An experimental study on Power Amplifier linearisation by artificial neural networks Yapay Sinir Aǧlari ile Güç Yükselteç Doǧrusalląstirma Amaçli Deneysel Bir Çalisma

Yesil, Soner
Kolagasioglu, Ahmet Ertugrul
Yılmaz, Ali Özgür
This paper represents an experimental study on the linearisation of Power Amplifiers especially on high output power regions by utilizing an artificial neural network structure and open-loop training method. For the same in-band output power, 9dB EVM and 6dB ACLR improvement has been observed on hardware by feeding the proposed digital predistortion signal (DPD) to the PA under test.


Joint Mitigation of IQ Imbalance and Power Amplifier Impairments by Real Valued Time Delay Neural Networks
Yeşil, Soner; Gürtunca, Burak; Yılmaz, Ali Özgür (2019-08-22)
This paper represents a neural network based joint mitigation of the IQ imbalance and power amplifier nonlinearities that cause degradation in the transmit signal quality of the wireless communication systems. A Real Valued Time Delay Neural Network architecture for this purpose has been verified on a hardware including cascaded NXP-MD8IC925 and NXPBLF8G10LS power amplifier components performing a total of 46dB gain. The test setup has been controlled over MATLAB in order to have a closed loop adaptive digi...
Development of a tuner topology for multiharmonic matching and implementation on tunable dual band power amplifier design
Kılıç, Hasan Hüseyin; Demir, Şimşek; Department of Electrical and Electronics Engineering (2018)
In this thesis work, the effect of multi-harmonic load matching on improving the efficiency of power amplifiers is investigated. Techniques of efficient power amplifier design are discussed and analyzed in terms of multi-harmonic matching. Several circuit topologies are evaluated for multi-harmonic matching by discussing the advantages and the limitations. Specifically, a detailed multi-harmonic analysis of the triple stub topology is presented. The already-known single frequency impedance matching capabili...
An SRWNN-based approach on developing a self-learning and self-evolving adaptive control system for motion platforms
Ari, Evrim Onur; Kocaoglan, Erol (2016-02-01)
In this paper, a self-recurrent wavelet neural network (SRWNN)-based indirect adaptive control architecture is modified for performing speed control of a motion platform. The transient behaviour of the original learning algorithm has been improved by modifying the learning rate updates. The contribution of the proposed modification has been verified via both simulations and experiments. Moreover, the performance of the proposed architecture is compared with robust RST designs performed on a similar benchmar...
Thermal imaging based on mechanical vibrations
Yılmaz, Şener; Azgın, Kıvanç; Department of Mechanical Engineering (2022-8-19)
The thesis proposes a digital, resonance readout method based on a lock-in based digital phase locked loop (DPLL) mechanism, which is designed, simulated, implemented and tested using a Xilinx made Field Programmable Gate Array (FPGA). Implementation is performed using a hardware descriptive language (VHDL) on low level. Certain digital signal processing algorithms such as lock-in detection, DPLL, DDS and CORDIC are implemented, simulated and tested. Moreover, the design is shown to be capable of resonating...
Linearization of RF power amplifiers with memoryless baseband predistortion method
Kolcuoğlu, Turusan; Demir, Şimşek; Department of Electrical and Electronics Engineering (2011)
In modern wireless communication systems, advanced modulation techniques are used to support more users by handling high data rates and to increase the utilization efficiency of the limited RF spectrum. These techniques are sensitive to the nonlinear distortions due to their high peak to average power ratios. Main source of nonlinear distortion in transmitter topologies are power amplifiers that determine the overall efficiency and linearity of the transmitter. To increase linearity without sacrificing effi...
Citation Formats
S. Yesil, A. E. Kolagasioglu, and A. Ö. Yılmaz, “An experimental study on Power Amplifier linearisation by artificial neural networks Yapay Sinir Aǧlari ile Güç Yükselteç Doǧrusalląstirma Amaçli Deneysel Bir Çalisma,” 2018, Accessed: 00, 2020. [Online]. Available: