Enabling polarisation filtering in wireless communications: models, algorithms and characteristics

Bin Cao; Jia Yu; Ye Wang; Qinyu Zhang

Enabling polarisation filtering in wireless communications: models, algorithms and characteristics

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Author(s): Bin Cao ¹ ; Jia Yu ¹ ; Ye Wang ¹ ; Qinyu Zhang ¹
- Affiliations: 1: Communication Engineering Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, Guangdong 518055, People's Republic of China
Source: Volume 7, Issue 3, 12 February 2013, p. 247 – 254
DOI: 10.1049/iet-com.2012.0409 , Print ISSN 1751-8628, Online ISSN 1751-8636

Received 13/07/2012, Accepted 10/11/2012, Revised 14/10/2012, Published

To suppress co-channel interference in polarisation-enabled wireless communication systems, this work aims to provide an interference suppression scheme by exploiting polarisation domain, besides the state-of-the-art temporal, frequency, spatial and code domains. System models, algorithms, characteristics and applications of polarisation filtering (PF) for co-channel interference suppressions for polarisation-enabled (e.g. orthogonal dually polarised antennas) wireless communications are investigated. Specifically, four system models for PF using subspace analysis are established and discussed. The four proposed system models are categorised based on different statistic characteristics of the target signal and that of the interfering signal: both the target signal and interference are temporal deterministic, the target signal is deterministic whereas interference is temporal random, the target signal is random whereas interference is deterministic and both the target signal and interference are random, respectively. Based on the statistic characteristics and subspace theory, the detailed PF implementation for each model is analysed and the closed-form filtering operator is given. It is also shown that the PF implementation for each model can be attained by using one of the zero-forcing matched subspace processing, decorrelating matched subspace processing or Wiener subspace processing. Furthermore, relationship among these four models indicates that, under certain conditions, the implementation of the other three models can be fulfilled by using the implementation of the first model. Numerical and simulation results show the effectiveness of the proposed scheme.

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Enabling polarisation filtering in wireless communications: models, algorithms and characteristics

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