Efficient Data Sensing Algorithm with Generalized Cascaded Chaotic Maps for Secure Cognitive Radio in 5G Networks

Efficient Data Sensing Algorithm with Generalized Cascaded Chaotic Maps for Secure Cognitive Radio in 5G Networks

연구 분야: Networking

학회: SN Computer Science

Sparse code multiple access (SCMA) has emerged as a significant technology to satisfy the essential criteria for 5G wireless networks, including high data rates, widespread connection, reliability, and greater spectrum efficiency. Under the restriction of scarce and limited spectrum utilization in 5G networks, the integrated cognitive radio (CR) with SCMA is a promising solution to handle these crucial needs. A reliable and secure connection network should be built in addition to this integrated network to deal with densely deployed networks. A secure transmission sensing approach for CR-SCMA systems employing chaos theory has been presented in the paper. Different chaotic maps, including the logistic map, tent map, Chebyshev map, sine map, and the generalized cascaded chaotic map (CCS), have been employed for sensing with secure communication. Bit error rate (BER) and probability of detection with effective simulation are two of the metrics used for performance evaluation. Instead of using random sequences, the chaos-based signal transmission provides a viable solution for 5G generation networks with a secure wireless communication link. Using chaotic map signals, which are extremely sensitive to their initial conditions and have non-periodic properties, the eavesdropper or the unauthorized user cannot simply grab the encrypted and secured vital data.