2025/08/13 by Petrov, Sergey, Lasaulce, Samson, Debbah, Merouane
#49M05 #68P30 #F.2.1 #FOS: Electrical engineering #FOS: Mathematics #G.1.3 #Numerical Analysis (math.NA) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2508.09646
Precoding matrix construction is a key element of the wireless signal processing using the multiple-input and multiple-output model. It is established that the problem of global throughput optimization under per-antenna power constraints belongs, in general, to the class of monotonic optimization problems, and is unsolvable in real-time. The most widely used real-time baseline is the suboptimal solution of Zero-Forcing, which achieves a cubic complexity by discarding the background noise coefficients. This baseline, however, is not readily adapted to per-antenna power constraints, and performs poorly if background noise coefficients are not negligible. In this paper, we are going to present a computational algorithm which constructs a precoder that is SINR multiobjective Pareto-optimal under per-antenna power constraints - with a complexity that differs from that of Zero-Forcing only by a constant factor. The algorithm has a set of input parameters, changing which skews the importance of particular user throughputs: these parameters make up an efficient parameterization of the entire Pareto boundary.