A low-rank approach for interference management in dense wireless networks

Kai Yang, Yuanming Shi, Jun Zhang, Zhi Ding, Khaled Letaief

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

Abstract

The curse of big data, propelled by the explosive growth of mobile devices, places overwhelming pressures on wireless communications. Network densification is a promising approach to improve the area spectral efficiency, but to acquire massive channel state information (CSI) for effective interference management becomes a formidable task. In this paper, we propose a novel interference management method which only requires the network connectivity information, i.e., the knowledge of the presence of strong links, and statistical information of the weak links. To acquire such mixed network connectivity information incurs significant less overhead than complete CSI, and thus this method is scalable to large network sizes. To maximize the sum-rate with the mixed network connectivity information, we formulate a rank minimization problem to cancel strong interference and suppress weak interference, which is then solved by a Riemannian trust-region algorithm. Such algorithm is robust to initial points and has a fast convergence rate. Simulation result shows that our approach achieves a higher data rate than the state-of-the-art methods.

Original languageEnglish
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages708-712
Number of pages5
ISBN (Electronic)9781509045457
DOIs
Publication statusPublished - 19 Apr 2017
Externally publishedYes
Event2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States
Duration: 7 Dec 20169 Dec 2016

Other

Other2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
CountryUnited States
CityWashington
Period7/12/169/12/16

Fingerprint

Channel state information
Wireless networks
Densification
Mobile devices
Communication
Big data

Keywords

  • Capacity
  • Interference leakage
  • Riemannian optimization
  • Sum-rate
  • Topological interference management

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Yang, K., Shi, Y., Zhang, J., Ding, Z., & Letaief, K. (2017). A low-rank approach for interference management in dense wireless networks. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings (pp. 708-712). [7905934] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2016.7905934

A low-rank approach for interference management in dense wireless networks. / Yang, Kai; Shi, Yuanming; Zhang, Jun; Ding, Zhi; Letaief, Khaled.

2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 708-712 7905934.

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

Yang, K, Shi, Y, Zhang, J, Ding, Z & Letaief, K 2017, A low-rank approach for interference management in dense wireless networks. in 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings., 7905934, Institute of Electrical and Electronics Engineers Inc., pp. 708-712, 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016, Washington, United States, 7/12/16. https://doi.org/10.1109/GlobalSIP.2016.7905934
Yang K, Shi Y, Zhang J, Ding Z, Letaief K. A low-rank approach for interference management in dense wireless networks. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 708-712. 7905934 https://doi.org/10.1109/GlobalSIP.2016.7905934
Yang, Kai ; Shi, Yuanming ; Zhang, Jun ; Ding, Zhi ; Letaief, Khaled. / A low-rank approach for interference management in dense wireless networks. 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 708-712
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