Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC

Bin SHEN; Hebiao WU; Shufeng ZHAO; Taiping CUI

doi:10.11999/JEIT190994

Volume 42 Issue 12

Dec. 2020

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Article Navigation > Journal of Electronics & Information Technology > 2020 > 42(12): 2960-2968

Bin SHEN, Hebiao WU, Shufeng ZHAO, Taiping CUI. Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2960-2968. doi: 10.11999/JEIT190994

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Bin SHEN, Hebiao WU, Shufeng ZHAO, Taiping CUI. Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2960-2968. doi: 10.11999/JEIT190994

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Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC

doi: 10.11999/JEIT190994

School of Communications and Information Engineering, Chongqing University of Posts andTelecommunications, Chongqing 400065, China

Funds: The National Key R&D Program of China (2017YFE0118900), The EU H2020 Project (734798)

Received Date: 2019-12-13
Rev Recd Date: 2020-06-23

Available Online: 2020-07-18

Publish Date: 2020-12-08

Abstract

Abstract

In massive Machine-Type Communication (mMTC) systems, when the user activity is exploited as a priori information for the receiver, the Sparsity-aware Maximum A Posteriori probability (S-MAP) criterion can be used to recover the sparse multi-user vectors over the uplink mMTC systems. In order to reduce the computational complexity of S-MAP detection, based on interference cancellation mechanism, an Improved Activity-aware Sorted QR Decomposition (IA-SQRD) algorithm is proposed in this paper. The IA-SQRD algorithm utilizes the final solution of the A-SQRD algorithm as the initial solution and the iterative interference cancellation operation is performed to improve further the detection performance. Following the same philosophy in improving the A-SQRD algorithm, the conventional Sparsity-Aware Successive Interference Cancellation (SA-SIC), Sorted QR Decomposition (SQRD), and Data-Dependent Sorting and regularization (DDS) algorithms are modified to enhance the performance, respectively. Simulation results verify that compared with the A-SQRD algorithm, a 3 dB gain is achieved by the proposed IA-SQRD algorithm when the Bit Error Rate (BER) is
\begin{document}$2.5 \times {10^{ - 2}}$\end{document}
, without significantly increasing the computational complexity. In addition, given different system configurations in terms of active probability and the length of spread spectrum sequence, the proposed IA-SQRD also exhibits better performance than that of the other algorithms mentioned in this paper.

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References(21)

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