In this paper, we study a multi-pair two-way half-duplex decode-and-forward (DF) massive multiple-input multiple-output (MIMO) relaying system, in which multiple single-antenna user pairs can exchange information through a massive MIMO relay. For low-complexity transmission, zeroforcing reception/zero-forcing transmission (ZFR/ZFT) is employed at the relay. First, we analytically study the large-scale approximations of the sum spectral efficiency (SE). Furthermore, we focus on three specific power scaling laws to study the tradeoff between the transmit powers of each pilot symbol, each user and the relay, and also focus on how the transmit powers scale with the number of relay antennas, M, to maintain a finite SE performance. Additionally, we consider a practical power consumption model to investigate the energy efficiency (EE), and illustrate the impact of M and the interplay between the power scaling laws and the EE performance. Finally, we consider the system fairness via maximizing the minimum achievable SE among all user pairs. Index Terms-Decode-and-forward relaying, half-duplex, massive MIMO, Max-min fairness, power scaling laws, spectral efficiency and energy efficiency, zero-forcing.
We propose a low-complexity approach for the downlink of physically constrained massive multiple-input multiple-output (MIMO) systems with user mobility. We examine a channel state information (CSI) acquisition strategy that exploits both the spatial and temporal correlations among the channels of adjacent base station antennas. The proposed strategy solely collects CSI for a subset of antennas and time frames. Then full CSI is approximated using the CSI of adjacent antennas and previous frames. This critically reduces the CSI acquisition complexity while sacrificing the CSI quality and, hence, introduces a scalable performancecomplexity tradeoff. The numerical results demonstrate that, for practical mobile speeds, the proposed scheme reduces the computational complexity and enhances the energy efficiency of massive MIMO base stations against systems with complete CSI, while approximately preserving performance.
In article number 2200155, Yan, Qian, Xi, and co-workers obtained the deep spinal cord (SC) vascular structure and achieved fast monitoring of indocyanine-green-labeled red blood cells up to 100 fps by NIR-II fluorescent microscopy, which exhibits the great potential of NIR-II window on SC imaging. The imaging research on SC vasculature is crucial, yet the high scattering tissue greatly affects the improvement of microscopic imaging depth.
In this paper, we study a multi-pair two-way large-scale multiple-input multiple-output (MIMO) decode-and-forward relay system. Multiple single-antenna user pairs exchange information via a shared relay working at half-duplex. The proposed scenario considers a practical case where an increasing number of antennas is deployed in a fixed physical space, giving rise to a trade-off between antenna gain and spatial correlation. The channel is assumed imperfectly known, and the relay employs linear processing methods. We study the large-scale approximations of the sum spectral efficiency (SE) and investigate the energy efficiency (EE) with a practical power consumption model when the number of relay antennas becomes large. We demonstrate the impact of the relay antenna number and spatial correlation with reducing inter-antenna distance on the EE performance. We exploit the increasing spatial correlation to allow an incomplete channel state information (CSI) acquisition where explicit CSI is acquired only for a subset of antennas. Our analytical derivations and numerical results show that applying the incomplete CSI strategy in the proposed system can improve the EE against complete CSI systems while maintaining the average SE performance.
In this paper, we consider a physically constrained multi-pair two-way massive multiple-input multipleoutput (MIMO) decode-and-forward (DF) half-duplex relay system, where multiple single-antenna user pairs exchange information through a massive MIMO relay, and we employ zeroforcing reception/zero-forcing transmission (ZFR/ZFT) at the relay. When the number of relay antennas M becomes very large and tends to be infinite, we study the large-scale approximation of the sum spectral e ciency (SE) with the e↵ect of spatial correlation generated by the constrained space. Furthermore, we investigate the energy e ciency (EE) with a practical power consumption model, and demonstrate the impact of the relay antenna number and the size of constrained space on the EE performance. Index Terms-Decode-and-forward relaying, massive MIMO, spatial correlation, spectral e ciency and energy e ciency, zero forcing processing.
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