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Decision Set Optimization and Energy-Efficient MIMO Communications

Abstract : Assuming that the number of possible decisions for a transmitter (e.g., the number of possible beam-forming vectors) has to be finite and is given, this paper investigates for the first time the problem of determining the best decision set when energy-efficiency maximization is pursued. We propose a framework to find a good (finite) decision set which induces a minimal performance loss w.r.t. to the continuous case. We exploit this framework for a scenario of energy-efficient MIMO communications in which transmit power and beamforming vectors have to be adapted jointly to the channel given under finite-rate feedback. To determine a good decision set we propose an algorithm which combines the approach of Invasive Weed Optimization (IWO) and an Evolutionary Algorithm (EA). We provide a numerical analysis which illustrates the benefits of our point of view. In particular, given a performance loss level, the feedback rate can by reduced by 2 when the transmit decision set has been designed properly by using our algorithm. The impact on energy-efficiency is also seen to be significant.
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Submitted on : Friday, May 29, 2020 - 9:27:14 AM
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Hang Zou, Chao Zhang, Samson Lasaulce, Lucas Saludjian, Patrick Panciatici. Decision Set Optimization and Energy-Efficient MIMO Communications. 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Sep 2019, Istanbul, Turkey. pp.1-7, ⟨10.1109/pimrc.2019.8904148⟩. ⟨hal-02648367⟩

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