An Energy-Efficient MIMO Algorithm with Receive Power Constraint
Andr\'es Alay\'on Glazunov

TL;DR
This paper introduces an energy-efficient MIMO algorithm that maximizes the rate-to-power ratio under receive power constraints, demonstrating significant energy savings and improved efficiency with more antennas and higher SNR.
Contribution
The paper proposes the EEWF algorithm for MIMO systems with receive power constraints, offering a novel approach to optimize energy efficiency over traditional capacity-based methods.
Findings
EEWF outperforms traditional Water-Filling in energy efficiency by over an order of magnitude.
Energy efficiency increases with the number of antennas and SNR.
Transmission rate grows slower than Shannon capacity, while total transmit power decreases with more antennas.
Abstract
We consider the energy-efficiency of Multiple-Input Multiple-Output (MIMO) systems with constrained received power rather than constrained transmit power. A Energy-Efficient Water-Filling (EEWF) algorithm that maximizes the ratio of the transmission rate to the total transmit power has been derived. The EEWF power allocation policy establishes a trade-off between the transmission rate and the total transmit power under the total receive power constraint. The static and the uncorrelated fast fading Rayleigh channels have been considered, where the maximization is performed on the instantaneous realization of the channel assuming perfect information at both the transmitter and the receiver with equal number of antennas. We show, based on Monte Carlo simulations that the energy-efficiency provided by the EEWF algorithm can be more than an order of magnitude greater than the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Network Optimization · Energy Harvesting in Wireless Networks
