Abstract
In the grant-free massive machine-type communication (mMTC) scenario, a key challenge is the joint device activity detection and data decoding. The sporadic nature of mMTC makes compressed sensing a promising solution to the activity detection problem. However, the typical two-phase coherent transmission scheme, which divides channel training and data decoding into two separate phases, suffers performance losses, especially when only a few bits of data are transmitted by each active device. This paper follows a newly proposed non-coherent transmission scheme in which the data bits are embedded in the pilot sequences and the BS simultaneously detects active devices and decodes the embedded data bits without explicit channel estimation. To exploit statistical channel information and the specific structure of the sparsity pattern introduced by the non-coherent transmission scheme, i.e., only one row in each section can be non-zero, we propose a receiving method based on the approximate message passing (AMP) algorithm with non-separable minimum mean-squared error denoisers specifically designed for the problem. The corresponding state evolution equations, which can be used to predict the section error rate (SER) performance, is obtained and simplified under certain assumptions. We also derive closed-form expressions of the SER performance based on the state evolution results. Finally, numerical simulations are given to validate the accuracy of the performance analysis and to show the superiority of the proposed receiving method over the conventional method based on AMP with separable denoisers in the literature.
Highlights
(1) To exploit the statistical channel information and the special correlation structure of the sparsity pattern incurred by the non-coherent transmission structure, i.e., only one row in each section can be non-zero, we propose a receiving method based on the approximate message passing (AMP) algorithm with a section-wise minimum mean square error (MMSE) denoiser
Y, which is the matched filter output of the received signal with the corresponding pilot sequences. We summarize this consequence in the following proposition without a formal proof Proposition 1: For the joint device activity detection and embedded data bit decoding problem (7) with fixed number of embedded data bits transmitted by each active user, considering the asymptotic regime in which the number of users N and the length of the pilot sequences L both go to infinity with their ratio converging to a fixed positive value, i.e., L/N → ρ, while both the SNR and the probability are fixed
To exploit the statistical channel information and the specific structure of the sparsity pattern introduced by this scheme, i.e., only one row in each section can be non-zero, a novel receiving method based on the AMP algorithm with non-separable denoisers is proposed
Summary
Z. Tang et al.: Device Activity Detection and Non-Coherent Information Transmission for mMTCs. Observing that the activity pattern recovery is mathematically equivalent to the support recovery problem in compressed sensing (CS), people have proposed a two-phase grant-free random access scheme based on CS techniques. (1) To exploit the statistical channel information and the special correlation structure of the sparsity pattern incurred by the non-coherent transmission structure, i.e., only one row in each section can be non-zero, we propose a receiving method based on the approximate message passing (AMP) algorithm with a section-wise minimum mean square error (MMSE) denoiser.
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