Narrowband interference parameterization for sparse Bayesian recovery
KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Online Publication Date2015-09-11
Print Publication Date2015-06
Permanent link to this recordhttp://hdl.handle.net/10754/621281
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AbstractThis paper addresses the problem of narrowband interference (NBI) in SC-FDMA systems by using tools from compressed sensing and stochastic geometry. The proposed NBI cancellation scheme exploits the frequency domain sparsity of the unknown signal and adopts a Bayesian sparse recovery procedure. This is done by keeping a few randomly chosen sub-carriers data free to sense the NBI signal at the receiver. As Bayesian recovery requires knowledge of some NBI parameters (i.e., mean, variance and sparsity rate), we use tools from stochastic geometry to obtain analytical expressions for the required parameters. Our simulation results validate the analysis and depict suitability of the proposed recovery method for NBI mitigation. © 2015 IEEE.
CitationAli A, Elsawy H, Al-Naffouri TY, Alouini M-S (2015) Narrowband interference parameterization for sparse Bayesian recovery. 2015 IEEE International Conference on Communications (ICC). Available: http://dx.doi.org/10.1109/ICC.2015.7249036.
Conference/Event nameIEEE International Conference on Communications, ICC 2015