Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning

By Ying Sun, Prabhu Babu, D. P. Palomar. 2017

1,647 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computational Mechanics, Numerical Analysis

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Citations in the corpus

Near-Field Communications: A Tutorial Review (2023, methodology): “It can be solved with existing methods [55]–[57].”
Enabling Secure Wireless Communications via Intelligent Reflecting Surfaces (2019, methodology): “In this paper, we propose to solve P4 by the MM technique [14], whose main idea is illustrated in Fig.”
Joint Transmit Waveform and Passive Beamforming Design for RIS-Aided DFRC Systems (2021, background): “As shown in the equation (14) in [49], function sHM−1s is jointly convex with respect to s and positive-definite matrix M, and a surrogate function of sHM−1s at point (st,Mt) is given by sHM−1s ≥ 2 {sHt M−1 t s}− Tr{M−1 t stst M−1 t M}+ c,”
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications (2021, methodology): “Convex approximation provides a natural way to design polynomial time complexity algorithms for nonconvex programs based on the principle of majorization-minimization [262] or successive convex approximation [263].”
Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing (2019, methodology): “In the following, the MM algorithm [43] is invoked for solving this problem, which has two steps.”
Constrained Deep Learning for Wireless Resource Management (2019, background): “For several decades, there have been significant progresses in nonconvex optimization techniques for signal processing and wireless communication systems [1], [2].”
Intelligent Reflecting Surface Aided Multigroup Multicast MISO Communication Systems (2019, methodology): “The function f̃(x|xn) is said to minorize f(x) at a given point x if they satisfy the following conditions [23]:”
A Brief Introduction to Machine Learning for Engineers (2017, methodology): “The EM algorithm is an instance of the more general Majorization Minimization (MM) algorithm [97].”
Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces (2019, methodology): “The first one is the Majorization-Minimization (MM) Algorithm [34], where a closed-form solution can be obtained in each iteration.”
A Very Brief Introduction to Machine Learning With Applications to Communication Systems (2018, background): “5EM is an instance of the more general Majorization-Minimization algorithm [61].”
Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer (2019, methodology): “Then, a novel iterative algorithm based on the majorization-minimization (MM) algorithm [31] and on the price-based method [32] is developed for solving the QCQP.”
IRS-Assisted Secure UAV Transmission via Joint Trajectory and Beamforming Design (2022, background): “Speciﬁcally, based on [37], the relationship is detailed as where A [ n ] , B [ n ] and C [ n ] are given by Note that ~ u [ n ] denotes the optimal solution to u [ n ] in the previous iteration.”
A Joint Precoding Framework for Wideband Reconfigurable Intelligent Surface-Aided Cell-Free Network (2020, background): “41], while it has been proved that its optimal solution can be obtained by adopting the majorization-minimization (MM) algorithm [43] or complex circle manifold (CCM) algorithm [44].”
UAV-Assisted Data Collection for Internet of Things: A Survey (2022, background): “8, the principle of SCA is similar to majorize– minimize or minorize–maximize (MM), which can solve a series of convex optimization problems similar to the original problem iteratively [94], [95].”
Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks (2019, methodology): “In this paper, we adopt the surrogate function constructed by the second order Taylor expansion [50]:”
Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing (2022, positive): “Moreover, for nonconvex unit-modulus phase shift constraints in RIS-aided systems, the majorization-minimization (MM) framework [162] and the Riemannian manifold optimization [163] are also commonly used.”