Iterative Interference Modulation Classification

In the presence of co-channel interference in cellular networks, interference mitigation by detecting the desired signal jointly with the interference promises considerable gain over the conventional way of handling the interference as colored Gaussian. Even though such interference-aware detection can improve the performance, it requires some information on the interference. In particular, the modulation format of the interference has to be classified to this end, when it is not signaled by the network explicitly. This paper investigates interference modulation classification methods for interference-aware joint detection. We propose an iterative interference modulation classification algorithm that utilizes the decoded information of the desired signal in order to cancel the desired signal from the received signal. After the cancellation, the remaining signal can be treated as interference plus noise so that we can classify the modulation format of the interference at reduced complexity with small performance loss due to decoding errors.