Unlike the commonly adopted random projections, we utilize the a priori probability distribution of the directions-of-arrival (DOAs) of the signals to optimize ...
In this paper, we have considered the compressive sensing matrix optimization for DOA estimation in a massive MIMO system. Different from the commonly used ...
In this paper, we have considered the compressive sensing matrix optimization for DOA estimation in a massive MIMO system. Different from the commonly used ...
Dive into the research topics of 'Optimized compressive sensing-based direction-of-arrival estimation in massive MIMO'. Together they form a unique fingerprint.
Abstract—This paper considers massive access in massive multiple-input multiple-output (MIMO) systems and proposes an adaptive active user detection and ...
In this paper, we consider the problem of direction-of-arrival (DoA) estimation using electronically steerable parasitic array radiator (ESPAR) antenna ...
To achieve high- resolution DOA estimation, the compressed measurements are employed to obtain the Capon spatial spectrum, where the large array aperture is ...
[PDF] 1-Bit Direction of Arrival Estimation based on Compressed Sensing
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The objective of the optimization problem ensures that the estimate ˆS is row sparse while its constraint forces it to be consistent with the measurements X.
Compared to large-scale MIMO radar, coprime MIMO radar can achieve approximate estimation performance with reduced antenna number.
In this paper, we propose a deep learning based approach to optimizing the CMM using long short-term memory (LSTM) networks.