Base Station Selection Algorithm for Distributed Massive MIMO System over Rician Fading Channels

LI Yongzhi; TAO Cheng; LIU Liu; LU Yanping; LIU Kai

doi:10.11999/JEIT150811

Volume 38 Issue 4

Apr. 2016

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LI Yongzhi, TAO Cheng, LIU Liu, LU Yanping, LIU Kai. Base Station Selection Algorithm for Distributed Massive MIMO System over Rician Fading Channels[J]. Journal of Electronics & Information Technology, 2016, 38(4): 856-862. doi: 10.11999/JEIT150811

Citation:

LI Yongzhi, TAO Cheng, LIU Liu, LU Yanping, LIU Kai. Base Station Selection Algorithm for Distributed Massive MIMO System over Rician Fading Channels[J]. Journal of Electronics & Information Technology, 2016, 38(4): 856-862. doi: 10.11999/JEIT150811

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Base Station Selection Algorithm for Distributed Massive MIMO System over Rician Fading Channels

doi: 10.11999/JEIT150811

1.
(Institute of Broadband Wireless Mobile Communications, Beijing Jiaotong University, Beijing 100044, China)
2.

Funds:

The National 863 Project of China (2014AA01A706), Beijing Science and Technology Talents Program (2016023), Fundamental Research Funds for the Central Universities (2015JBM011), The National Natural Science Foundation of China (61471027), The Research Fund of National Mobile Communications Research Laboratory, Southeast University (2014D05), Beijing Natural Science Foundation Project (4152043)

Received Date: 2015-07-08
Rev Recd Date: 2015-12-11
Publish Date: 2016-04-19

Abstract

Abstract

The Base Station (BS) selection for distributed massive MIMO system is studied. The channels between the BSs and the users are assumed to be Rician fading. First the closed-form expressions of downlink achievable rates for Matched-Filter (MF) and Zero-Forcing (ZF) precoding are derived respectively, and the power efficiency performance of the system is investigated. Based on the closed-form expressions, the approximate incremental BS selection and the approximate user priority BS selection algorithms are proposed, both of which only require the statistical Channel State Information (CSI), to maximize the system spectral efficiency. Numerical results show that the proposed algorithms perform close to the optimal one. Specifically, it is shown that the approximate user priority BS selection algorithm outperforms the approximate incremental one when the BSs utilize the MF precoding in the large scale antenna limit.
- Massive MIMO,
- Distributed,
- Rician fading channel,
- Base Station (BS) selection,
- Spectral efficiency

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References(24)

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