Distributing Complexity: A New Approach to Antenna Selection for Distributed Massive MIMO
Antenna selection in massive multiple input multiple output (MIMO) communication systems enables reduction of complexity, cost, and power while keeping the channel capacity high and retaining the diversity, interference reduction, spatial multiplexity, and array gains of massive MIMO. We investigate the possibility of decentralized antenna selection both to parallelize the optimization process and put the environment awareness to use. Results of experiments with two different power control rules and varying number of users show that a simple and computationally inexpensive algorithm can be used in real time. The algorithm we propose draws its foundations from self-organization, environment awareness, and randomness.