Sparse symbol detection by a greedy tree search

In this paper, we consider a detection problem of the underdetermined system when the input vector is sparse and its elements are chosen from a set of finite alphabets. We propose a greedy sparse recovery algorithm dubbed as the sparse detection matching pursuit (SDMP) that is effective in recovering the sparse signals with integer constraint. In our performance guarantee analysis and empirical simulations, we show that SDMP is effective in recovering sparse signals in both noiseless and noisy scenarios.