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Showing 1 to 8 of 8 for “"Successive convex approximation"”.
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Successive convex approximation: analysis and applications
… approach which updates the variable blocks by successively minimizing a sequence of approximations of f which are either locally tight upper bounds of f or strictly convex local approximations of f. Different block selection rules are considered such as cyclic (Gauss-Seidel), greedy …
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Fast algorithm for joint unicast and multicast beamforming in large-scale systems
… For the multicast subproblem, we apply the successive convex approximation (SCA) method to solve it iteratively. Each SCA subproblem is then reformulated to the ADMM form, providing the closed-form update for the multicast subproblem. Simulation results show that the proposed algorithm …
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Optimal structure and efficient algorithm for max-min fair multi-group multicast beamforming
… two algorithms by either direct method via successive convex approximation (SCA), or solving the QoS problem iteratively. For massive MIMO systems, we propose an efficient MMF multicast beamforming design based on the optimal solution structure. The semi-definite relaxation (SDR) method and …
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Low complexity multicast beamforming in massive MIMO multi-cell networks
… solve it via semi-definite relaxation (SDR) and successive convex approximation (SCA). To further reduce the computational complexity and the communication overhead, a distributed weighted MRT beamforming design based on signal-to-leakage ratio (SLR) is developed. Furthermore, we propose a …
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Sum-rate maximization in multi-RIS multi-carrier systems through active power allocation and passive beamforming
… power allocation and passive RIS beamforming. Approximations are introduced in the algorithm design to enable tractable, suboptimal solutions for the passive array optimization under each scenario. To validate our approach, we benchmark the proposed methods against an exhaustive search …
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Machine learning approach to slice admission control in 5G wireless network
… this problem, including branch and bound (BnB), successive convex approximation (SCA), the alternating direction method of multipliers (ADMM), heuristic methods, genetic algorithms (GA), and machine learning (ML) techniques. Secondly, this thesis introduces a multi-server, multi-queue resource …
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Coupled Natural Gas and Electric Power Systems
… and inequalities, and is further relaxed to a convex semidefinite program (SDP) minimization. Drawing parallels to the power flow problem, the relaxation is shown to be exact if the cost function is judiciously designed using a representative set of network states. Numerical tests on a Belgian …
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Centralized and distributed resource allocation with applications to signal processing in communications
… algorithms for the optimization of nonconvex and nonseparable sum-utility functions subject to convex coupling constraints. Even though, we focus on utility functions of the Difference of Convex (DC) type, further generalizations are possible. Moreover, the obtained iterative schemes …