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ALTERNATING MAXIMIZATION ALGORITHM FOR THE BROADCAST BEAMFORMING
Date
2014-09-05
Author
Demir, Özlem Tuğfe
Tuncer, Temel Engin
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Semidefinite relaxation (SDR) is a powerful approach to solve nonconvex optimization problems involving rank condition. However its performance becomes unacceptable for certain cases. In this paper, a nonconvex equivalent formulation without the rank condition is presented for the broadcast beamforming problem. This new formulation is exploited to obtain an alternating optimization method which is shown to converge to the local optimum rank one solution. Proposed method opens up new possibilities in different applications. Simulations show that the new method is very effective and can attain global optimum especially when the number of users is low.
Subject Keywords
Transmit beamforming
,
Multicast beamforming
,
Semidefinite relaxation
,
Convex optimization
URI
https://hdl.handle.net/11511/54991
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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Ö. T. Demir and T. E. Tuncer, “ALTERNATING MAXIMIZATION ALGORITHM FOR THE BROADCAST BEAMFORMING,” 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54991.
