IEICE TRANSACTIONS on Communications
Block Adaptive Beamforming via Parallel Projection Method
Summary :
This paper addresses a simple, and yet effective approach to the design of block adaptive beamformers via parallel projection method (PPM), which is an extension of the classic projection onto convex set (POCS) method to inconsistent sets scenarios. The proposed approach begins with the construction of the convex constraint sets which the weight vector of the adaptive beamformer lies in. The convex sets are judiciously chosen to force the weights to possess some desirable properties or to meet some prescribed rules. Based on the minimum variance criterion and a fixed gain at the look direction, two constraint sets including the minimum variance constraint set and the gain constraint set are considered. For every input block of data, the weights of the proposed beamformer can then be determined by iteratively projecting the weight vector onto these convex sets until it converges. Furnished simulations show that the proposed beamformer provides superior performance compared with previous works in various scenarios but yet in general with lower computational overhead.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E88-B No.3 pp.1227-1233
- Publication Date
- 2005/03/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietcom/e88-b.3.1227
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Keyword
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Wen-Hsien FANG, Hsien-Sen HUNG, Chun-Sem LU, Ping-Chi CHU, "Block Adaptive Beamforming via Parallel Projection Method" in IEICE TRANSACTIONS on Communications,
vol. E88-B, no. 3, pp. 1227-1233, March 2005, doi: 10.1093/ietcom/e88-b.3.1227.
Abstract: This paper addresses a simple, and yet effective approach to the design of block adaptive beamformers via parallel projection method (PPM), which is an extension of the classic projection onto convex set (POCS) method to inconsistent sets scenarios. The proposed approach begins with the construction of the convex constraint sets which the weight vector of the adaptive beamformer lies in. The convex sets are judiciously chosen to force the weights to possess some desirable properties or to meet some prescribed rules. Based on the minimum variance criterion and a fixed gain at the look direction, two constraint sets including the minimum variance constraint set and the gain constraint set are considered. For every input block of data, the weights of the proposed beamformer can then be determined by iteratively projecting the weight vector onto these convex sets until it converges. Furnished simulations show that the proposed beamformer provides superior performance compared with previous works in various scenarios but yet in general with lower computational overhead.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e88-b.3.1227/_p
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@ARTICLE{e88-b_3_1227,
author={Wen-Hsien FANG, Hsien-Sen HUNG, Chun-Sem LU, Ping-Chi CHU, },
journal={IEICE TRANSACTIONS on Communications},
title={Block Adaptive Beamforming via Parallel Projection Method},
year={2005},
volume={E88-B},
number={3},
pages={1227-1233},
abstract={This paper addresses a simple, and yet effective approach to the design of block adaptive beamformers via parallel projection method (PPM), which is an extension of the classic projection onto convex set (POCS) method to inconsistent sets scenarios. The proposed approach begins with the construction of the convex constraint sets which the weight vector of the adaptive beamformer lies in. The convex sets are judiciously chosen to force the weights to possess some desirable properties or to meet some prescribed rules. Based on the minimum variance criterion and a fixed gain at the look direction, two constraint sets including the minimum variance constraint set and the gain constraint set are considered. For every input block of data, the weights of the proposed beamformer can then be determined by iteratively projecting the weight vector onto these convex sets until it converges. Furnished simulations show that the proposed beamformer provides superior performance compared with previous works in various scenarios but yet in general with lower computational overhead.},
keywords={},
doi={10.1093/ietcom/e88-b.3.1227},
ISSN={},
month={March},}
Copy
TY - JOUR
TI - Block Adaptive Beamforming via Parallel Projection Method
T2 - IEICE TRANSACTIONS on Communications
SP - 1227
EP - 1233
AU - Wen-Hsien FANG
AU - Hsien-Sen HUNG
AU - Chun-Sem LU
AU - Ping-Chi CHU
PY - 2005
DO - 10.1093/ietcom/e88-b.3.1227
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E88-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2005
AB - This paper addresses a simple, and yet effective approach to the design of block adaptive beamformers via parallel projection method (PPM), which is an extension of the classic projection onto convex set (POCS) method to inconsistent sets scenarios. The proposed approach begins with the construction of the convex constraint sets which the weight vector of the adaptive beamformer lies in. The convex sets are judiciously chosen to force the weights to possess some desirable properties or to meet some prescribed rules. Based on the minimum variance criterion and a fixed gain at the look direction, two constraint sets including the minimum variance constraint set and the gain constraint set are considered. For every input block of data, the weights of the proposed beamformer can then be determined by iteratively projecting the weight vector onto these convex sets until it converges. Furnished simulations show that the proposed beamformer provides superior performance compared with previous works in various scenarios but yet in general with lower computational overhead.
ER -
English
