On the impact of hardware impairments on massive MIMO

Gustavsson, Ulf; Sánchez-Pérez, César; Eriksson, Thomas; Athley, Fredrik; Durisi, Giuseppe; Landin, Per N.; Hausmair, Katharina; Fager, Christian; Svensson, Lars

doi:10.1109/glocomw.2014.7063447

Cited by 103 publications

(117 citation statements)

References 14 publications

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“…Based on this model, it was concluded that massive MU-MIMO exhibits a certain degree of robustness against hardware impairments. While the underlying Gaussian impairment model was demonstrated to be accurate for a diverse set of residual RF impairments [5], [6], this model is a poor match for coarse quantization, which causes deterministic distortions that areby nature-dependent on the transmit signal.…”

Section: B Relevant Prior Artmentioning

confidence: 99%

“…5 This holds provided that the priors are product distributions, i.e., that f (h) = W w=1 f (hw) and that p(s) = W w=1 p(sw). 6 Our framework enables also the use of multi-antenna user equipments. In this case, forward error correction and channel decoding can be performed over the multiple antennas.…”

Section: A Quantized Mimo-ofdm System Modelmentioning

confidence: 99%

“…The system model is depicted in Fig. 1 and consists of U independent single-antenna users 6 communicating with a BS having B ≥ U receive antennas. We consider a frame-based OFDM transmission, where each OFDM symbol consists of W tones, similar to what is used in IEEE 802.11n [45].…”

Section: A Quantized Mimo-ofdm System Modelmentioning

confidence: 99%

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Quantized Massive MU-MIMO-OFDM Uplink

Studer

Durisi

2016

IEEE Trans. Commun.

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231

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Abstract-Coarse quantization at the base station (BS) of a massive multi-user (MU) multiple-input multiple-output (MIMO) wireless system promises significant power and cost savings. Coarse quantization also enables significant reductions of the raw analog-to-digital converter (ADC) data that must be transferred from a spatially-separated antenna array to the baseband processing unit. The theoretical limits as well as practical transceiver algorithms for such quantized MU-MIMO systems operating over frequency-flat, narrowband channels have been studied extensively. However, the practically relevant scenario where such communication systems operate over frequency-selective, wideband channels is less well understood. This paper investigates the uplink performance of a quantized massive MU-MIMO system that deploys orthogonal frequency-division multiplexing (OFDM) for wideband communication. We propose new algorithms for quantized maximum a-posteriori (MAP) channel estimation and data detection, and we study the associated performance/quantization trade-offs. Our results demonstrate that coarse quantization (e.g., four to six bits, depending on the ratio between the number of BS antennas and the number of users) in massive MU-MIMO-OFDM systems entails virtually no performance loss compared to the infinite-precision case at no additional cost in terms of baseband processing complexity.Index Terms-Analog-to-digital conversion, convex optimization, forward-backward splitting (FBS), frequency-selective channels, massive multi-user multiple-input multiple-output (MU-MIMO), maximum a-posteriori (MAP) channel estimation, minimum mean-square error (MMSE) data detection, orthogonal frequency-division multiplexing (OFDM), quantization.

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Section: B Relevant Prior Artmentioning

confidence: 99%

Section: A Quantized Mimo-ofdm System Modelmentioning

confidence: 99%

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Quantized Massive MU-MIMO-OFDM Uplink

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Durisi

2016

IEEE Trans. Commun.

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“…It was shown that the total power efficiency of the transmitter in the LSAS regime is significantly higher than the total power efficiency in classical design. In [35], authors examined the effects of hardware impairments on a LSAS single-cell system. The simulations were performed using simplified, well-established statistical hardware impairment models as well as more sophisticated and realistic models based upon measurements and electromagnetic antenna array simulations.…”

Section: Rf Componentmentioning

confidence: 99%

“…There are several studies related to the RF component of LSAS [34][35][36]. In [34], a novel single-RF LSAS transmitter was presented.…”

Section: Rf Componentmentioning

confidence: 99%

Energy Efficiency Gain of Cellular Base Stations with Large-Scale Antenna Systems for Green Information and Communication Technology

Lee

2017

Sustainability

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Due to the ever-increasing data demand of end users, the number of information and communication technology (ICT)-related devices and equipment continues to increase. This induces large amounts of heat emissions, which can cause serious environmental pollution. In recent times, signal transmission systems such as cellular base stations (BSs) have been constructed everywhere and these emit a large carbon footprint. Large-scale antenna systems (LSASs) that use a large amount of transmission antennas to serve a limited number of users can increase energy efficiency (EE) of BSs based on the beamforming effect, and thus can be a promising candidate to reduce the carbon footprint of the ICT field. In this paper, we discuss the necessary schemes to realize LSASs and show the expected EE gain of the LSAS with enough practicality. There are many obstacles to realize the high EE LSAS, and even though several studies have shown separate schemes to increase the EE and/or throughput (TP) of LSASs, few have shown combinations of schemes, and presented how much EE gain can be achieved by the schemes in the overall system. Based on the analysis in this paper, we believe more detailed work for the realization of high energy efficient BSs with LSASs is possible because this paper shows the necessary schemes and the maximum achievable energy efficiency gain as a reference. Extensive analysis and simulation results show that with proper implementation of the power amplifier/RF module and a robust channel estimation scheme, LSASs with 600 transmitter (TX) antennas can achieve 99.4 times more EE gain compared to the current systems, thereby resulting in significant reduction of carbon footprints.

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