On the overhead of interference alignment: training, feedback, and cooperation
Interference alignment (IA) is a cooperative transmission strategy that, under some conditions,/nachieves the interference channel’s maximum number of degrees of freedom. Realizing IA gains,/nhowever, is contingent upon providing transmitters with sufficiently accurate channel knowledge. In/nthis pa...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2012 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/23403 |
| Acceso en línea: | http://hdl.handle.net/10230/23403 http://dx.doi.org/10.1109/TWC.2012.092412120588 |
| Access Level: | acceso abierto |
| Palabra clave: | MIMO Analog feedback Channel estimation Channel state information (CSI) Interference alignment Interference cancellation Interference channels Multiple access interference |
| Sumario: | Interference alignment (IA) is a cooperative transmission strategy that, under some conditions,/nachieves the interference channel’s maximum number of degrees of freedom. Realizing IA gains,/nhowever, is contingent upon providing transmitters with sufficiently accurate channel knowledge. In/nthis paper, we study the performance of IA in multiple-input multiple-output systems where channel/nknowledge is acquired through training and analog feedback.We design the training and feedback system/nto maximize IA’s effective sum-rate: a non-asymptotic performance metric that accounts for estimation/nerror, training and feedback overhead, and channel selectivity. We characterize effective sum-rate with/noverhead in relation to various parameters such as signal-to-noise ratio, Doppler spread, and feedback/nchannel quality. A main insight from our analysis is that, by properly designing the CSI acquisition/nprocess, IA can provide good sum-rate performance in a very wide range of fading scenarios. Another/nobservation from our work is that such overhead-aware analysis can help solve a number of practical/nnetwork design problems. To demonstrate the concept of overhead-aware network design, we consider/nthe example problem of finding the optimal number of cooperative IA users based on signal power and/nmobility. |
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