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Assuming that the number of possible decisions for a transmitter (e.g., the number of possible beamforming 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.
Future wireless communications are largely inclined to deploy a massive number of antennas at the base stations (BS) by exploiting energy-efficient and environmentally friendly technologies. An emerging technology called dynamic metasurface antennas
The recent concept of beamspace multiple input multiple output (MIMO) can significantly reduce the number of required radio-frequency (RF) chains in millimeter-wave (mmWave) massive MIMO systems without obvious performance loss. However, the fundamen
Terahertz (THz) communications have been envisioned as a promising enabler to provide ultra-high data transmission for sixth generation (6G) wireless networks. To tackle the blockage vulnerability brought by severe path attenuation and poor diffracti
Phase Shift Keying on the Hypersphere (PSKH), a generalization of conventional Phase Shift Keying (PSK) for Multiple-Input Multiple-Output (MIMO) systems, is introduced. In PSKH, constellation points are distributed on a multidimensional hypersphere.
In this paper, we introduce the problem of decision-oriented communications, that is, the goal of the source is to send the right amount of information in order for the intended destination to execute a task. More specifically, we restrict our attent