Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/182439
Title: Beamforming for Full-Duplex Multiuser MIMO Systems
Authors: Jinwoo Kim;Wan Choi;Hyuncheol Park
Year: 2017
Publisher: IEEE
Abstract: We solve a sum rate maximization problem of full-duplex (FD) multiuser multiple-input-multiple-output (MU-MIMO) systems. Since additional self-interference (SI) in the uplink channel and cochannel interference (CCI) in the downlink channel are coupled in FD communication, the downlink and uplink multiuser beamforming vectors are required to be jointly designed. However, the joint optimization problem is nonconvex and difficult to solve due to the coupled effect. To properly address the coupled design issue, we reformulate the problem into an equivalent uplink channel problem by using the uplink and downlink channel duality known as multiple-access channel-broadcast channel duality (MAC-BC duality). Then, using a minorization-maximization (MM) algorithm based on an affine approximation, we obtain a solution for the reformulated problem. In addition, without any approximation and thus performance degradation, we develop an alternative algorithm based on iterative water filling (IWF) to solve the nonconvex problem. The proposed algorithms warrant fast convergence and low computational complexity.
URI: http://localhost/handle/Hannan/182439
volume: 66
issue: 3
More Information: 2423,
2432
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7492210.pdf537.34 kBAdobe PDF
Title: Beamforming for Full-Duplex Multiuser MIMO Systems
Authors: Jinwoo Kim;Wan Choi;Hyuncheol Park
Year: 2017
Publisher: IEEE
Abstract: We solve a sum rate maximization problem of full-duplex (FD) multiuser multiple-input-multiple-output (MU-MIMO) systems. Since additional self-interference (SI) in the uplink channel and cochannel interference (CCI) in the downlink channel are coupled in FD communication, the downlink and uplink multiuser beamforming vectors are required to be jointly designed. However, the joint optimization problem is nonconvex and difficult to solve due to the coupled effect. To properly address the coupled design issue, we reformulate the problem into an equivalent uplink channel problem by using the uplink and downlink channel duality known as multiple-access channel-broadcast channel duality (MAC-BC duality). Then, using a minorization-maximization (MM) algorithm based on an affine approximation, we obtain a solution for the reformulated problem. In addition, without any approximation and thus performance degradation, we develop an alternative algorithm based on iterative water filling (IWF) to solve the nonconvex problem. The proposed algorithms warrant fast convergence and low computational complexity.
URI: http://localhost/handle/Hannan/182439
volume: 66
issue: 3
More Information: 2423,
2432
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7492210.pdf537.34 kBAdobe PDF
Title: Beamforming for Full-Duplex Multiuser MIMO Systems
Authors: Jinwoo Kim;Wan Choi;Hyuncheol Park
Year: 2017
Publisher: IEEE
Abstract: We solve a sum rate maximization problem of full-duplex (FD) multiuser multiple-input-multiple-output (MU-MIMO) systems. Since additional self-interference (SI) in the uplink channel and cochannel interference (CCI) in the downlink channel are coupled in FD communication, the downlink and uplink multiuser beamforming vectors are required to be jointly designed. However, the joint optimization problem is nonconvex and difficult to solve due to the coupled effect. To properly address the coupled design issue, we reformulate the problem into an equivalent uplink channel problem by using the uplink and downlink channel duality known as multiple-access channel-broadcast channel duality (MAC-BC duality). Then, using a minorization-maximization (MM) algorithm based on an affine approximation, we obtain a solution for the reformulated problem. In addition, without any approximation and thus performance degradation, we develop an alternative algorithm based on iterative water filling (IWF) to solve the nonconvex problem. The proposed algorithms warrant fast convergence and low computational complexity.
URI: http://localhost/handle/Hannan/182439
volume: 66
issue: 3
More Information: 2423,
2432
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7492210.pdf537.34 kBAdobe PDF