Abstract
This paper explores the maximization of the harvested power efficiency (HPE) in a modular extremely large multiple-input multiple-output (XL-MIMO) system, which supports energy harvesting (EH) for near-field users. These users are located in spatially distinct visibility regions (VRs) with non-stationary channel characteristics. We propose to determine which sub-arrays are switched on or off as well the power control coefficients at the sub-arrays to maximize the HPE. The design can be processed via a multi-tier joint optimization framework based on fractional programming. The numerical results showcase that the HPE performance of the proposed algorithm is nearly optimal, comparable to that of exhaustive search. As a matter of fact, it achieves up to a 120% gain over the benchmark scheme which uses the entire XL-MIMO array with equal power allocation (PA) across sub-arrays, while significantly reducing the computational time.