1. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 1 Contributions and Proposals of UPC - Department 1 NEWCOM Antonio Pascual Iserte Universitat Politècnica de Catalunya Barcelona, 9 March 2005

2. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 2  Design of MIMO systems: a practical overview: MIMO robust designs Design of limited feedback  Some proposals for future work: Other robust designs Impact of MIMO channels on system level aspects Outline

3. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 3  Design of MIMO systems: a practical overview: MIMO robust designs Design of limited feedback  Some proposals for future work: Other robust designs Impact of MIMO channels on system level aspects Outline

4. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 4 Robustness  Robust Designs: They take into account the errors in the CSI Sources of errors in the CSI for MIMO channels: oEstimation noise oChannel variability oQuantization of the channel estimate (feedback)  Robustness Strategies: Bayesian approach: statistical solution Maximin approach: best worst-case

5. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 5 Robustness Strategies  f : cost function to minimize, B : TX, A : RX  Bayesian Design Best statistical mean value  Maximin Design Optimization of the worst-case

6. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 6 Maximin Robust Transmitter - MIMO  OSTBC + power allocation + beamforming:  Receiver: linear operations

7. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 7  SNR:  Notation: Error Error in the channel estimate: oConvex uncertainty region: Beamformers Beamformers: estimated eigenmodes of Power distribution Power distribution: Cost function Cost function to maximize: Notation

8. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 8 Problem Formulation and Solution  Maximin robust design:  The problem can be solved using standard software packages for convex optimization problems:

9. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 9 Uncertainty Regions (I) Several sources of errors can be modeled (a) Gaussian estimation errors (TDD) (b) Errors from scalar quantization (FDD) (c) Combination of both (FDD) Quadratic convex problems…

10. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 10 Uncertainty Regions (II) Also vector quantization… In general… any error that can be modeled by a convex uncertainty region

11. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 11 Robust Adaptive Modulation

12. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 12  Design of MIMO systems: a practical overview: MIMO robust designs Design of limited feedback  Some proposals for future work: Other robust designs Impact of MIMO channels on system level aspects Outline

13. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 13 Limited Feedback  Introduction: Design of the feedback strategy: Transmitter Receiver Feedback Channel Quantization channel estimate ??? B bits of feedback

14. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 14 Limited Feedback - MIMO Channels (I)  Scalar Quantization (SQ): Direct quantization of the channel: oNon-iterative: uniform vs. non-uniform oIterative quantization: delta modulation Quantization of the strongest eigenvectors: oDirect quantization oQuantization in a parameterized space (e.g. the set of orthonormal vectors)

15. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 15 Limited Feedback - MIMO Channels (II)  Vector Quantization (VQ): Distortion measure: oSuboptimum oSuboptimum: distortion = error in the channel estimate oOptimum oOptimum: distortion = system performance Transmitter architecture: F (linear precoder) STC (space-time code) B bits of feedback N = 2 B : F 1, …, F N

16. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 16 Limited Feedback - MIMO Channels (III) Precoder codebook: {F 1, …, F N } Precoder selection function F= f (H): performance metric (SER, MSE, SNR, mutual information, etc…)  Example of design of the precoder codebook: Use a set of linear precoders F 1, …, F N spanning maximally spaced subspaces Grassmannian packaging Random precoder: easier, asymptotically equivalent to Grassmannian

17. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 17 Illustrative Results

18. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 18  Design of MIMO systems: a practical overview: MIMO robust designs Design of limited feedback  Some proposals for future work: Other robust designs Impact of MIMO channels on system level aspects Outline

19. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 19 Other Robust Designs  Extensions of the robust designs: Other transmitter architectures Multiuser scenarios Limited channel knowledge: oOnly gain oOnly phase Different degrees of knowledge at the transmitter and the receiver Robustness against implementation errors

20. A. Pascual Contributions and Proposals of UPC to Department 1 - NEWCOM 20 Impact of MIMO on System Level  Analysis of the benefits provided by MIMO at the system level: Identification of simulation scenarios Identification of appropriate figures of merit channel quality metric Identification of a channel quality metric for interface between the physical/link and higher layers oMIMO channel capacity omaximum eigenvalue of the MIMO channel matrix oothers… ???