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Constrained combinatorial clustering (CCC) is a new approach for grouping multiple features where the clustering metric depends on an unknown communication channel assignment. Features assigned to the same channel cannot be from the same source and, conversely, channels assigned to the same source must be distinct. While the number of sources and their states are unknown, the channels are assumed to be known except for additive noise. Potential clustering assignments are checked for compatibility with the constraints in a structured way that results in significant computational savings with respect to exhaustive enumeration, especially when combined with a -best channel assignment algorithm that has polynomial complexity. By combining two channel assignment methods (exhaustive and -best) with two clustering techniques (CCC and greedy), four new algorithms are presented to solve this …