Sparse Multiple Relay Selection for Network Beamforming with Individual Power Constraints Using Semidefinite Relaxation
This paper deals with the multiple relay selection problem in two-hop wireless cooperative networks with individual power constraints at the relays. In particular, it addresses the problem of selecting the best subset of K cooperative nodes and their corresponding beamforming weights so that the sig...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) |
| Repositorio: | r-CTTC. Repositorio Institucional Producción Científica del Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) |
| OAI Identifier: | oai:cttc.fundanetsuite.com:p1750 |
| Acceso en línea: | https://cttc.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=1750 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962159082&doi=10.1109%2fTWC.2015.2487439&partnerID=40&md5=a337fd77e5e130d89baeb9a8dc753982 |
| Access Level: | acceso abierto |
| Palabra clave: | Beamforming Combinatorial optimization Complex networks Distributed beam-forming Multiple relay selections Semidefinite relaxation sparsity-promoting norms Wireless relay networks Signal to noise ratio |
| Sumario: | This paper deals with the multiple relay selection problem in two-hop wireless cooperative networks with individual power constraints at the relays. In particular, it addresses the problem of selecting the best subset of K cooperative nodes and their corresponding beamforming weights so that the signal-to-noise ratio (SNR) is maximized at the destination. This problem is computationally demanding and requires an exhaustive search over all the possible combinations. In order to reduce the complexity, a new suboptimal method is proposed. This technique exhibits a near-optimal performance with a computational burden that is far less than the one needed in the combinatorial search. The proposed method is based on the use of the l1-norm squared and the Charnes-Cooper transformation and naturally leads to a semidefinite programming relaxation with an affordable computational cost. Contrary to other approaches in the literature, the technique exposed herein is based on the knowledge of the second-order statistics of the channels and the relays are not limited to cooperate with full power. © 2002-2012 IEEE. |
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