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Orthogonal Frequency Division Multiplexing (OFDM) is a technique that will prevail in the next generation wireless communication. Channel estimation is one of the key challenges in an OFDM system. In this paper, the authors formulate OFDM channel estimation as a compressive sensing problem, which takes advantage of the sparsity of the channel impulse response and reduces the number of probing measurements, which in turn reduces the ADC speed needed for channel estimation. Specifically, they propose sending out pilots with random phases in order to "Spread out" the sparse taps in the impulse response over the uniformly down-sampled measurements at the low speed receiver ADC, so that the impulse response can still be recovered by sparse optimization.
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