Asymptotic Distribution of System Capacity in Multiuser MIMO Systems with Large Number of Antennas

Jung, Minchae; Kim, Tae-Hyung; Min, Kyungsik; Kim, Younsun; Lee, Juho; Choi, Sooyong

doi:10.1109/vtcspring.2013.6692462

Cited by 17 publications

(17 citation statements)

References 10 publications

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“…While assuming component carrier (CC) bandwidth assigned to each UE is B CCs where CC is sufficient enough for K UEs. In line with study in [2,11,18], with K, M growing large with a constant ratio M/K, by an equal power allocation, achievable rate of UE k can be given by [2] R k = E B CCs log 2 1 + ρ…”

Section: The Transmission Rate Analysismentioning

confidence: 89%

“…Moreover, power of each antenna is equally assumed to be P a . By ignoring the inter-cluster interferences from the neighboring BS area [2,11], further take h k , a 1 × M complex-Gaussian vector with zeromean-complex-Gaussian entries, and variance 1 2 for each dimension, as the channel from BS to UE k [18]. While assuming component carrier (CC) bandwidth assigned to each UE is B CCs where CC is sufficient enough for K UEs.…”

Section: The Transmission Rate Analysismentioning

confidence: 99%

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Integrating energy efficiency analysis of massive MIMO-based C-RAN

Zhang

Tariq

Mumtaz

et al. 2016

J Wireless Com Network

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Besides the prior study of energy efficiency (EE) that focuses on single component (antenna, radio frequency (RF) chain, circuit, etc.), or limited to one base station (BS) area, in this paper, EE is integrated, investigated with various components (antenna, RF chain, circuit, coverage area) considering in, based on an optimized system model. That is, one optimized multi-BS system model is introduced beforehand with the cloud radio access network (C-RAN) for easier deployment of the selecting/sleeping mechanism. In addition, the system EE is described by an optimization problem while taking more component factors into consideration. While solving, this integrated optimization problem in all time intervals of all BS areas is proved to be equal to an optimization problem of each single BS area within each single time interval. After that, the integrated optimization solution is obtained while adding up the single-BS-singleinterval optimization solutions, whereas the later solution is addressed by an offline decision method plus a convex optimization strategy. Observation from the numerical results demonstrates that the antenna power consumption is the dominant factor of the power consumption, which therefore, the dominant factor of EE performance.

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Section: The Transmission Rate Analysismentioning

confidence: 89%

Section: The Transmission Rate Analysismentioning

confidence: 99%

Integrating energy efficiency analysis of massive MIMO-based C-RAN

Zhang

Tariq

Mumtaz

et al. 2016

J Wireless Com Network

View full text Add to dashboard Cite

show abstract

“…이러한 다 수의 공간 자원을 다수의 사용자에게 할당하는 다중 사용자 (multiuser) MIMO 시스템에 대한 연구 [4]- [8] 를 비롯하여 최근에는 다수의 기지국 안테나를 활용하는 massive MIMO 기술에 대한 연구가 5G 핵심 기술 중 하나로 활발히 연구되고 있다 [9][10][11][12][13][14][15][16][17] . Massive MIMO 시 스템은 다수의 기지국 안테나 특징을 활용한 배열 이 득(array gain)을 통해 커버리지 확대, 주파수 효율 및 링크 신뢰도를 향상시킬 수 있다 [9]- [10] .…”

Section: 무선 통신 환경에서 기존에 사용하던 시간 및 주파수 자원의 한계에 따라 고 전송률을 보장하기 위해 공간 자unclassified

“…Massive MIMO 시 스템은 다수의 기지국 안테나 특징을 활용한 배열 이 득(array gain)을 통해 커버리지 확대, 주파수 효율 및 링크 신뢰도를 향상시킬 수 있다 [9]- [10] . 하지만 다중 사 용자를 동시에 지원하는 다중 사용자 massive MIMO 시스템에서는 사용자 간 간섭 문제가 발생한다 [9]- [12] .…”

Section: 무선 통신 환경에서 기존에 사용하던 시간 및 주파수 자원의 한계에 따라 고 전송률을 보장하기 위해 공간 자unclassified

Optimal Numbers of Base Station Antennas and Users in Multiuser Massive MIMO Systems with Pilot Overhead

Jung¹,

Choi²

2016

The Journal of Korean Institute of Communications and Informati

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In this paper, we consider multiuser massive multiple-input and multiple-output (MIMO) system where multiusers simultaneously utilize massive antennas of base station (BS). With a downlink frame structure considering pilot signals, we derive the ergodic cell capacity based on zero-forcing beamforming (ZFBF) technique. This paper proves that the ergodic cell capacity is concave function with respect to the numbers of BS antennas and users, and derives the optimum numbers of BS antennas and users maximizing ergodic cell capacity. From the simulation results, it is shown that the derived numbers of BS antennas and users has the optimum value for the maximum ergodic cell capacity, and the ergodic cell capacity with the derived optimum values increases with respect to the transmit SNR(Signal to Noise Ratio).

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“…이러한 다수의 공간 자원 을 다수의 사용자들에게 할당하는 다중 사용자 (multiuser) MIMO 시스템은 최근 활발히 연구되고 있는 분야 중의 하나이다 [3][4][5][6][7] . 나아가 공간 자원을 최대한 활용하기 위해 다수의 기지국 안테나를 활 용하는 거대 안테나 시스템 (massive MIMO)이 차 세대 무선 통신 기술의 핵심 기술 중 하나로 주목 받고 있다 [8][9][10][11][12][13][14][15] .…”

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Optimal Number of Base Station Antennas and Users in MF Based Multiuser Massive MIMO Systems

Jung¹,

Choi²

2013

The Journal of Korea Information and Communications Society

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In this paper, we analyze a performance of multiuser massive multiple-input and multiple-output ( MIMO) system. We derive the ergodic cell capacity based on a downlink frame structure and analyze the ergodic cell capacity with respect to the number of base station (BS) antennas and the number of users. This paper shows that the ergodic cell capacity is a concave function with respect to the number of BS antennas and the number of users, and also derives the optimal numbers of BS antennas and users for the maximum cell capacity. The simulation results verify the derived analyses and show that the derived numbers of BS antennas and users provide the maximum cell capacity.

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Asymptotic Distribution of System Capacity in Multiuser MIMO Systems with Large Number of Antennas

Cited by 17 publications

References 10 publications

Integrating energy efficiency analysis of massive MIMO-based C-RAN

Integrating energy efficiency analysis of massive MIMO-based C-RAN

Optimal Numbers of Base Station Antennas and Users in Multiuser Massive MIMO Systems with Pilot Overhead

Optimal Number of Base Station Antennas and Users in MF Based Multiuser Massive MIMO Systems

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