On the performance of iterative receivers in massive MIMO systems with pilot contamination

Huang, Yuqi; Tang, Wenrui; Wei, Hao; Li, Jiamin; Wang, Dongming; Su, Xin

doi:10.1109/iciea.2014.6931130

Cited by 5 publications

(6 citation statements)

References 13 publications

(20 reference statements)

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“…In fact, due to the duality of the uplink and downlink, the mechanisms of both uplink and downlink transmission methods are very similar. For instance, in [71] and [72], a polynomial expansion based precoding and a polynomial expansion based iterative receiver were proposed for massive MIMO to simplify matrix inversion, respectively. In order to exploit the sparsity of LSAS, belief propagation (BP) was extended to downlink precoding [73] and iterative detection [14].…”

Section: Transmission Methods Of Multi-user Lsasmentioning

confidence: 99%

“…In [77] a joint channel estimation and data detection algorithm with message passing was proposed by exploiting the channel hardening effect of massive MIMO. To overcome the complexity of the detection, recently, some researchers have studied large dimensional MIMO detection include simplified matrix inversion [72] [76] and sparsity-based detection [14] [78].…”

Section: Low-complexity Receiversmentioning

confidence: 99%

“…In [72], a turbo receiver has been proposed for massive MIMO. The iterative receiver consists of channel estimation, interference estimation, low-complexity soft-input soft-output (SISO) detection and decoding .…”

Section: Low-complexity Receiversmentioning

confidence: 99%

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An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

WANG¹,

YOU²,

Yu³

et al. 2015

Sci. Sin.-Inf.

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To meet the future demand for huge traffic volume of wireless data service, the research on the fifth generation (5G) mobile communication systems has been undertaken in recent years. It is expected that the spectral and energy efficiencies in 5G mobile communication systems should be ten-fold higher than the ones in the fourth generation (4G) mobile communication systems. Therefore, it is important to further exploit the potential of spatial multiplexing of multiple antennas. In the last twenty years, multiple-input multiple-output (MIMO) antenna techniques have been considered as the key techniques to increase the capacity of wireless communication systems. When a large-scale antenna array (which is also called massive MIMO) is equipped in a base-station, or a large number of distributed antennas (which is also called large-scale distributed MIMO) are deployed, the spectral and energy efficiencies can be further improved by using spatial domain multiple access. This paper provides an overview of massive MIMO and large-scale distributed MIMO systems, including spectral efficiency analysis, channel state information (CSI) acquisition, wireless transmission technology, and resource allocation. Index TermsThe fifth generation mobile communication, massive MIMO, large-scale distributed antenna systems, spectral efficiency, channel state information acquisition, multi-user MIMO, resource allocation.

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Section: Transmission Methods Of Multi-user Lsasmentioning

confidence: 99%

Section: Low-complexity Receiversmentioning

confidence: 99%

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An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

WANG¹,

YOU²,

Yu³

et al. 2015

Sci. Sin.-Inf.

Self Cite

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“…Authors in [19] proposed a channel estimation scheme for a massive MIMO which does not require the knowledge of the inter-cell large fading coefficient, thus no overload. An iterative soft decision IC has been investigated in multi-cell multi-user massive MIMO with pilot contamination [20] where only the MMSE was considered. Authors in [21] designed a pilot contamination pre-coding which maximizes the minimum SINR subject to the network sum power constraint for interference reduction.…”

Section: A Related Researchmentioning

confidence: 99%

Interference Management in LTE-Advanced Cooperative Relay Networks: Decentralized Transceiver Design With Channel Estimation

2019

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Wireless networks improve indoor communications by deploying femtocell networks into the macrocell coverage. This results in spectrum sharing with the consequences of cross-tier interference from the macrocell user equipment (MUEs) to the femtocell access points (FAPs). This work considers the uplink cross-tier interference management for the cell-edge MUEs (CUEs) in cooperative multi-user multiple input multiple output (MU-MIMO) systems. For better interference management, the CUEs are grouped into clusters and communicate to the macrocell base station (MBS) through a relay node (RN). The linear pre-coders and decoders algorithms for the FAPs, MUEs and CUEs are proposed for effective interference management to minimize the sum mean square error (MSE), subject to the total transmit power constraints. The designed pre-coders and decoders use the pilot-assisted channel estimation to improve the accuracy of the acquired channel state information (CSI). The least-square (LS) and minimum MSE (MMSE) channel estimators are considered. The performance of the system is investigated in terms of the bit error rate (BER) for the linear pre-coders and decoders algorithms with the pilot-assisted channel estimators.INDEX TERMS Channel estimation, decentralized transceiver, femtocells, long term evolution-advanced, relay node, uplink communication. FAMBIRAI TAKAWIRA (M'96) received the B.Sc. degree (Hons.

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“…In [8], a multistage receiver was designed with the help of MMSE and interference cancellation method. Furthermore, in [9] the low density soft iterative multi-user through multi user detection (MUD) and MMSE detector was discussed.…”

Section: Introductionmentioning

confidence: 99%

Evolution of Diversity Gain with and without Coding Gain in MIMO for Emerging Wireless Networks

Kaimkhani¹,

Chen²,

Yin³

2017

IJCTE

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The wireless networks are growing rapidly that cause constraint in data rate and power consumption. The multiple-input multiple-output (MIMO) has incredible performance to overcome the limitations by spatial multiplexing gain. Spatial multiplexing gain is achieved with the help of space time encoding technique in which a high rate signal splitting into multiple lower rate streams and transmitting them through the different antennas. This paper provides a comprehensive comparative study of diversity gain with and without coding gain for 4 × 2 and 4 × 4 MIMO systems. The coding gain is explored through turbo coding (TC) with ½ and ¾ coding rates, and diversity gain is adopted by orthogonal space time coding (OSTBC). Turbo coding is useful to reduce the forward error correction in multiplexed data transmissions. The compounding of OSTBC and turbo coding is valuables to increase data rate and reduce energy consumption by reducing bit error rate in emerging wireless network transmissions. Simulation results convinced the validity of proposed scheme. He has a bachelor degree in electronics engineering from Sir Syed University of Engineering and Technology, Karachi, Pakistan and master's degree in computer and communication networks from Telecom & Management SudParis (ex INT), Evry, France. He has worked as a lecturer and the head of the Network Department from 2007 to 2009 at Universities of Engineering Science and Technology of Pakistan (UESTP-France), Karachi, Pakistan and also work as an assistant professor from 2009 to 2011 at COMSATS Institute of information Technology, Abbottabad, Pakistan. His main research areas include, MIMO, beamforming, WiMax over GSM/GPRS network, physical layer of wireless network, energy efficient wireless network.Zhe Chen received his B.S degree in electronics engineering, the M.S degree in signal and information processing, and the PhD. degree in signal and information processing from Dalian university of Technology (DUT), Dalian, China, in 1996, 1999 and 2003 respectively. He joined the Department of electronics Engineering, DUT, as a lecturer in 2002, and become an associate professor in 2006. His research includes speech processing, image processing and wideband wireless communication. Fuliang Yin was born in Fushun city, Liaoning province, China, in 1962. He received the B.S. degree in electronic engineering and M.S. degree in communications and electronic systems from Dalian University of Technology (DUT), Dalian, China, in 1984 and 1987, respectively. He

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On the performance of iterative receivers in massive MIMO systems with pilot contamination

Cited by 5 publications

References 13 publications

An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications

Interference Management in LTE-Advanced Cooperative Relay Networks: Decentralized Transceiver Design With Channel Estimation

Evolution of Diversity Gain with and without Coding Gain in MIMO for Emerging Wireless Networks

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