| Paper: | SAM-P6.2 | ||
| Session: | Space-Time Processing for Communications | ||
| Time: | Thursday, May 20, 09:30 - 11:30 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: MIMO systems and space-time decoding | ||
| Title: | STATISTICAL PREFILTER DESIGN FOR MIMO ZF AND MMSE RECEIVERS BASED ON MAJORIZATION THEORY | ||
| Authors: | Mario Kiessling; University of Stuttgart | ||
| Joachim Speidel; University of Stuttgart | |||
| Abstract: | Recently, the authors have proposed statistical prefilters for MMSE and ZF receivers that minimize SER. In this paper, we give a general derivation of their structure based on majorization theory. For both receiver types it is shown that the optimal prefilter essentially transmits on the strongest long-term eigenmodes of the channel with proper power allocation. Moreover, simple closed-form power allocation schemes are presented for Rayleigh and Ricean fading environments. Interestingly, while the statistical prefilters exhibit the same basic mathematical structure as their short-term counterparts, they require only statistical information of the correlation properties and the Ricean component of the channel. Monte-Carlo simulations show that the proposed filters can achieve a considerable performance gain. Specifically, it is demonstrated that they can completely counteract the SER degradation due to a Ricean channel component. | ||
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