Decision Set Optimization and Energy-Efficient MIMO Communications

Hang Zou (1) , Chao Zhang , Samson Lasaulce (1) , Lucas Saludjian (2) , Patrick Panciatici (3)

1 L2S - Laboratoire des signaux et systèmes
2 G2ELab - Laboratoire de Génie Electrique de Grenoble
3 RTE - Réseau de Transport d'Electricité [Paris]

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.

Keywords: Energy-Efficiency; Evolutionary Algo- rithms; Power Control; Quantization; Resource Allocation

Domains: Engineering Sciences [physics]

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⟩