2014 Fiscal Year Annual Research Report
Compressive channel estimation techniques for narrowband or wideband communications systems
| Project/Area Number |
26889050
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| Research Institution | Akita Prefectural University |
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Principal Investigator |
桂 冠 秋田県立大学, システム科学技術学部, 特任助教 (80734904)
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| Project Period (FY) |
2014-08-29 – 2016-03-31
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| Keywords | 先端的通信 / 圧縮センシング / 情報通信工学 / 圧縮チャネル推定 / スパース適応チャネル推定 / スパース適応フィルタ / 非ガウス雑音 |
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| Outline of Annual Research Achievements |
Regarding the characterization and discretization of sparse D-scale channels, discrete channel model were studied under two typical noise environments, Gaussian noise and non-Gaussian impulsive noise.
In the scenario of Gaussian noise environment, we proposed compressive sensing based sparse channel estimation techniques and Bayesian sparse channel estimation techniques to mitigate the noise as well as to exploit channel sparsity and/to cluster sparsity. Corresponding results have been published in international journals and conferences.
In the scenario of non-Gaussian noise environment, we have proposed adaptive sparse channel estimation techniques to mitigate the impulsive noise and to exploit channel sparsity. Theoretical analysis of the proposed techniques was derived and simulations were conduced to confirm the effectiveness of the proposed algorithms. Corresponding results have been published in international journals and conferences.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
According to our research plan, we have proposed two kinds of identification techniques, i.e. compressive channel estimation and sparse adaptive filtering channel estimation for accurate D-scale channel model. Corresponding research results have been published including 5 international journal papers and 8 international conference papers.
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| Strategy for Future Research Activity |
Based on our proposed techniques, data transmission over the estimate channel will be evaluated. To achieve the above purpose, our research implementation plan is divided into following three stages: 1) Modulation and demodulation. We will devise modulation and demodulation techniques that enable efficient channel equalization and, more generally, efficient transceivers for sparse D-scale channels. 2) Compressive channel estimation techniques. We will investigate equalization-based coherent detection within the D-scale MC systems. 3) Performance analysis. Extensive numerical simulations (in Maple/MATLAB) will be used to experimentally evaluate the performance of the developed compressive channel estimation techniques under practically relevant operating conditions.
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