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Two-stage time-domain pilot contamination elimination in large-scale multiple-antenna aided and TDD based OFDM systems

Two-stage time-domain pilot contamination elimination in large-scale multiple-antenna aided and TDD based OFDM systems
Two-stage time-domain pilot contamination elimination in large-scale multiple-antenna aided and TDD based OFDM systems
Pilot contamination (PC) is a major impediment of large-scale multi-cell multiple-input multiple-output (MIMO) systems. Hence we propose an optimal pilot design for timedomain channel estimation, which is capable of completely eliminating PC. More specifically, a sophisticated combination of downlink training and ‘scheduled’ uplink training is designed with the aid of the optimal pilot set. Given the optimal pilot set, every user acquires its unique downlink time-domain channel state information (CSI) through downlink training. The estimated downlink CSIs are then embedded in the uplink training. As a result, PC can be completely eliminated, at the cost of a slight increase in training computational complexity. Our simulation results demonstrate the power of the proposed scheme. Most significantly, our scheme imposes a modest training overhead of (L + 3), training-phase durations corresponding to the number of OFDM symbols, where L is the number of cells, which is substantially lower than that imposed by some of the existing PC elimination schemes. Therefore, it imposes a less stringent requirement on the channel’s coherence time. Finally, our scheme does not need any information exchange between base stations.
8629-8641
Guo, Xinying
941af9ec-ae51-4dd1-a3eb-85a2dc4058be
Zhang, Jiankang
6add829f-d955-40ca-8214-27a039defc8a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Mu, Xiaomin
3d578909-36ba-4b16-b703-2ef63532116c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Guo, Xinying
941af9ec-ae51-4dd1-a3eb-85a2dc4058be
Zhang, Jiankang
6add829f-d955-40ca-8214-27a039defc8a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Mu, Xiaomin
3d578909-36ba-4b16-b703-2ef63532116c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Guo, Xinying, Zhang, Jiankang, Chen, Sheng, Mu, Xiaomin and Hanzo, Lajos (2017) Two-stage time-domain pilot contamination elimination in large-scale multiple-antenna aided and TDD based OFDM systems. IEEE Access, 5, 8629-8641. (doi:10.1109/ACCESS.2016.2604202).

Record type: Article

Abstract

Pilot contamination (PC) is a major impediment of large-scale multi-cell multiple-input multiple-output (MIMO) systems. Hence we propose an optimal pilot design for timedomain channel estimation, which is capable of completely eliminating PC. More specifically, a sophisticated combination of downlink training and ‘scheduled’ uplink training is designed with the aid of the optimal pilot set. Given the optimal pilot set, every user acquires its unique downlink time-domain channel state information (CSI) through downlink training. The estimated downlink CSIs are then embedded in the uplink training. As a result, PC can be completely eliminated, at the cost of a slight increase in training computational complexity. Our simulation results demonstrate the power of the proposed scheme. Most significantly, our scheme imposes a modest training overhead of (L + 3), training-phase durations corresponding to the number of OFDM symbols, where L is the number of cells, which is substantially lower than that imposed by some of the existing PC elimination schemes. Therefore, it imposes a less stringent requirement on the channel’s coherence time. Finally, our scheme does not need any information exchange between base stations.

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More information

Accepted/In Press date: 15 August 2016
e-pub ahead of print date: 30 August 2016
Published date: 23 May 2017
Organisations: Comms, Signal Processing & Control

Identifiers

Local EPrints ID: 402862
URI: http://eprints.soton.ac.uk/id/eprint/402862
PURE UUID: 4a06df88-3955-4584-8025-3e92ff4179ba
ORCID for Jiankang Zhang: ORCID iD orcid.org/0000-0001-5316-1711
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 16 Nov 2016 16:03
Last modified: 07 Oct 2020 04:16

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