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

被引:256
作者
Bjornson, Emil [1 ]
Sanguinetti, Luca [2 ]
机构
[1] Linkoping Univ, Dept Elect Engn ISY, S-58183 Linkoping, Sweden
[2] Univ Pisa, Dipartimento Ingn Informaz, I-56122 Pisa, Italy
来源
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY | 2020年 / 1卷 / 01期
关键词
Intelligent reflecting surface; reconfigurable intelligent surface; software-controlled metasurface; massive MIMO; regenerative MIMO relays; asymptotic limits; power scaling law; near-field; far-field; WIRELESS NETWORK; TRANSMISSION; CAPACITY; ENERGY; MODEL;
D O I
10.1109/OJCOMS.2020.3020925
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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 article, 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 -> 8. 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.
引用
收藏
页码:1306 / 1324
页数:19
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