Can Hardware Distortion Correlation be Neglected when Analyzing Uplink SE in Massive MIMO?

Björnson, Emil; Sanguinetti, Luca; Hoydis, Jakob

doi:10.1109/spawc.2018.8446008

Cited by 5 publications

(9 citation statements)

References 13 publications

(49 reference statements)

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“…We solve the non-convex problem in (33) approximately in two steps. First, we find the precoding matrix that maximizes the sum rate under a per-antenna power constraint, namely, we maximize R sum (P) subject to (32).…”

Section: Energy-efficient Distortion-aware Precodingmentioning

confidence: 99%

Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

Aghdam¹,

Jacobsson²,

Gustavsson³

et al. 2020

Preprint

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We introduce a framework for linear precoder design over a massive multiple-input multipleoutput downlink system and in presence of nonlinear power amplifiers (PAs). By studying the spatial characteristics of the distortion, we demonstrate that conventional linear precoding techniques steer nonlinear distortions in the direction of the users. We show that, by taking into account PA nonlinearity characteristics, one can design linear precoders that reduce, and in single-user scenarios, even remove completely the distortion transmitted in the direction of the users. This, however, is achieved at the price of a considerably reduced array gain. To address this issue, we present precoder optimization algorithms which simultaneously take into account the effects of array gain, distortion, multiuser interference, and receiver noise. Specifically, we derive an expression for the achievable sum rate and propose an iterative algorithm that attempts to find the precoding matrix maximizing this expression. Moreover, using a model for PA power consumption, we propose an algorithm that attempts to find the precoding matrix minimizing the consumed power for a given minimum achievable sum rate. Our numerical results demonstrate that the proposed distortion-aware precoding techniques yield considerable improvements in terms of spectral and energy efficiency compared to conventional linear precoding techniques.

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Section: Energy-efficient Distortion-aware Precodingmentioning

confidence: 99%

Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

Aghdam¹,

Jacobsson²,

Gustavsson³

et al. 2020

Preprint

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“…For tractable analysis, a simple but accurate diagonal approximation method is utilized, where the quantization distortion is modeled as a white process, both in space and time, by assuming that the off-diagonal elements of C d are zeros [5], [13]. Thus, the diagonal approximation C diag d of C d can be expressed as [14].…”

Section: Diagonal Approximationmentioning

confidence: 99%

“…where , respectively. Note that [13], which implies that the elements on the diagonal of C d in (24) are exact.…”

Section: Diagonal Approximationmentioning

confidence: 99%

Quantized Polar Transmitters for Power Efficient Massive MIMO Systems

Lampu

Kosunen

et al. 2021

IEEE Wireless Commun. Lett.

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“…caused by nonideal hardware as power-dependent additive white Gaussian noise. While such simple statistical models have been shown to yield accurate results in some scenarios when characterizing bit error rate (BER) and spectral efficiency [7]- [9], they do not fully capture the impact of real-world hardware impairments on practical systems [9], [10]. Indeed, nonideal hardware causes distortion that is, in general, correlated in time, frequency, and across the BS antenna array [10]- [13].…”

Section: A Previous Workmentioning

confidence: 99%

Massive MU-MIMO-OFDM Uplink with Hardware Impairments: Modeling and Analysis

Jacobsson

Gustavsson

Durisi

et al. 2018

2018 52nd Asilomar Conference on Signals, Systems, and Computers

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We study the impact of hardware impairments at the base station (BS) of an orthogonal frequency-division multiplexing (OFDM)-based massive multiuser (MU) multiple-input multipleoutput (MIMO) uplink system. We leverage Bussgang's theorem to develop accurate models for the distortions caused by nonlinear low-noise amplifiers, local oscillators with phase noise, and oversampling finite-resolution analog-to-digital converters. By combining the individual effects of these hardware models, we obtain a composite model for the BS-side distortion caused by nonideal hardware that takes into account its inherent correlation in time, frequency, and across antennas. We use this composite model to analyze the impact of BS-side hardware impairments on the performance of realistic massive MU-MIMO-OFDM uplink systems.

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Can Hardware Distortion Correlation be Neglected when Analyzing Uplink SE in Massive MIMO?

Cited by 5 publications

References 13 publications

Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

Quantized Polar Transmitters for Power Efficient Massive MIMO Systems

Massive MU-MIMO-OFDM Uplink with Hardware Impairments: Modeling and Analysis

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