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within Newcom Dept. 1 - Cluster 2 Coding Design for OFDM and MIMO Systems Competences and Collaborations. Roberto Bosisio On behalf of Antonio Assalini CNIT unit: University of Padova. November 2nd-3rd, 2005 Barcelona.

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within Newcom

Dept. 1 - Cluster 2

Coding Design for OFDM and MIMO Systems

Competences and


Roberto Bosisio

On behalf of Antonio Assalini

CNIT unit: University of Padova

November 2nd-3rd, 2005 Barcelona

italy national inter university consortium for telecommunications
(Italy)National Inter-University Consortium for Telecommunications
  • non-profit consortium
  • linking 34 Italian Universities
  • main purpose: to foster research activity and provide networking support to specific projects in the area of telecommunications
  • 3 universities participating to Newcom Dept.1: Milan, Padova, and Bologna





University of Padova

Department of Information Engineering (DEI)

  • Active engineering degrees in:
    • Automation engineering
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    • Computer engineering - even teleteaching
    • Telecommunications
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    • Industrial engineering (Chemistry, Mechanical, Electrical), Civil Engineering, Business
    • Faculty of Medicine
    • Faculty of Psychology
    • Faculty of Science of communications
    • Faculty of Statistics
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  • Academic and Research Personnel
    • 82 Professors
    • 92 PhD students and researchers
  • Staff
    • 16 Administrative units
    • 15 Technicians
  • Students
    • 3700 Students
competence 1 coded mimo ofdm 1 2
Competence # 1Coded MIMO-OFDM (1/2)
  • Design of improved MIMO radio interfaces for OFDM modulated systems
    • Space-time bit-interleaved coded modulation
    • Performance evaluation
    • Transmitter design
    • Efficient receiver implementation
offers for cooperation 1 coded mimo ofdm 2 2
Offers for Cooperation # 1Coded MIMO-OFDM (2/2)
  • Coding for OFDMA systems
  • Besides OFDM, we are interested to other schemes
    • Single carrier transmissions with cyclic prefix insertion (CP-SC)
    • Multicarrier modulators adopting shaping filters (Shaped-OFDM, Windowed OFDM, OFDM-OQAM, and Filtered Multitone)
  • Comparisons among these solutions
    • Performance evaluation
    • Transmitter and receiver design
    • Low complexity solutions
    • Extension to OFDMA environments
competence 2 single carrier mimo
Competence # 2Single CarrierMIMO
  • Linear and non-linear precoding schemes for the MIMO broadcast channel (MIMO-BC)
    • Achieving performance close to “dirty paper” coding
      • Vector precoding with peak power reduction
      • Study of the optimal beamformer for lattice precoding schemes
      • Comparison between Tomlinson-Harashima based precoders and vector-perturbation techniques for MIMO channels
  • Low-complexity joint detectors for SC-MIMO systems
    • Frequency-domain algorithms for multi-stream interference cancellation (BLAST)
competence 3 mimo mc cdma
Competence # 3MIMO MC-CDMA
  • Design of receivers for MC-CDMA systems
    • Soft interference cancellation techniques
  • Pre-equalization techniques for MC-CDMA systems
    • Multi-user pre-equalization for downlink MISO
    • Single user pre-equalization for uplink
  • DSP platform for MC-CDMA
    • Software defined radio platform with
      • DSP Texas Instruments C6400
      • Dual ADC and DAC
      • FPGA
    • Algorithms and DSP code to be implemented
offers for cooperation 2 3 mimo mc cdma
Offers for Cooperation # 2-3MIMO MC-CDMA
  • Receivers design for MIMO multi-user MC-CDMA systems
    • Investigation on V-BLAST receivers for multiple-input multiple-output (MIMO) extended to multi-user MC-CDMA systems
    • In particular, the work will focus on finding suitable ordering criteria to demodulate symbols and streams of each user
    • In uplink coded MC-CDMA systems, possible schemes to iteratively combine V-BLAST detection and decoding will be investigated (turbo principle)
  • Pre-coded MIMO MC-CDMA systems
    • Investigation on non-linear precoding schemes for downlink
competence 4 cross layer optimization
Competence # 4Cross Layer Optimization
  • Design of new architectures for performance optimization in wireless networks using a cross layer approach
    • Quality of service management
    • Resource allocation
    • Cognitive radio concept
    • Opportunistic scheduling
  • Interference analysis
    • Multi-cell environment
    • Intra-inter cell interference analysis
    • Near capacity performance
    • High reuse factor
ongoing collaborations within newcom
Ongoing Collaborations within Newcom
  • Joint activity with EURECOM (G. Caire)
    • F. Boccardi and G. Caire, “The p-sphere encoder: peak power reduction by lattice precoding for the MIMO-BC,” Globecom 2005
    • F. Boccardi and G. Caire, "Precoding with Low Peak-Power for the MIMO Gaussian Broadcast Channel”,  Allerton Conference, Sept. 2005.
  • Joint activity with KTH (M. Bengtsson)
    • M. Butussi and M. Bengtsson, “Low Complexity Admission in Downlink Beamfrorming,” Submitted to ICASSP, Toulouse, France, May 2006.
  • Joint activity with ETH (H. Bölcskei)
    • At the beginning of December 2005 a researcher is going to visit ETH University (Communication Theory Group)
low complexity in downlink beamforming
Low Complexity in Downlink Beamforming
  • Consider the downlink of a system where N-1 single antenna mobile are served by one or more base stations, each equipped with an antenna array

When a new user enters the system

The system only modifies the power allocation for the existing user, not the spatial signature of the beamformers.

The algorithm is compared to jointly optimal solution, using the COST231 TU channel model, a carrier frequency fo 2.4 MHz, a 500m cell radius and assuming a single base station equipped with 4 element uniform linear array

numerical results 1 2
Numerical Results (1/2)

Outage probability when adding a new user to a sytem with 4 and 5 existing users

numerical results 2 2
Numerical Results (2/2)

CDF of difference in total power between out proposed and joint optimum when a new user has been added to 4 and 5 existing users

  • Te user that can be admitted to the system using joint optimal downlink beamforming can almost always also be admitted using this low complexity algorithm, at least if there is a limit on the transmit power


  • Martin Schubert and Holger Boche, ”Solution of the multiuser downlink beamforming problem with individual SINR constraints” IEEE Trans. VT, vol 53, no 1, pp 18 -28, Jan 2004
people involved

Giambattista Carnevale

SC Precoding MIMO

Federico Boccardi

Implementation Aspects

Roberto Corvaja

People involved
  • Team Head
    • Prof. Silvano Pupolin
  • Newcom - Dept. 1
    • Prof. Nevio Benvenuto
    • Tomaso Erseghe
  • Newcom Cluster 2
    • Antonio Assalini

phone: +39.049.827.7752