Downlink spectral efficiency of multi-cell multi-user large-scale DAS with pilot contamination

Li, Jiamin; Wang, Dongming; Zhu, Pengcheng; You, Xiaohu

doi:10.1109/icc.2015.7248621

Cited by 9 publications

(7 citation statements)

References 19 publications

(21 reference statements)

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“…Considering minimum mean-square error (MMSE) channel estimator, the channel estimate of (1) with pilot contamination has been given in [22] bŷ…”

Section: B Channel Estimation With Pilot Contaminationmentioning

confidence: 99%

“…Note that [18] did not provide a general closed-form expression for (22), and in order to give analytical tractability, [19]- [23] all assumed average transmit power normalization instead of the per user power normalization considered in [18] which can provide user fairness. In the following theorems, considering per user power normalization, we derive the closed-form expressions for the lower bound (22) with MRT and ZF beamforming in distributed massive MIMO systems.…”

Section: Lower Bound On Ergodic Achievable Ratementioning

confidence: 99%

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Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Wang

Zhu

et al. 2018

IEEE Trans. Veh. Technol.

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Abstract-In this paper, the downlink spectral efficiency of multi-cell multi-user distributed massive MIMO systems with linear beamforming is studied in the presence of pilot contamination. According to the levels of effective channel gain information at user side, we provide the lower bound and upper bound on user ergodic achievable downlink rate. Due to the different access distance from each user to different remote antenna units, the entries of user channel vectors are no longer identically distributed in distributed massive MIMO systems, which makes the spectral efficiency analysis challenging. Using the properties of Gamma distributions together with the approximate methods for non-isotropic vectors, we derive tractable but accurate closed-form expressions for the rate bounds with maximum ratio transmission (MRT) and zero-forcing (ZF) beamforming in distributed massive MIMO systems. Based on these expressions, user ultimate achievable rates are also given when the ratio of the total number of transmit antennas to the number of users goes to infinity. It is shown that MRT and ZF beamforming achieve the same ultimate rate no matter what levels of effective channel gain information at user side. Numerical results show that ZF achieves better performance gain and faster convergence speed than MRT. When the coherence interval is large, the downlink beamforming training scheme is more preferable for the distributed massive MIMO systems.

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“…Considering minimum mean-square error (MMSE) channel estimator, the channel estimate of (1) with pilot contamination has been given in [22] bŷ…”

Section: B Channel Estimation With Pilot Contaminationmentioning

confidence: 99%

Section: Lower Bound On Ergodic Achievable Ratementioning

confidence: 99%

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Wang

Zhu

et al. 2018

IEEE Trans. Veh. Technol.

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“…A large scale distributed antenna system can achieve considerable performance gain compared with a co-located massive MIMO system with the same number of antennas. Thus, DAS can mitigate largescale fading which is a path loss using the many antennas distributed geographically [22]. Assuming channel reciprocity, the downlink of distributed massive MIMO system is considered to be operating in TDD mode.…”

Section: System Modelmentioning

confidence: 99%

Efficient Antenna Selection Strategy for a Massive Mimo Downlink System

Shiney¹,

Ganesan²,

Asis³

2020

PIER M

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This paper focuses on an efficient antenna selection strategy for a distributed massive MIMO system. The objective of the proposed algorithm is to attain ergodic achievable rate as much as possible with antenna selection in a constrained capacity limited system. In this proposed work, the initial selection of antenna set is based on channel amplitude and correlation which then follows an iterative approach in order to select the best subset of transmit antenna elements from the overall antenna set. The proposed scheme significantly outperforms, in terms of ergodic rate with low complexity, the prevailing transmit antenna selection methods. Simulation results show that the performance of the proposed antenna selection method is close to select all transmission with a minimum throughput loss. Thus the proposed method is best suited for a large scale distributed Massive MIMO system without degradation in system performance and is of low computational complexity.

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“…average power normalization instead of per user power normalization (20)) was assumed in [37][38][39][40][41] to give analytical tractability, where v l,l,k =ĝ l,l,k or f l,l,k . Figure 1 shows the difference in performance between the two power normalization schemes.…”

Section: Downlink Signal Model and Achievable Ratesmentioning

confidence: 99%

Impacts of practical channel impairments on the downlink spectral efficiency of large-scale distributed antenna systems

Wang

Zhu

et al. 2018

Sci. China Inf. Sci.

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An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications SCIENCE CHINA Information Sciences 59, 081301 (2016); Distributed antenna systems: resource allocation and energy efficiency optimization}{Distributed antenna systems: resource allocation and energy efficiency optimization SCIENTIA SINICA Informationis 47, 591 (2017); An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications SCIENTIA SINICA Informationis 46, 3 (2016); Numerical experimental study on the potential climatic impacts of large-scale wind farms in China Advances in Climate Change Research 10, 143 (2019); SCIENCE CHINA Information Sciences

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Downlink spectral efficiency of multi-cell multi-user large-scale DAS with pilot contamination

Cited by 9 publications

References 19 publications

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Downlink Spectral Efficiency of Distributed Massive MIMO Systems With Linear Beamforming Under Pilot Contamination

Efficient Antenna Selection Strategy for a Massive Mimo Downlink System

Impacts of practical channel impairments on the downlink spectral efficiency of large-scale distributed antenna systems

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