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Characterization of Volterra Kernels for RF Power Amplifiers Using a Two-Tone Signal and a Large-Signal
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.ORCID iD: 0000-0003-2061-6366
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences, Electronics.ORCID iD: 0000-0003-2887-049x
Department of information science and engineering Royal Institute of Technology (KTH), Stockholm, Sweden.ORCID iD: 0000-0002-2718-0262
2018 (English)In: 2018 International Conference on Communications, COMM 2018 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, Vol. 1, p. 351-356Conference paper, Published paper (Refereed)
Abstract [en]

The 3rd-order Volterra kernels of a radio frequency (RF) power amplifier (PA) are characterized using a large-signal and a two-tone probing-signal. In this technique, the magnitude and phase asymmetries of the kernels of the PA excited by the probing-signal are analyzed in different amplitude regions of the large-signal. The device under test is a class-AB PA operating at 2.14 GHz. The maximum sweeping frequency space of the probing-signal is 20 MHz. The results indicate that the Volterra kernels of the PA show different behaviors (frequency dependency and asymmetry) in different regions.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 1, p. 351-356
Keywords [en]
Kernel, Radio frequency, Baseband, Nonlinear systems, Frequency dependence, Frequency-domain analysis, Discrete Fourier transforms, nonlinear dynamic RF power amplifier, volterra kernels, asymmetry, two-tone test
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Intelligent Industry
Identifiers
URN: urn:nbn:se:hig:diva-27867DOI: 10.1109/ICComm.2018.8430119ISI: 000449526000066Scopus ID: 2-s2.0-85052507435ISBN: 978-1-5386-2351-0 (print)ISBN: 978-1-5386-2350-3 (electronic)ISBN: 978-1-5386-2349-7 (print)OAI: oai:DiVA.org:hig-27867DiVA, id: diva2:1246028
Conference
2018 International Conference on Communications (COMM), 14-16 June 2018, Bucharest, Romania
Available from: 2018-09-06 Created: 2018-09-06 Last updated: 2022-10-31Bibliographically approved
In thesis
1. Characterisation, Modelling and Digital Pre-Distortion Techniques for RF Transmitters in Wireless Systems
Open this publication in new window or tab >>Characterisation, Modelling and Digital Pre-Distortion Techniques for RF Transmitters in Wireless Systems
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wireless systems have become an inevitable part of modern technologies serving humankind. The rapid growth towards large dimensional systems, e.g. 5th generation (5G) technologies, incurs needs for improving the performance of the systems and considering aspects to make them as far as possible environmentally friendly in terms of power efficiency, cost, and so on. One of the key parts of every wireless communication system is the radio frequency (RF) power amplifier (PA), which consumes the largest percentage of the total energy. Hence, accurate models of RF PAs can be used to optimize their design and to compensate for signal distortions. This thesis starts with two methods for frequency-domain characterisation to analyse the dynamic behaviour of PAs in 3rd-order non-linear systems. Firstly, two-tone signals superimposed on large-signals are used to analyse the frequency-domain symmetry properties of inter-modulation (IM) distortions and Volterra kernels in different dynamic regions of RF PAs in a single-input single-output (SISO) system. Secondly, three-tone signals are used to characterise the 3rd-order self- and cross-Volterra kernels of RF PAs in a 3 × 3 multiple-input multiple-output (MIMO) system. The main block structures of the models are determined by analysing the frequency-domain symmetry properties of the Volterra kernels in different three-dimensional (3D) frequency spaces. This approach significantly simplifies the structure of the 3rd-order non-linear MIMO model.

The following parts of the thesis investigate techniques for behavioural modelling and linearising RF PAs. A piece-wise modelling technique is proposed to characterise the dynamic behaviour and to mitigate the impairments of non-linear RF PAs at different operating points (regions). A set of thresholds decompose the input signal into several sub-signals that drive the RF PAs at different operating points. At each operating point, the PAs are modelled by one sub-model, and hence, the complete model consists of several sub-models. The proposed technique reduces the model errors compared to conventional piece-wise modelling techniques.

A block structure modelling technique is proposed for RF PAs in a MIMO system based on the results of the three-tone characterisation technique. The main structures of the 3rd- and higher-order systems are formulated based on the frequency dependence of each block. Hence, the model can describe more relevant interconnections between the inputs and outputs than conventional polynomial-type models.

This thesis studies the behavioural modelling and compensation techniques in both the time and the frequency domains for RF PAs in a 3 × 3MIMO system. The 3D time-domain technique is an extension of conventional 2D generalised memory polynomial (GMP) techniques. To reduce the computational complexity, a frequency-domain technique is proposed that is efficient and feasible for systems with long memory effects. In this technique, the parameters of the model are estimated within narrow sub-bands. Each sub-band requires only a few parameters, and hence the size of the model for each sub-band is reduced.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. p. 73
Series
TRITA-EECS-AVL ; ; 2019:9
Keywords
RF power amplifiers, non-linearity, memory effects, Behavioral modelling, MIMO, Digital pre-distortion
National Category
Signal Processing Telecommunications
Research subject
Intelligent Industry
Identifiers
urn:nbn:se:hig:diva-29302 (URN)978-91-7873-076-6 (ISBN)
Public defence
2019-02-18, Hörsal 99131, Kungsbäcksvägen 47, Gävle, 13:00 (English)
Opponent
Supervisors
Available from: 2019-02-18 Created: 2019-02-18 Last updated: 2022-10-31Bibliographically approved

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Alizadeh, MahmoudRönnow, DanielHändel, Peter

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