Collision Control in Tandem Spreading Multiple Access with Cognitive Radio for 6G Internet of Things: Enhanced System Reliability through Effective User Identification
Kailin Wang, Guoyu Ma, Yiyan Ma, Mi Yang, Yunlong Lu, Jingya Yang, Bo Ai · IEEE Vehicular Technology Magazine · 2025
Supported by 6G communication technologies, the Internet of Things (IoT) is realizing the vision of connecting everything, with massive machine-type communication (mMTC) scenarios serving as its cornerstone. Tandem spreading multiple access (TSMA), as an emerging grant-free nonorthogonal multiple access (NOMA) scheme, has been widely applied in mMTC scenarios. However, with the rapid growth of device numbers in the 6G IoT, the issue of data collision due to nonorthogonal resource allocation has become increasingly prominent. This specifically manifests as increased difficulty in user identification and data recovery, directly impacting the reliability of mMTC systems. To address these challenges, a TSMA scheme integrated with cognitive radio (CR) is proposed in this article. This scheme allows each user to utilize autonomous sensing modes to obtain channel information, thereby reducing the likelihood of data collision through a “listen-before-talk” strategy. Additionally, a two-stage user identification algorithm is proposed to mitigate the impact of data segmentation on user identification performance. Theoretical analysis and simulation results validate the feasibility of CR-TSMA, demonstrating that CR-TSMA significantly enhances system reliability through effective user identification and collision control strategies.