The University of Southampton
University of Southampton Institutional Repository

Location-based channel estimation and pilot assignment for massive MIMO systems

Location-based channel estimation and pilot assignment for massive MIMO systems
Location-based channel estimation and pilot assignment for massive MIMO systems
In this paper, a location-based channel estimation algorithm is proposed for massive multi-input multi-output (MIMO) systems. By utilizing the property of the steering vector, a fast Fourier transform (FFT)-based post-processing is introduced after the conventional pilot-aided channel estimation. Under the condition that different users with the same pilot sequence have non-overlapping angle-of-arrivals (AOAs), the proposed channel estimation algorithm is capable of distinguishing these users effectively. To cooperate with the location-based channel estimation, a pilot assignment algorithm is also proposed to ensure that the users in different cells using the same pilot sequence have different
AOAs at base station. The simulation results demonstrate that the proposed scheme can reduce the inter-cell interference caused by the reuse of the pilot sequence and thus improves the overall system performance significantly.
1-5
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Qian, Chen
2b85263f-c5ae-413e-a0d3-4c3abd84ff61
Dai, Linglong
a3b9a8e1-777f-4196-a388-969444c7239d
Chen, Jinhui
ba3e7e76-75cb-4ce3-8f75-de0e9b4b5e02
Sun, Chen
73141893-cc41-415d-ab99-4f9f9822c90b
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Wang, Zhaocheng
70339538-3970-4094-bcfc-1b5111dfd8b4
Qian, Chen
2b85263f-c5ae-413e-a0d3-4c3abd84ff61
Dai, Linglong
a3b9a8e1-777f-4196-a388-969444c7239d
Chen, Jinhui
ba3e7e76-75cb-4ce3-8f75-de0e9b4b5e02
Sun, Chen
73141893-cc41-415d-ab99-4f9f9822c90b
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Wang, Zhaocheng, Qian, Chen, Dai, Linglong, Chen, Jinhui, Sun, Chen and Chen, Sheng (2015) Location-based channel estimation and pilot assignment for massive MIMO systems. ICC2015, Workshop on 5G & Beyond - Enabling Technologies and Applications, London, United Kingdom. 08 - 12 Jun 2015. pp. 1-5 . (doi:10.1109/ICCW.2015.7247351).

Record type: Conference or Workshop Item (Paper)

Abstract

In this paper, a location-based channel estimation algorithm is proposed for massive multi-input multi-output (MIMO) systems. By utilizing the property of the steering vector, a fast Fourier transform (FFT)-based post-processing is introduced after the conventional pilot-aided channel estimation. Under the condition that different users with the same pilot sequence have non-overlapping angle-of-arrivals (AOAs), the proposed channel estimation algorithm is capable of distinguishing these users effectively. To cooperate with the location-based channel estimation, a pilot assignment algorithm is also proposed to ensure that the users in different cells using the same pilot sequence have different
AOAs at base station. The simulation results demonstrate that the proposed scheme can reduce the inter-cell interference caused by the reuse of the pilot sequence and thus improves the overall system performance significantly.

Text
icc2015-w23.pdf - Other
Download (115kB)

More information

Published date: June 2015
Venue - Dates: ICC2015, Workshop on 5G & Beyond - Enabling Technologies and Applications, London, United Kingdom, 2015-06-08 - 2015-06-12
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 377031
URI: http://eprints.soton.ac.uk/id/eprint/377031
PURE UUID: 4f67a90e-3785-41b1-8cc4-5c23a45e4506

Catalogue record

Date deposited: 14 May 2015 10:37
Last modified: 14 Mar 2024 19:54

Export record

Altmetrics

Contributors

Author: Zhaocheng Wang
Author: Chen Qian
Author: Linglong Dai
Author: Jinhui Chen
Author: Chen Sun
Author: Sheng Chen

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×