1. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 CNIT-POLIMI: technical expertise and people in Dep. 1 Researchers: –Umberto Spagnolini (spagnoli@elet.polimi.it) –Arnaldo Spalvieri (spalvier@elet.polimi.it) –Monica Nicoli (nicoli@elet.polimi.it) –Maurizio Magarini (magarini@elet.polimi.it) PhD students: –Osvaldo Simeone (simeone@elet.polimi) –Roberto Bosisio (bosisio@elet.polimi.it) –Stefano Savazzi (savazzi@elet.polimi.it) –Matteo Albanese (albanese @elet.polimi.it) Technical expertise: –channel estimation and equalization; –coding techniques and soft-decision decoding algorithms; –soft-iterative receiver structures; –advanced signal processing for MIMO/OFDM wireless systems; –FPGA implementation of coding and equalization algorithms

2. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Subspace methods for channel estimation and tracking Technical background: Subspace methods for channel estimation, tracking and equalization of time-varying space-time structured channels in multiple-antenna OFDM receivers. Ongoing cooperations with other universities: 1. Signals and Systems - University of Uppsala (within Dep. 1 and Project C): adaptive transmission in MIMO-OFDM systems using subspace-based channel tracking (6-month exchange of 1 PhD student). 2. CWC - University of Oulu (not within NEWCOM): soft-iterative SIMO/MIMO subspace-based receivers with soft-based channel estimation and synchronization (6-month exchange of 1 Master student). Offers for cooperations : CNIT-Polimi is open to cooperations/exchange of researchers Contact persons: R. Bosisio, M. Nicoli, S. Savazzi, O. Simeone, U. Spagnolini [1] M. Nicoli and U. Spagnolini, "Subspace-methods for space-time processing," in Smart Antennas State of the Art, Chapter 1: Receiver Processing, EURASIP-Book series, Hindawi Publ. Corp., to be published, 2005. [2] M. Cicerone, O. Simeone, N. Geng, U. Spagnolini, “Modal analysis/filtering to estimate time-varying MIMO-OFDM channels,” ITG Workshop on Smart Antennas (WSA), March 18-19, Munich, 2004 (journal paper submitted). [3] R. Bosisio, M. Nicoli and U. Spagnolini, "Kalman filter of channel modes in time-varying wireless systems," Proc. IEEE ICASSP 2005 (journal paper submitted).

3. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Reduced complexity detection schemes for MIMO-OFDM systems Technical background: Extension of the mapping by set partitioning principle to develop a low complexity detection scheme for flat-fading MIMO systems with spatial multiplexing [4] Offers for cooperation: Design of efficient reduced complexity detection schemes for MIMO-OFDM systems. The starting point is represented by suboptimal architectures that are proposed for flat-fading MIMO systems. Contact persons: Arnaldo Spalvieri, Maurizio Magarini [4] M. Magarini, A. Spalvieri, “A suboptimal detection scheme for MIMO systems with non-binary constellations,” IEEE PIMRC 2004.

4. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Subspace methods for channel estimation and tracking CNIT-POLIMI

5. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Multipath channel model NTNT NRNR Antenna arrays gains Fading amplitudes Power profile Clarke model Space-Time channel matrix: Delay profile )( ][ nφββ dnd,    E

6. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Channel modal analysis Rearrangement of the parameters to separate slow/fast varying components: Angles/delays Fast-fading Subspace channel model: with Space-time modes UdUΣVTh  )( H Modal amplitudes Adaptive channel estimation based on the subspace model (MODAL ESTIMATION) Slow tracking of the space-time channel modes by subspace-tracking algorithms Fast tracking of the modal fading amplitudes by Kalman Filter tracking

7. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Simulation results MSE vs. SNR ( ) -30-20-1001020 -40 -30 -20 -10 0 10 20 30 40 50 MSE [dB] SNR [dB] LEAST SQUARES MODAL ESTIMATION LOWER BOUND

8. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Efficient modal-amplitude tracking Simplified Kalman method: it decouples channel tracking into a set of independent tracking algorithms, one for each modal amplitude. MSE vs. SNR for different algorithms ( ) 0510152025303540 SNR [dB] MSE [dB] -10 -20 -30 -40 LMS WIENER LMS KALMAN KALMAN SIMPLIFIED

9. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 A suboptimal detection scheme for MIMO systems with non-binary constellations CNIT-POLIMI

10. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Maximum Likelihood Detector (MLD) In a flat-fading MIMO transmission systems, the ML detector performs the estimation of the transmitted signal vector according to By denoting as q the size of the scalar QAM constellation transmitted from each antenna and N the number of transmitting antennas, an exhaustive search over a total of q N is required The complexity can be prohibitively extensive when N and q are high

11. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Proposed detector Real and the imaginary part of each QAM symbol belongs to the integer set ℤ The binary partition ℤ /2 ℤ is considered in each dimension of the QAM constellation for each transmitted substream A list of 2 2N candidate subsets is generated by considering the 2 2N combinations of LSB’s for the N entries of the transmitted vector ã Let q=2 2k be the size of the scalar QAM constellation The V-BLAST can be applied to perform the detection in each of these 2 2N subsets each containing N2 2(k-1) points At each stage the detector examines the decision statistic for the symbol sent from antenna n and compares it with the candidate symbols that are drawn from the current subset associated to substream n At the end of the procedure a list of 2 2N candidate vectors is generated

12. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Proposed detector A final decision is taken by applying the MLD to this reduced set where A r is the reduced set containing the 2 2N candidate vectors The complexity of the MLD on the reduced set of candidate vectors is independent of the size of the constellation in use

13. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Simulation results

14. CNIT-Polimi, Newcom Cluster 2 Meeting, Barcelona 9-10 March 2005 Conclusions Main contribution Extension of the mapping by set partitioning principle, used in RSSD, to the development of suboptimal receivers in spatial multiplexing systems Performance of the resulting suboptimal receiver is close to that of the Maximum Likelihood (ML) receiver for low-to-intermediate SNR Offers for cooperation: Design of efficient reduced complexity detection schemes for MIMO- OFDM systems. The starting point is represented by suboptimal architectures that are proposed for flat-fading MIMO systems. Contact persons: Arnaldo Spalvieri (spalvier@elet.polimi.it) Maurizio Magarini (magarini@elet.polimi.it)