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"Blind Grant-Free Random Access with Message Passing Based Matrix Facto" by Zhengdao Yuan, Fei Liu et al.

Grant-free random access is promising in achieving massive connectivity with sporadic transmissions in massive machine type communications (mMTC) for internet of things (IoT) applications, where the hand-shaking between the access point (AP) and users is skipped, leading to high multiple access efficiency. In grant-free random access, the AP needs to identify the active users and perform channel estimation and signal detection. Conventionally, pilot signals are required for the AP to achieve user activity detection and channel estimation before active user signal detection, which may still result in substantial overhead and latency. In this paper, to further reduce the overhead and latency, we investigate the problem of grant-free random access without the use of pilot signals in a millimeter wave (mmWave) multiple input and multiple output (MIMO) system, where the AP performs blind joint user activity detection, channel estimation and signal detection (UACESD). We show that the blind ....

Approximate Message Passing , Channel Estimation , Covariance Matrices , Rant Free Random Access , Nternet Of Things , Massive Machine Type Communications , Message Passing , Illimeter Wave Communication , Millimeter Wave Communications , Imo Communication , Signal Detection , Ser Activity Detection ,

"UAMP-Based Equalization for Dual Pulse Shaping Transmission Systems" by Peisen Cai, Hang Li et al.

Dual pulse shaping (DPS) transmissions enable the use of A/D and D/A converters with half of the symbol rate, alleviating the requirement of high speed conversion devices in wideband millimeter wave communications. In this letter, we focus on DPS equalization and propose a unitary approximate message passing (UAMP) based equalization technique. Two DPS transmission schemes are considered, and by exploiting the special structure of the system transfer matrix, two low-complexity equalizers are developed with the fast Fourier transform (FFT). Simulation results show that significant performance gains can be achieved by the UAMP-based equalizers, compared to the conventional DPS equalizer. ....

Covariance Matrices , Igital Analog Conversion , Ual Pulse Shaping , Message Passing , Yquist Pulses And Complementary Nyquist , Performance Gain , Ulse Shaping Methods , Nitary Approximate Message Passing ,

"Direction of Arrival Estimation With Gain-Phase Uncertainties in Unkno" by He Xu, Ming Jin et al.

This paper considers the problem of direction-of-arrival (DOA) estimation for narrowband source signals under the coexistence of gain-phase uncertainties and nonuniform noise. Firstly, by exploiting the low-rank property of the covariance of signal components, and the diagonal property of noise covariance, an optimization problem with low-rank constraints is formulated to estimate the nonuniform noise covariance matrix, which is then solved efficiently by the alternating direction method of multipliers (ADMM). Secondly, a linear transformation operator is employed to construct a rank reduction (RARE) estimator, and subsequently an initial DOA and gain-phase uncertainties are obtained via one-dimensional (1-D) spectral search. With initial estimates, an augmented DOA estimation is finally achieved by constructing a weighted and structured sparse total least-squares (WSS-TLS) optimization problem, which is solved using the block coordinate descent algorithm. Simulation results show the s ....

Alternating Direction Method Of Multipliers , Covariance Matrices , Irection Of Arrival Estimation , Ain Phase Uncertainties , Noise Level , Signal To Noise Ratio , Parse Total Least Squares , Nknown Nonuniform Noise ,

"Unitary Approximate Message Passing for Sparse Bayesian Learning" by Man Luo, Qinghua Guo et al.

Sparse Bayesian learning (SBL) can be implemented with low complexity based on the approximate message passing (AMP) algorithm. However, it does not work well for a generic measurement matrix, which may cause AMP to diverge. Damped AMP has been used for SBL to alleviate the problem at the cost of reducing convergence speed. In this work, we propose a new SBL algorithm based on structured variational inference, leveraging AMP with a unitary transformation (UAMP). Both single measurement vector and multiple measurement vector problems are investigated. It is shown that, compared to stateof- the-art AMP-based SBL algorithms, the proposed UAMPSBL is more robust and efficient, leading to remarkably better performance. ....

Approximate Message Passing , Approximation Algorithms , Bayes Methods , Covariance Matrices , Nference Algorithms , Message Passing , Signal Processing Algorithms , Parse Bayesian Learning , Parse Matrices , Tructured Variational Inference ,