Exact(1)
In Fig. 4, the frame error rate (FER) of the proposed scheme is compared to those obtained by the approximate message-passing decoding algorithms presented in [14, 18].
Similar(59)
The approximate message passing (AMP) algorithm, designed for compressed sensing, has attracted researchers to counter this problem due to its reduced complexity with a large system limit.
The channel marginal probability density function is expressed by using the general approximate message-passing algorithm.
And all of the parameters needed for EM update are computed by the general approximate message passing (GAMP) [9, 10] algorithm, which provides a huge gain in reducing the computational complexity.
Our algorithm is inspired by the complex approximate message passing algorithm (CAMP) that solves complex-valued LASSO.
A residual is computed in line 8. Above points subsume the Bayesian approximate message passing (BAMP) [21 23] iteration that is executed for all N B blocks.
While many recovery algorithms aiming at solving (1) for x have been proposed in literature [18, 19], we utilize the versatile approximate message passing (AMP) framework that was introduced in [21 23].
We employ the Bayesian structured signal approximate message passing (BASSAMP) algorithm [15] in order to exploit the joint sparsity.
Moreover, a fast decoding method is developed and tested by comparing the obtained results with both the uncoded system performance and two approximate message passing (AMP) algorithms.
Finally, the works [14, 16 18] take into account approximate message passing decoding algorithms.
To close this section, we recall an algorithm in [10] for the recovery of signals based on generalized approximate message passing (GAMP).
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