Spatially-Stationary Model for Holographic MIMO Small-Scale Fading

Pizzo, Andrea Del; Marzetta, Thomas L.; Sanguinetti, Luca

doi:10.1109/jsac.2020.3000877

Cited by 177 publications

(209 citation statements)

References 28 publications

Supporting

Mentioning

208

Contrasting

Unclassified

Order By: Relevance

“…In fact, the classical stochastic channel models do not well-reflect the physical properties of large arrays with a massive number of antennas in a compact space, not even in the far-field. A recent attempt to address this deficiency is [52], where a spatiallystationary model for the small-scale fading in the far-field of non-isotropic random scattering environments is developed on the basis of a Fourier plane-wave spectral representation. The proof proceeds in two steps.…”

Section: Discussionmentioning

confidence: 99%

“…The active arrays are essentially mMIMO transceivers but with many more antenna elements than what is considered in 5G (i.e., much more than 64). To make this clear, the research community has recently used new names to describe this category; for example, large intelligent surfaces [8], extremely large aperture arrays [9], and holographic MIMO [10]. However, in this paper, we will simply refer to it as mMIMO since asymptotically large arrays have been analyzed since the inception of mMIMO [3], [11], [12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces

Björnson

Sanguinetti

2020

IEEE Open J. Commun. Soc.

Self Cite

333

203

View full text Add to dashboard Cite

The use of large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements N when using Massive MIMO receivers and half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have recently attracted attention since these can relay signals to achieve an SNR that grows as N 2 , which seems like a major benefit. In this paper, we use a deterministic propagation model for a planar array of arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws, only apply in the far-field. They cannot be used to study the regime where N → ∞. We derive an exact channel gain expression that captures three essential near-field behaviors and use it to revisit the power scaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely to be approached in practice. We further prove that an IRS-aided setup cannot achieve a higher SNR than an equal-sized Massive MIMO setup, despite its faster SNR growth. We quantify analytically how much larger the IRS must be to achieve the same SNR. Finally, we show that an optimized IRS does not behave as an "anomalous" mirror but can vastly outperform that benchmark.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces

Björnson

Sanguinetti

2020

IEEE Open J. Commun. Soc.

Self Cite

333

203

View full text Add to dashboard Cite

show abstract

“…최근에는 초 다수 안테나를 활용한 통신 시스템 분석 및 빔포밍 기술이 활발히 연구되고 있다 [24] . 제한된 영역 에 초 다수의 안테나를 설치할 경우, 연속된 안테나로 근 사화된 개구면(aperture)의 신호 송수신 과정은 광학 홀로 그래픽 영상(optical holographic image) 신호의 수신 및 재 형성 과정으로 모델링된다 [25], [26] . 이에 전파의 기록 및 재 생을 위한 홀로그래픽 빔포밍 전송 기술이 연구되고 있 다 [27] .…”

Section: 표현은 다음과 같다unclassified

Beamforming Algorithms

Noh¹,

Chun²

2020

J. Korean Inst. Electromagn. Eng. Sci.

View full text Add to dashboard Cite

Beamforming techniques have become an integral part of the fifth-generation(5G) of mobile communication systems and continue to evolve for providing high spectral efficiency, spatial diversity, and beamforming gain in millimeter-wave and terahertz(THz) communication for future 6G networks. This paper presents a comprehensive overview of beamforming algorithms from statistical signal processing and optimization perspectives. The fundamentals of beamforming for wireless communication and several representative beamforming algorithms for single-stream and multi-stream transmission are discussed.

show abstract

“…F UTURISTIC 6G wireless technologies will supposedly accomplish the expectations not met with 5G. In infrastructure aspect, the key enablers of 6G are envisioned to be Reconfigurable Intelligent Surfaces (RIS), ultra-massive Multiple Input Multiple Output (MIMO) communications, and user-centric networking [1,2,3]. Currently, the research focus is on investigating the customization aspect of the wireless propagation environment [4,5].…”

Section: Introductionmentioning

confidence: 99%