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Distributed antenna selection for distributed massive multiple input multiple output (MIMO) communication systems reduces computational complexity compared to centralized approaches, and provides high fault tolerance while retaining diversity and spatial multiplexity. We propose a novel distributed algorithm for antenna selection and show its advantage over existing centralized and distributed solutions. The proposed algorithm is shown to perform well with imperfect channel state information, and to execute a small number of simple computational operations per node, converging fast to a steady state. We base it on reversing Petri nets, a variant of Petri nets inspired by reversible computation, capable of both forward and backward execution while obeying conservation laws.