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A New Heterogeneous Hybrid Massive MIMO Receiver with An Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning
To address this problem, a new heterogeneous sub-connected hybrid analog and digital (HAD) MIMO structure is proposed with an intrinsic ability of removing phase ambiguity and a corresponding new framework is developed to implement a rapid high-precision DOA estimation using only single time-slot.
Low-Complexity Three-Dimensional AOA-Cross Geometric Center Localization Methods via Multi-UAV network
It is not able to estimate angle noise but has lower computational complexity.
Deep Learning Based DOA Estimation for Hybrid Massive MIMO Receive Array with Overlapped Subarrays
To improve the accuracy of direction-of-arrival (DOA) estimation, a deep learning (DL)-based method called CDAE-DNN is proposed for hybrid analog and digital (HAD) massive MIMO receive array with overlapped subarray (OSA) architecture in this paper.
High-performance Passive Eigen-model-based Detectors of Single Emitter Using Massive MIMO Receivers
The test statistic (TS) of the first method is defined as the ratio of maximum eigen-value (Max-EV) to minimum eigen-value (R-MaxEV-MinEV) while that of the second one is defined as the ratio of Max-EV to noise variance (R-MaxEV-NV).
Enhanced RSS-based UAV Localization via Trajectory and Multi-base Stations
First, fixing the nth BS, by exploiting multiple measurements along trajectory, the position of UAV is computed by ML rule.
Impact of Low-Resolution ADC on DOA Estimation Performance for Massive MIMO Receive Array
In this paper, we present a new scenario of direction of arrival (DOA) estimation using massive multiple-input multiple-output (MIMO) receive array with low-resolution analog-to-digital convertors (ADCs), which can strike a good balance between performance and circuit cost.
Information Theory Signal Processing Information Theory
