arXiv subjects

Alexander Koelpin

Publications and source records attributed to Alexander Koelpin.

4 recordsLinked to original sources

arXiv2026

OwnDPDLab: A Flexible Open-Source Testbed for Wideband DPD Algorithm Benchmarking

5G and Beyond-5G standards require digital predistortion (DPD) algorithms to operate on increased signal bandwidths. Wideband laboratory test hardware is cost-intensive, and openly available solutions lack flexibility. The OwnDPDLab provides a highly flexible, affordable, open-source, and openly accessible system. It is based on the RFSoC 4x2 and supports full control of center frequency, sampling mode, output power, and input attenuation at a signal bandwidth of up to 1 GHz. The system's capability is demonstrated by linearizing a laboratory power amplifier using a 196.608 MHz orthogonal frequency division multiplexing (OFDM) signal with 256-QAM modulation using both a memory polynomial and an augmented real-valued time-delay neural network in the first and second Nyquist zone. The system achieves a normalized mean squared error improvement of up to 23 dB and an adjacent channel leakage ratio improvement of up to 11 dB, using DPD.

eess.SP↗

arXiv2026

Digital Predistortion of Power Amplifiers for Quantum Computing

Power amplifiers (PA) are essential for microwavecontrolled trapped-ion and semiconductor spin based quantum computers (QC). They adjust the power level of the control signal and therefore the processing time of the QC. Their nonlinearities and memory effects degrade the signal quality and, thus, the fidelity of qubit gate operations. Driving the PA with a significant input power back-off reduces nonlinear effects but is neither power-efficient nor cost-effective. To overcome this limitation, this letter augments the conventional signal generation system applied in QCs by digital predistortion (DPD) to linearize the radio frequency (RF) channel. Numerical analysis of the qubit behavior based on measured representative control signals indicates that DPD improves its fidelity.

quant-ph↗

arXiv2017

Robust Resource Allocation for MIMO Wireless Powered Communication Networks Based on a Non-linear EH Model

In this paper, we consider a multiple-input multiple-output wireless powered communication network (MIMO-WPCN), where multiple users harvest energy from a dedicated power station in order to be able to transmit their information signals to an information receiving station. Employing a practical non-linear energy harvesting (EH) model, we propose a joint time allocation and power control scheme, which takes into account the uncertainty regarding the channel state information (CSI) and provides robustness against imperfect CSI knowledge. In particular, we formulate two non-convex optimization problems for different objectives, namely system sum throughput maximization and maximization of the minimum individual throughput across all wireless powered users. To overcome the non-convexity, we apply several transformations along with a one-dimensional search to obtain an efficient resource allocation algorithm. Numerical results reveal that a significant performance gain can be achieved when the resource allocation is designed based on the adopted non-linear EH model instead of the conventional linear EH model. Besides, unlike a non-robust baseline scheme designed for perfect CSI, the proposed resource allocation schemes are shown to be robust against imperfect CSI knowledge.

cs.IT↗

arXiv2016

Robust Beamforming for SWIPT Systems with Non-linear Energy Harvesting Model

This paper investigates resource allocation for simultaneous wireless information and power transfer (SWIPT) downlink systems based on a non-linear energy harvesting model. The resource allocation algorithm design is formulated as a non-convex optimization problem for the maximization of the total harvested power. The proposed problem formulation not only takes into account imperfect channel state information (CSI) but also guarantees the quality-of-service (QoS) of information transfer. A novel iterative algorithm is proposed to obtain the globally optimal solution of the considered non-convex optimization problem. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally by SDP relaxation. Simulation results demonstrate the significant gains in harvested power and the robustness against CSI imperfection for the proposed optimal resource allocation, compared to a baseline scheme designed for perfect CSI and the conventional linear energy harvesting model.

cs.IT↗