Mei Y, Gao Z, Mi D, Zhou M, Zheng D, Matthaiou M, Xiao P, Schober R (2023)
Publication Type: Journal article
Publication year: 2023
Pages Range: 1-6
Massive connectivity for extra large-scale multi-input multi-output (XL-MIMO) systems is a challenging issue due to the near-field access channels and the prohibitive cost. In this paper, we propose an uplink grant-free massive access scheme for XL-MIMO systems, in which a mixed-analog-to-digital converters (ADC) architecture is adopted to strike the right balance between access performance and power consumption. By exploiting the spatial-domain structured sparsity and the piecewise angular-domain cluster sparsity of massive access channels, a compressive sensing (CS)-based two-stage orthogonal approximate message passing algorithm is proposed to efficiently solve the joint activity detection and channel estimation problem. Particularly, high-precision quantized measurements are leveraged to perform accurate hyper-parameter estimation, thereby facilitating the activity detection. Moreover, we adopt a subarray-wise estimation strategy to overcome the severe angular-domain energy dispersion problem which is caused by the near-field effect in XL-MIMO channels. Simulation results verify the superiority of our proposed algorithm over state-of-the-art CS algorithms for massive access based on XL-MIMO with mixed-ADC architectures.
APA:
Mei, Y., Gao, Z., Mi, D., Zhou, M., Zheng, D., Matthaiou, M.,... Schober, R. (2023). Massive Access in Extra Large-Scale MIMO With Mixed-ADC Over Near-Field Channels. IEEE Transactions on Vehicular Technology, 1-6. https://doi.org/10.1109/TVT.2023.3266230
MLA:
Mei, Yikun, et al. "Massive Access in Extra Large-Scale MIMO With Mixed-ADC Over Near-Field Channels." IEEE Transactions on Vehicular Technology (2023): 1-6.
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