NOMA Pilot Based Channel Estimation for 6G CF–mMIMO Communication System

This paper delves into the intricacies of channel estimation within cell-free massive multiple input multiple output (CF-mMIMO) systems integrated with pilot signals of non-orthogonal multiple access (NOMA), promising enhanced spectral efficiency and scalability to meet increasing user demands in the 6G cellular wireless communication system. In this work, maximum likelihood (ML) and linear minimum mean squared error (LMMSE) based channel estimation is adopted for proposed NOMA pilot based CF-mMIMO systems. Next, a closed-form expression for channel estimation mean square error (MSE) for both ML and LMMSE techniques for NOMA pilot based CF-mMIMO system is derived, which include power allocation techniques for pilot symbols. Next, a MATLAB-based thorough simulation analysis is performed and a MSE vs. signal-to-noise ratio (SNR) curve is obtained for both ML and LMMSE techniques. Finally, the result obtained is compared with the conventional orthogonal pilot symbol-based channel estimation for the CF-mMIMO system. The result comparison concludes that the NOMA pilot based channel estimation outperforms the conventional technique with little high computational complexity, however it further reduces the pilot contamination problem.