arXiv subjects

Alberto Brihuega

Publications and source records attributed to Alberto Brihuega.

9 recordsLinked to original sources

arXiv2021

HybridDeepRx: Deep Learning Receiver for High-EVM Signals

In this paper, we propose a machine learning (ML) based physical layer receiver solution for demodulating OFDM signals that are subject to a high level of nonlinear distortion. Specifically, a novel deep learning based convolutional neural network receiver is devised, containing layers in both time- and frequency domains, allowing to demodulate and decode the transmitted bits reliably despite the high error vector magnitude (EVM) in the transmit signal. Extensive set of numerical results is provided, in the context of 5G NR uplink incorporating also measured terminal power amplifier characteristics. The obtained results show that the proposed receiver system is able to clearly outperform classical linear receivers as well as existing ML receiver approaches, especially when the EVM is high in comparison with modulation order. The proposed ML receiver can thus facilitate pushing the terminal power amplifier (PA) systems deeper into saturation, and thereon improve the terminal power-efficiency, radiated power and network coverage.

eess.SP↗

arXiv2020

Gradient-Adaptive Spline-Interpolated LUT Methods for Low-Complexity Digital Predistortion

In this paper, new digital predistortion (DPD) solutions for power amplifier (PA) linearization are proposed, with particular emphasis on reduced processing complexity in future 5G and beyond wideband radio systems. The first proposed method, referred to as the spline-based Hammerstein (SPH) approach, builds on complex spline-interpolated lookup table (LUT) followed by a linear finite impulse response (FIR) filter. The second proposed method, the spline-based memory polynomial (SMP) approach, contains multiple parallel complex spline-interpolated LUTs together with an input delay line such that more versatile memory modeling can be achieved. For both structures, gradient-based learning algorithms are derived to efficiently estimate the LUT control points and other related DPD parameters. Large set of experimental results are provided, with specific focus on 5G New Radio (NR) systems, showing successful linearization of multiple sub-6 GHz PA samples as well as a 28 GHz active antenna array, incorporating channel bandwidths up to 200 MHz. Explicit performance-complexity comparisons are also reported between the SPH and SMP DPD systems and the widely-applied ordinary memory-polynomial (MP) DPD solution. The results show that the linearization capabilities of the proposed methods are very close to that of the ordinary MP DPD, particularly with the proposed SMP approach, while having substantially lower processing complexity.

eess.SP↗

arXiv2020

Digital Predistortion for Multiuser Hybrid MIMO at mmWaves

Efficient mitigation of power amplifier (PA) nonlinear distortion in multi-user hybrid precoding based broadband mmWave systems is an open research problem. In this article, we first carry out detailed signal and distortion modeling in broadband multi-user hybrid MIMO systems, with a bank of nonlinear PAs in each subarray, while also take the inevitable crosstalk between the antenna/PA branches into account. Building on the derived models, we then propose an efficient closed-loop (CL) digital predistortion (DPD) solution that requires only a single-input DPD unit per transmit chain or subarray, despite crosstalk, providing substantial complexity-benefit compared to the state-of-the art multi-dimensional DPD solutions. We show that under spatially correlated multipath propagation, each DPD unit can provide linearization towards every intended user, or more generally, towards all spatial directions where coherent propagation is taking place, and that the proposed CL DPD system is robust against crosstalk}. Extensive numerical results building on practical measurement-based mmWave PA models are provided, demonstrating and verifying the excellent linearization performance of the proposed DPD system in different evaluation scenarios.

eess.SP↗

arXiv2020

Piecewise Digital Predistortion fo mmWave Active Antenna Arrays: Algorithms and Measurements

In this paper, we describe a novel framework for digital predistortion (DPD) based linearization of strongly nonlinear millimeter-wave active antenna arrays. Specifically, we formulate a piecewise (PW) closed-loop (CL) DPD solution and low-complexity gradient-adaptive parameter learning algorithms, together with a region partitioning method, that can efficiently handle deep compression of the PA units. The impact of beamsteering on the DPD performance is studied, showing strong beam-dependence, thus necessitating frequent updating of the DPD. In order to facilitate fast adaptation, an inexpensive, non-iterative, pruning algorithm is introduced, which allows to significantly reduce the amount of model coefficients. The proposed methods are validated with extensive over-the-air RF measurements on a 64-element active antenna array transmitter operating at 28 GHz carrier frequency and transmitting a 400 MHz 5G New Radio (NR) standard-compliant orthogonal frequency division multiplexing waveform. The obtained results demonstrate the excellent linearization capabilities of the proposed solution, conforming to the new 5G NR requirements for frequency range 2 (FR2) in terms of both inband waveform quality and out-of-band emissions. The proposed PW-CL DPD is shown to outperform the state-of-the-art PW DPD based on the indirect learning architecture, as well as the classical single-polynomial based DPD solutions in terms of linearization performance and computational complexity by a clear margin.

eess.SP↗

arXiv2019

On Antenna Array Out-of-Band Emissions

We substantiate and extend recent research on the behavior of the out-of-band emissions in antenna array transmitters. Specifically, with multi-user precoding, we show that the emissions are always beamformed in the directions of the intended receivers, contrary to some claims in the recent literature. Moreover, while also other spurious directions exist, we show that the emissions are always strongest in the directions of the intended receivers. We also show that power amplifiers with mutually different nonlinear phase characteristics will reduce the beamforming gain of the unwanted emissions, with the gain approaching the noncoherent combining limit as the phase deviations are increased.

eess.SP↗

arXiv2019

Linearizing Active Antenna Arrays: Method and Measurements

In this paper, we provide a novel framework for efficient digital predistortion (DPD) based linearization of active antenna arrays with multiple and mutually different nonlinear power amplifiers. The proposed method builds on the use of a combined feedback signal essentially characterizing the observable nonlinear distortion at the receiving end. The proposed method is validated with extensive over-the-air RF measurements on a 64-element active antenna array transmitter operating at 28 GHz carrier frequency and transmitting a 200 MHz wide 5G New Radio (NR) waveform. The obtained results demonstrate the excellent linearization capabilities of the proposed solution, which allows for a very efficient implementation in practical systems.

eess.SP↗

arXiv2018

Digital Predistortion in Large-Array Digital Beamforming Transmitters

In this article, we propose a novel digital predistortion (DPD) solution that allows to considerably reduce the complexity resulting from linearizing a set of power amplifiers (PAs) in single-user large-scale digital beamforming transmitters. In contrast to current state-of-the art solutions that assume a dedicated DPD per power amplifier, which is unfeasible in the context of large antenna arrays, the proposed solution only requires a single DPD in order to linearize an arbitrary number of power amplifiers. To this end, the proposed DPD predistorts the signal at the input of the digital precoder based on minimizing the nonlinear distortion of the combined signal at the intended receiver direction. This is a desirable feature, since the resulting emissions in other directions get partially diluted due to less coherent superposition. With this approach, only a single DPD is required, yielding great complexity and energy savings.

eess.SP↗

arXiv2018

Performance Comparison of Constant Envelope and Zero-forcing Precoders in Multiuser Massive MIMO

In this article, the adoption and performance of a constant envelope (CE) type spatial precoder is addressed in large-scale multiuser MIMO based cellular network. We first formulate an efficient computing solution to obtain the antenna samples of such CE precoder. We then evaluate the achievable CE precoder based multiuser downlink (DL) system performance and compare it with the corresponding performance of more ordinary zero-forcing (ZF) spatial precoder. We specifically also analyze how realistic highly nonlinear power amplifiers (PAs) affect the achievable DL performance, as the individual PA units in large-array or massive MIMO systems are expected to be small, cheap and operating close to saturation for increased energy-efficiency purposes. It is shown that the largely reduced peak-to-average power ratio (PAPR) of the PA input signals in the CE precoder based system allows for pushing the PA units harsher towards saturation, while allowing to reach higher signal-to-interference-plus-noise ratio (SINRs) at the intended receivers compared to the classical ZF precoder based system. The obtained results indicate that the CE precoder can outperform the ZF precoder by up to 5-6 dBs, in terms of the achievable SINRs, when the PA units are pushed towards their saturating region. Such large gains are a substantial benefit when seeking to improve the spectral and energy-efficiencies of the mobile cellular networks.

eess.SP↗

arXiv2018

Digital Predistortion for Hybrid MIMO Transmitters

This article investigates digital predistortion (DPD) linearization of hybrid beamforming large-scale antenna transmitters. We propose a novel DPD processing and learning technique for an antenna sub-array, which utilizes a combined signal of the individual power amplifier (PA) outputs in conjunction with a decorrelation-based learning rule. In effect, the proposed approach results in minimizing the nonlinear distortions in the direction of the intended receiver. This feature is highly desirable, since emissions in other directions are naturally weak due to beamforming. The proposed parameter learning technique requires only a single observation receiver, and therefore supports simple hardware implementation. It is also shown to clearly outperform the current state-of-the-art technique which utilizes only a single PA for learning. Analysis of the feedback network amplitude and phase imbalances reveals that the technique is robust even to high levels of such imbalances. Finally, we also show that the array system out-of-band emissions are well-behaving in all spatial directions, and essentially below those of the corresponding single-antenna transmitter, due to the combined effects of the DPD and beamforming.

eess.SP↗