access icon free Iterative sparse channel estimation and demodulation for blind equalisation

The authors formulate a blind equalisation problem minimising the residual that is difference between the received signal and the predicted signal. Since both channel impulse responses and transmitted symbols are unknown, the authors regard the problem as a kind of dictionary learning problem. The authors divide the problem into two sub-problems and iteratively find the channel impulse response and the demodulated symbols. Since the wireless channels with a large bandwidth tend to have a sparse multipath structure, the authors apply the compressive sensing technique to the channel estimation sub-problem. Numerical results show that the proposed algorithm achieves the Genie-aided lower-bound performance.

Inspec keywords: transient response; demodulation; blind equalisers; channel estimation; iterative methods; wireless channels

Other keywords: dictionary learning problem; channel estimation subproblem; demodulation; predicted signal; sparse multipath structure; residual minimization; compressive sensing technique; transmitted symbols; wireless channels; iterative sparse channel estimation; blind equalisation problem; Genie-aided lower-bound performance; channel impulse responses; received signal; demodulated symbols

Subjects: Modulation and coding methods; Communication channel equalisation and identification; Interpolation and function approximation (numerical analysis); Radio links and equipment

References

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http://iet.metastore.ingenta.com/content/journals/10.1049/el.2017.2917
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