An Exact Quantized Decentralized Gradient Descent Algorithm
We consider the problem of decentralized consensus optimization, where the sum of n smooth and strongly convex functions are minimized over…
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Resilient Distributed Parameter Estimation With Heterogeneous Data
This paper studies resilient distributed estimation under measurement attacks. A set of agents each makes successive local, linear, noisy…
Read moreSecure Distributed Detection of Sparse Signals via Falsification of Local Compressive Measurements
The problem of detecting a high-dimensional signal based on compressive measurements in the presence of an eavesdropper (Eve) is studied in this…
Read moreSequence Design for Spectral Shaping via Minimization of Regularized Spectral Level Ratio
The topic of sequence design has received considerable attention due to its wide applications in active sensing. One important desired property for…
Read moreSemi-Blind, Training, and Data-Aided Channel Estimation Schemes for MIMO-FBMC-OQAM Systems
This paper considers and analyzes the performance of semiblind, training, and data-aided channel estimation schemes for multiple-input multiple…
Read moreSuper-Resolution Blind Channel-and-Signal Estimation for Massive MIMO With One-Dimensional Antenna Array
In this paper, we study blind channel-and-signal estimation by exploiting the burst-sparse structure of angular-domain propagation channels in…
Read moreDecentralized Equalization With Feedforward Architectures for Massive MU-MIMO
Linear data-detection algorithms that build on zero forcing (ZF) or linear minimum mean-square error (L-MMSE) equalization achieve near-optimal…
Read moreFast Beam Alignment for Millimeter Wave Communications: A Sparse Encoding and Phaseless Decoding Approach
In this paper, we study the problem of beam alignment for millimeter wave (mmWave) communications, where a hybrid analog and digital beamforming…
Read moreHigh-Dimensional Filtering Using Nested Sequential Monte Carlo
Sequential Monte Carlo (SMC) methods comprise one of the most successful approaches to approximate Bayesian filtering. However, SMC without a good…
Read moreStability Bound of the Initial Mean-Square Deviation of High-Order Stochastic Gradient Adaptive Filtering Algorithms
The paper derives the stability bound of the initial mean-square deviation of an adaptive filtering algorithm based on minimizing the 2 L th moment…
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