Multiuser modulation classification based on cumulants in additive white Gaussian noise channel

Abstract

In this paper the negative impacts of interference transmitters on automatic modulation classification (AMC) have been discussed. We proposed two approaches for AMC in the presence of interference: single user modulation classification (SUMC) and multiuser modulation classification (MUMC). When the received power of one transmitter is larger than the other transmitters, SUMC approach recognizes the modulation type of that transmitter and other transmitters are treated as interferences. Alternatively when the received powers of all transmitters are close to each other we propose MUMC method to recognize the modulation type of all of the transmitted signals. The features being used to recognize the modulation types of transmitters for both approaches, SUMC and MUMC are higher order cumulants. The superposition property of cumulants for independent random variables is utilized for SUMC and MUMC. We investigated the robustness of our classifier with respect to different powers of the received signals via analytical and simulation results and we have shown the analytical results will be confirmed by simulations. Also we studied the effect of signal synchronization error via simulation results in the both condition for MUMC and SUMC.

Blind Modulation Classification for Cognitive Satellite in the Spectral Coexistence Context

“…However, AM PT-based method is more complex than [9] (relying on Classical Cumulants which are low-complexity) but as seen the blind performance results (Section IX), the trade-off is clearly in favor of our method.…”

“…In the case of partially overlapping signals -i.e. when the residual CFOs are of the order the symbol rhythm -filter-bank may be use to separate the interferers before the AMC step [9]. However, to the best of our knowledge, the realistic scenario proposed in Section II has never been specifically carried out.…”

“…It relies on a MD classification based on some ratios of classical Higher Order Cumulants (HOCs). While this approach shows a very low complexity, its performance would quickly degrade in the blind scenario with realistic impairments: actually, it is assumed in [9] a perfect knowledge of all the parameters involved in the mixture. Moreover, the method performs well only if the residual f ru , delays τ u and phases φ u are null which does not hold in practice.…”

“…Zaerin et al proposed a second approach to tackle the single-antenna MAMC issue [9]. It relies on a MD classification based on some ratios of classical Higher Order Cumulants (HOCs).…”

“…Specific case study: U = 2 with the 2/4PT classifier Among the co-channel scenarios, the situation where two signals coexist is encountered in several contexts such as in dual-satellite systems. This scenario was studied by Zaerin et al in [9] with simplifying assumptions. In Section IX, we mainly study the performance of our method in this specific context and we confront it with Zaerin's method.…”