关键词: 稀疏信道, 压缩感知, 子空间追踪, 信道估计

Abstract: Due to the sparse structure of channels in a number of communication systems, the sparse channel estimation problem can be formulated as the reconstruction problem of sparse signals, and then being solved by certain algorithm in Compressive Sensing (CS) theory. To avoid needing prior knowledge for sparseness, a Modified Subspace Pursuit (MSP) was proposed. The feedback and refining processes of MSP are the same as those of the existing Subspace Pursuit (SP), the difference between them is that, in MSP, the number of vectors added to the candidate set is increased one by one, not equal to the number of sparseness in SP in every iteration. The simulation results show that, compared with the existing subspace pursuit method, the main innovative feature of the proposed algorithm is that it does not need to assume the sparseness of channel but offers superior estimation resolution.

Key words: sparse channel, Compressive Sensing (CS), subspace pursuit, channel estimation