Optimum beamforming for MIMO multicasting

Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-...
Ausführliche Beschreibung

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Autor*in:	Du, Baisheng [verfasserIn] Jiang, Yi [verfasserIn] Xu, Xiaodong [verfasserIn] Dai, Xuchu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	Physical layer multicasting Multiple-input multiple-output Transmit beamforming Semidefinite relaxation (SDR)

Übergeordnetes Werk:	Enthalten in: EURASIP journal on advances in signal processing - Heidelberg : Springer, 2007, 2013(2013), 1 vom: 25. Juni
Übergeordnetes Werk:	volume:2013 ; year:2013 ; number:1 ; day:25 ; month:06

Links:	Volltext

DOI / URN:	10.1186/1687-6180-2013-121

Katalog-ID:	SPR032003625

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520			\|a Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms.
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allfields	10.1186/1687-6180-2013-121 doi (DE-627)SPR032003625 (SPR)1687-6180-2013-121-e DE-627 ger DE-627 rakwb eng 620 ASE 53.73 bkl Du, Baisheng verfasserin aut Optimum beamforming for MIMO multicasting 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms. Physical layer multicasting (dpeaa)DE-He213 Multiple-input multiple-output (dpeaa)DE-He213 Transmit beamforming (dpeaa)DE-He213 Semidefinite relaxation (SDR) (dpeaa)DE-He213 Jiang, Yi verfasserin aut Xu, Xiaodong verfasserin aut Dai, Xuchu verfasserin aut Enthalten in EURASIP journal on advances in signal processing Heidelberg : Springer, 2007 2013(2013), 1 vom: 25. Juni (DE-627)534054277 (DE-600)2364203-8 1687-6180 nnns volume:2013 year:2013 number:1 day:25 month:06 https://dx.doi.org/10.1186/1687-6180-2013-121 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 53.73 ASE AR 2013 2013 1 25 06
spelling	10.1186/1687-6180-2013-121 doi (DE-627)SPR032003625 (SPR)1687-6180-2013-121-e DE-627 ger DE-627 rakwb eng 620 ASE 53.73 bkl Du, Baisheng verfasserin aut Optimum beamforming for MIMO multicasting 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms. Physical layer multicasting (dpeaa)DE-He213 Multiple-input multiple-output (dpeaa)DE-He213 Transmit beamforming (dpeaa)DE-He213 Semidefinite relaxation (SDR) (dpeaa)DE-He213 Jiang, Yi verfasserin aut Xu, Xiaodong verfasserin aut Dai, Xuchu verfasserin aut Enthalten in EURASIP journal on advances in signal processing Heidelberg : Springer, 2007 2013(2013), 1 vom: 25. Juni (DE-627)534054277 (DE-600)2364203-8 1687-6180 nnns volume:2013 year:2013 number:1 day:25 month:06 https://dx.doi.org/10.1186/1687-6180-2013-121 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 53.73 ASE AR 2013 2013 1 25 06
allfields_unstemmed	10.1186/1687-6180-2013-121 doi (DE-627)SPR032003625 (SPR)1687-6180-2013-121-e DE-627 ger DE-627 rakwb eng 620 ASE 53.73 bkl Du, Baisheng verfasserin aut Optimum beamforming for MIMO multicasting 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms. Physical layer multicasting (dpeaa)DE-He213 Multiple-input multiple-output (dpeaa)DE-He213 Transmit beamforming (dpeaa)DE-He213 Semidefinite relaxation (SDR) (dpeaa)DE-He213 Jiang, Yi verfasserin aut Xu, Xiaodong verfasserin aut Dai, Xuchu verfasserin aut Enthalten in EURASIP journal on advances in signal processing Heidelberg : Springer, 2007 2013(2013), 1 vom: 25. Juni (DE-627)534054277 (DE-600)2364203-8 1687-6180 nnns volume:2013 year:2013 number:1 day:25 month:06 https://dx.doi.org/10.1186/1687-6180-2013-121 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 53.73 ASE AR 2013 2013 1 25 06
allfieldsGer	10.1186/1687-6180-2013-121 doi (DE-627)SPR032003625 (SPR)1687-6180-2013-121-e DE-627 ger DE-627 rakwb eng 620 ASE 53.73 bkl Du, Baisheng verfasserin aut Optimum beamforming for MIMO multicasting 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms. Physical layer multicasting (dpeaa)DE-He213 Multiple-input multiple-output (dpeaa)DE-He213 Transmit beamforming (dpeaa)DE-He213 Semidefinite relaxation (SDR) (dpeaa)DE-He213 Jiang, Yi verfasserin aut Xu, Xiaodong verfasserin aut Dai, Xuchu verfasserin aut Enthalten in EURASIP journal on advances in signal processing Heidelberg : Springer, 2007 2013(2013), 1 vom: 25. Juni (DE-627)534054277 (DE-600)2364203-8 1687-6180 nnns volume:2013 year:2013 number:1 day:25 month:06 https://dx.doi.org/10.1186/1687-6180-2013-121 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 53.73 ASE AR 2013 2013 1 25 06
allfieldsSound	10.1186/1687-6180-2013-121 doi (DE-627)SPR032003625 (SPR)1687-6180-2013-121-e DE-627 ger DE-627 rakwb eng 620 ASE 53.73 bkl Du, Baisheng verfasserin aut Optimum beamforming for MIMO multicasting 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms. Physical layer multicasting (dpeaa)DE-He213 Multiple-input multiple-output (dpeaa)DE-He213 Transmit beamforming (dpeaa)DE-He213 Semidefinite relaxation (SDR) (dpeaa)DE-He213 Jiang, Yi verfasserin aut Xu, Xiaodong verfasserin aut Dai, Xuchu verfasserin aut Enthalten in EURASIP journal on advances in signal processing Heidelberg : Springer, 2007 2013(2013), 1 vom: 25. Juni (DE-627)534054277 (DE-600)2364203-8 1687-6180 nnns volume:2013 year:2013 number:1 day:25 month:06 https://dx.doi.org/10.1186/1687-6180-2013-121 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 53.73 ASE AR 2013 2013 1 25 06
language	English
source	Enthalten in EURASIP journal on advances in signal processing 2013(2013), 1 vom: 25. Juni volume:2013 year:2013 number:1 day:25 month:06
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institution	findex.gbv.de
topic_facet	Physical layer multicasting Multiple-input multiple-output Transmit beamforming Semidefinite relaxation (SDR)
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author	Du, Baisheng
spellingShingle	Du, Baisheng ddc 620 bkl 53.73 misc Physical layer multicasting misc Multiple-input multiple-output misc Transmit beamforming misc Semidefinite relaxation (SDR) Optimum beamforming for MIMO multicasting
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topic_title	620 ASE 53.73 bkl Optimum beamforming for MIMO multicasting Physical layer multicasting (dpeaa)DE-He213 Multiple-input multiple-output (dpeaa)DE-He213 Transmit beamforming (dpeaa)DE-He213 Semidefinite relaxation (SDR) (dpeaa)DE-He213
topic	ddc 620 bkl 53.73 misc Physical layer multicasting misc Multiple-input multiple-output misc Transmit beamforming misc Semidefinite relaxation (SDR)
topic_unstemmed	ddc 620 bkl 53.73 misc Physical layer multicasting misc Multiple-input multiple-output misc Transmit beamforming misc Semidefinite relaxation (SDR)
topic_browse	ddc 620 bkl 53.73 misc Physical layer multicasting misc Multiple-input multiple-output misc Transmit beamforming misc Semidefinite relaxation (SDR)
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title	Optimum beamforming for MIMO multicasting
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title_full	Optimum beamforming for MIMO multicasting
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title_sort	optimum beamforming for mimo multicasting
title_auth	Optimum beamforming for MIMO multicasting
abstract	Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms.
abstractGer	Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms.
abstract_unstemmed	Abstract This paper investigates the transmit (Tx) beamforming design to maximize the throughput of a multiple-input multiple-output multicast channel, where common information is sent from the base station to K users simultaneously. This so-called max-min fair beamforming problem is known to be NP-hard. When the base station is equipped with two Tx antennas, we prove that the original complex-valued beamforming problem can be transformed into a real-valued problem and the globally optimal solution can be found by exhausting at most hypothesis tests. Moreover, a prune and search algorithm (PASA) is proposed for searching the optimal beamformer with computational complexity in the worst case. When the base station has more than two Tx antennas, we develop an efficient algorithm named iterative two-dimensional optimization which converts the original beamforming problem into a series of two-antenna subproblems by iterations and hence, the beamformer is improved using PASA iteratively. Simulations results are presented to demonstrate the superior performance of the proposed algorithms.
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title_short	Optimum beamforming for MIMO multicasting
url	https://dx.doi.org/10.1186/1687-6180-2013-121
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up_date	2024-07-04T02:07:06.185Z
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