Optimized Clipping Thresholds for Tandem Spreading Multiple Access in 6G IoT Under Impulsive Noise

This letter presents a code-redundancy-assisted optimization framework for tandem spreading multiple access (TSMA) systems under impulsive noise (IN). While TSMA offers low-complexity, grant-free access for massive machine-type communications (mMTC), its performance degrades in IN environments. Conventional methods optimize nonlinear clipping thresholds per segment, ignoring the global error-correction capabilities of Reed-Solomon (RS) codes. The proposed framework integrates nonlinear clipping with RS decoding constraints, leveraging code redundancy to derive the optimal clipping threshold. Simulations show significant improvements in block error rate (BLER) performance and enhanced robustness against IN with low computational complexity.