Code-Aided Modulation Classification Algorithm for Multiuser Uplink SC-FDMA Systems

Modulation classification has attracted great interest in rapid deployment in wireless radios for civilian and military applications. While there is a massive amount of works on this topic for single-signal transmissions, a few works are reported in the literature for multi-signal transmissions. Therefore, there is an urgent need to explore different modulation classification algorithms for such scenarios. In this work, we propose a novel modulation classification algorithm for multiuser uplink single-carrier frequency division multiple access systems exploiting the channel decoder's soft information as a beneficial resource to improve the classification performance. Starting from the maximum-likelihood principle, we analytically design the proposed algorithm using a space-alternating generalized expectation-maximization approach. Channel estimation is also developed as an auxiliary task for the proposed algorithm. Simulation results indicate that the proposed algorithm is superior to the traditional algorithms with reduced processing time.