information. To address this, the fourth direction of the dissertation is to propose efficient and secure decentralized computation of information using a Quantum-enhanced Federated Learning (QFL) framework to preserve the data privacy of edge URLLC users. The proposed QFL framework efficiently allocates the resources to ensure secure URLLC task offloading while managing the data heterogeneity in comparison to classical FL-based methods. Finally, the dissertation presents the concluding remarks on the research contributions and discusses the security challenges, enabling technologies, and future research directions for next-generation wireless service Hyper Reliable Low Latency Communication (HRLLC) in 6G.