Massive CSI acquisition in dense cloud-RAN with spatial and temporal prior information

Xuan Liu, Yuanming Shi, Jun Zhang, Khaled Letaief

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In this paper, we shall develop a generic channel estimation framework based on the convex formulation for dense cloud radio access networks (Cloud-RAN). Due to the training resource constraint and the large number of transmit antennas, the pilot length is smaller than the antenna number, and thus channel estimation becomes an ill-posed inverse problem. By observing that the wireless channel possesses ample exploitable statistical characteristics, we propose to convert the available spatial and temporal prior information into appropriate convex regularizing functions, yielding convex optimization formulations for the underdetermined channel estimation problem. Simulation results demonstrate that exploiting the prior information of large-scale fading and temporal correlation can achieve good estimation performance even with limited training resources. The alternating direction method of multipliers (ADMM) algorithm is further adopted to solve the resultant large-scale channel estimation problems. The proposed framework is, therefore, scalable to the overhead of prior information and the computation cost for large network sizes.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Communications, ICC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467389990
DOIs
Publication statusPublished - 28 Jul 2017
Externally publishedYes
Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
Duration: 21 May 201725 May 2017

Other

Other2017 IEEE International Conference on Communications, ICC 2017
CountryFrance
CityParis
Period21/5/1725/5/17

Fingerprint

Channel estimation
Antennas
Convex optimization
Inverse problems
Costs

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Cite this

Liu, X., Shi, Y., Zhang, J., & Letaief, K. (2017). Massive CSI acquisition in dense cloud-RAN with spatial and temporal prior information. In 2017 IEEE International Conference on Communications, ICC 2017 [7996916] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2017.7996916

Massive CSI acquisition in dense cloud-RAN with spatial and temporal prior information. / Liu, Xuan; Shi, Yuanming; Zhang, Jun; Letaief, Khaled.

2017 IEEE International Conference on Communications, ICC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7996916.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, X, Shi, Y, Zhang, J & Letaief, K 2017, Massive CSI acquisition in dense cloud-RAN with spatial and temporal prior information. in 2017 IEEE International Conference on Communications, ICC 2017., 7996916, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE International Conference on Communications, ICC 2017, Paris, France, 21/5/17. https://doi.org/10.1109/ICC.2017.7996916
Liu X, Shi Y, Zhang J, Letaief K. Massive CSI acquisition in dense cloud-RAN with spatial and temporal prior information. In 2017 IEEE International Conference on Communications, ICC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. 7996916 https://doi.org/10.1109/ICC.2017.7996916
Liu, Xuan ; Shi, Yuanming ; Zhang, Jun ; Letaief, Khaled. / Massive CSI acquisition in dense cloud-RAN with spatial and temporal prior information. 2017 IEEE International Conference on Communications, ICC 2017. Institute of Electrical and Electronics Engineers Inc., 2017.
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