Beamspace based AIC and MDL Algorithm for Counting the Number of Signals in Specific Range

Park, Heui-Seon; Hwang, Suk-Seung; Shin, Seok Joo; Pyun, Jae-Young

doi:10.1109/icufn55119.2022.9829625

Cited by 1 publication

(1 citation statement)

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“…[39] designed a hypothesis-testing algorithm based on stochastic matrix theory for MIMO-OFDM systems. In order to effectively estimate the number of signals within a specific range, the Akaike information criterion and the minimum description length algorithm based on beam space were proposed [40]. Zhao et al designed a convolutional neural network model based on the mapping relationship between signal covariance matrix and source number and realized the joint estimation of source number and DOA [41].…”

Section: Introductionmentioning

confidence: 99%

Spatial Parameter Identification for MIMO Systems in the Presence of Non-Gaussian Interference

Zhang,

Shi,

Chen

et al. 2024

Remote Sensing

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Reliable identification of spatial parameters for multiple-input multiple-output (MIMO) systems, such as the number of transmit antennas (NTA) and the direction of arrival (DOA), is a prerequisite for MIMO signal separation and detection. Most existing parameter estimation methods for MIMO systems only consider a single parameter in Gaussian noise. This paper develops a reliable identification scheme based on generalized multi-antenna time-frequency distribution (GMTFD) for MIMO systems with non-Gaussian interference and Gaussian noise. First, a new generalized correlation matrix is introduced to construct a generalized MTFD matrix. Then, the covariance matrix based on time-frequency distribution (CM-TF) is characterized by using the diagonal entries from the auto-source signal components and the non-diagonal entries from the cross-source signal components in the generalized MTFD matrix. Finally, by making use of the CM-TF, the Gerschgorin disk criterion is modified to estimate NTA, and the multiple signal classification (MUSIC) is exploited to estimate DOA for MIMO system. Simulation results indicate that the proposed scheme based on GMTFD has good robustness to non-Gaussian interference without prior information and that it can achieve high estimation accuracy and resolution at low and medium signal-to-noise ratios (SNRs).

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Section: Introductionmentioning

confidence: 99%