WebLab: A Web-Based Setup for PA Digital Predistortion and Characterization [Application Notes]

Landin, Per N.; Gustafsson, Sebastian; Fager, Christian; Eriksson, Thomas

doi:10.1109/mmm.2014.2367857

Cited by 57 publications

(19 citation statements)

References 1 publication

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“…We set b m1 = 1 and b m2 = −0.03491 + j0.005650 (extracted through linear regression from measurements on the class AB amplifier that can be run from [16]), for all m, and made the amplifier operate at its 1 dB-compression point. As pulse shaping filter, we chose a root-raised cosine with rolloff 0.22, as in LTE [1], which gives the normalized bandwidth BT = 1.22.…”

Section: A Assumptions Of the Numerical Analysismentioning

confidence: 99%

Out-of-band radiation measure for MIMO arrays with beamformed transmission

Mollén¹,

Gustavsson²,

Eriksson³

et al. 2016

2016 IEEE International Conference on Communications (ICC)

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The spatial characteristics of the out-of-band radiation that a multiuser MIMO system emits in the environment, due to its power amplifiers (modeled by a polynomial model) are nonlinear, is studied by deriving an analytical expression for the continuous-time cross-correlation of the transmit signals. At a random spatial point, the same power is received at any frequency on average with a MIMO base station as with a SISO base station when the two radiate the same amount of power. For a specific channel realization however, the received power depends on the channel. We show that the power received outof-band only deviates little from the average in a MIMO system with multiple users and that the deviation can be significant with only one user. Using an ergodicity argument, we conclude that out-of-band radiation is less of a problem in massive MIMO, where total radiated power is lower compared to SISO systems and that requirements on spectral regrowth can be relaxed in MIMO systems without causing more total out-of-band radiation.Index Terms-ACLR, massive MIMO, MIMO, nonlinearity, outof-band radiation, power amplifier, spectral regrowth.

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Section: A Assumptions Of the Numerical Analysismentioning

confidence: 99%

Out-of-band radiation measure for MIMO arrays with beamformed transmission

Mollén¹,

Gustavsson²,

Eriksson³

et al. 2016

2016 IEEE International Conference on Communications (ICC)

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“…In our simulation setup, we assume that all base station antennas are equipped with identical PAs whose nonlinearity characteristics are modeled by ( 2 ) with

, and

. These coefficients have been obtained by linear regression on measurements over the class AB amplifier performed using [ 23 ]. The maximum output power at each antenna is

dBm, and the maximum power efficiency of the PAs is

for

[ 7 ].…”

Section: Numerical Resultsmentioning

confidence: 99%

Low Spatial Peak-to-Average Power Ratio Transmission for Improved Energy Efficiency in Massive MIMO Systems

Aghdam

Eriksson

2021

Sensors

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A significant portion of the operating power of a base station is consumed by power amplifiers (PAs). Much of this power is dissipated in the form of heat, as the overall efficiency of currently deployed PAs is typically very low. This is because the structure of conventional precoding techniques typically results in a relatively high variation in output power at different antennas in the array, and many PAs are operated well below saturation to avoid distortion of the transmitted signals. In this work, we use a realistic model for power consumption in PAs and study the impact of power variation across antennas in the array on the energy efficiency of a massive MIMO downlink system. We introduce a family of linear precoding matrices that allow us to control the spatial peak-to-average power ratio by projecting a fraction of the transmitted power onto the null space of the channel. These precoding matrices preserve the structure of conventional precoders; e.g., they suppress multiuser interference when used together with zeroforcing precoding and bring advantages over these precoders by operating PAs in a more power-efficient region and reducing the total radiated distortion. Our numerical results show that by controlling the power variations between antennas in the array and incorporating the nonlinearity properties of PA into the precoder optimization, significant gains in energy efficiency can be achieved over conventional precoding techniques.

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“…The measurement setup is based on the RF WebLab [34], which can be remotely accessed at www.dpdcompetition.com. Its block diagram is shown in Fig.…”

Section: A Setup 1) Measurement Setupmentioning

confidence: 99%

Low Complexity Joint Impairment Mitigation of I/Q Modulator and PA Using Neural Networks

Gustavsson

Amat

et al. 2021

Preprint

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Neural networks (NNs) for multiple hardware impairments mitigation of a realistic direct conversion transmitter are impractical due to high computational complexity. We propose two methods to reduce complexity without significant performance penalty. We first propose a novel attention residual learning NN, referred to as attention residual real-valued time-delay neural network (ARDEN), where trainable neuronwise shortcut connections between the input and output layers allow to keep the attention always active. Furthermore, we implement a NN pruning algorithm that gradually removes connections corresponding to minimal weight magnitudes in each layer. Simulation and experimental results show that ARDEN with pruning achieves better performance for compensating frequency-dependent quadrature imbalance and power amplifier nonlinearity than other NN-based and Volterra-based models, while requiring less or similar complexity.

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WebLab: A Web-Based Setup for PA Digital Predistortion and Characterization [Application Notes]

Cited by 57 publications

References 1 publication

Out-of-band radiation measure for MIMO arrays with beamformed transmission

Out-of-band radiation measure for MIMO arrays with beamformed transmission

Low Spatial Peak-to-Average Power Ratio Transmission for Improved Energy Efficiency in Massive MIMO Systems

Low Complexity Joint Impairment Mitigation of I/Q Modulator and PA Using Neural Networks

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