A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization

This paper considers a wireless communication system with multiple transmit and receive antennas, i.e., a multiple-input-multiple-output (MIMO) channel. The objective is to design the transmitter according to an imperfect channel estimate, where the errors are explicitly taken into account to obtain...

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Detalles Bibliográficos
Autores: Pascual Iserte, Antonio|||0000-0001-5596-2029, Pérez Palomar, Daniel, Pérez Neira, Ana Isabel|||0000-0003-4281-3934, Lagunas Hernandez, Miguel A.|||0000-0003-3338-244X
Tipo de recurso: artículo
Fecha de publicación:2006
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/8782
Acceso en línea:https://hdl.handle.net/2117/8782
https://dx.doi.org/10.1109/TSP.2005.861084
Access Level:acceso abierto
Palabra clave:Antennas
Signal theory (Telecommunication)
Antenes
Senyal, Teoria del (Telecomunicació)
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
Descripción
Sumario:This paper considers a wireless communication system with multiple transmit and receive antennas, i.e., a multiple-input-multiple-output (MIMO) channel. The objective is to design the transmitter according to an imperfect channel estimate, where the errors are explicitly taken into account to obtain a robust design under the maximin or worst case philosophy. The robust transmission scheme is composed of an orthogonal space–time block code (OSTBC), whose outputs are transmitted through the eigenmodes of the channel estimate with an appropriate power allocation among them. At the receiver, the signal is detected assuming a perfect channel knowledge. The optimization problem corresponding to the design of the power allocation among the estimated eigenmodes, whose goal is the maximization of the signal-to-noise ratio (SNR), is transformed to a simple convex problem that can be easily solved. Different sources of errors are considered in the channel estimate, such as the Gaussian noise from the estimation process and the errors from the quantization of the channel estimate, among others. For the case of Gaussian noise, the robust power allocation admits a closed-form expression. Finally, the benefits of the proposed design are evaluated and compared with the pure OSTBC and nonrobust approaches.