Interference Alignment for UWB-MIMO Communication Systems

Due to the enormous occupied bandwidth even by a single pair of UWB users, one major scientific challenge in UWB communications is interference management. Recently, Interference Alignment (IA) has become popular not only to well manage the interference, but also to optimally exploit the possible capacity gain caused by multiple pairs of transmitters and receivers. Theoretically, IA scales the channel capacity by K/2, where K is the number of user pairs. This fact makes IA highly attractive for future communication systems with numerous pairs of users. However, in the literature it has been reported that IA is not robust [7] against imperfections such as channel estimation errors. Thanks to the interdisciplinary research of antenna, communication and hardware engineers within the UKoLoS project Decimus, we were able to jointly search for solutions to improve IA robustness while not suffering from too perfect simulation idealities or too unrealistic hardware requirements. We find that antenna or pattern selection is a promising approach to improving the robustness of IA while keeping the underlying algorithms at a reasonable complexity and feasibility for implementation. Our contribution is structured as follows: first, a brief introduction of IA tailored to UWB is given. Then, we propose an antenna selection algorithm with low complexity and demonstrate its performance. In the third chapter a general methodology of MIMO UWB antenna design for orthogonal channels maximizing the channel capacity is presented. A first outcome of this methodology is a multi-mode orthogonal antenna which has been used for the investigated antenna selection approach. At last, the hardware requirements of IA systems with the proposed antenna selection method are studied. A conclusion summarizes the outcomes of our contribution.

[1]  David Middleton,et al.  Sampling and Reconstruction of Wave-Number-Limited Functions in N-Dimensional Euclidean Spaces , 1962, Inf. Control..

[2]  Peter Pirsch,et al.  Architectures for digital signal processing , 1998 .

[3]  Mohammad Ali Khalighi,et al.  Water filling capacity of Rayleigh MIMO channels , 2001, 12th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. PIMRC 2001. Proceedings (Cat. No.01TH8598).

[4]  Robert W. Heath,et al.  Antenna selection for spatial multiplexing systems with linear receivers , 2001, IEEE Communications Letters.

[5]  Michael A. Jensen,et al.  Intrinsic capacity of the MIMO wireless channel , 2002 .

[6]  Werner Wiesbeck,et al.  MIMO-capacity of bridge access points based on measurements and simulations for arbitrary arrays , 2003 .

[7]  David Gesbert,et al.  From theory to practice: an overview of MIMO space-time coded wireless systems , 2003, IEEE J. Sel. Areas Commun..

[8]  Sergey Loyka,et al.  Information theory and electromagnetism: Are they related? , 2004, 2004 10th International Symposium on Antenna Technology and Applied Electromagnetics and URSI Conference.

[9]  Moe Z. Win,et al.  Capacity of MIMO systems with antenna selection , 2001, IEEE Transactions on Wireless Communications.

[10]  W. Wiesbeck,et al.  Capability of 3-D Ray Tracing for Defining Parameter Sets for the Specification of Future Mobile Communications Systems , 2006, IEEE Transactions on Antennas and Propagation.

[11]  Gene H. Golub,et al.  Numerical methods for computing angles between linear subspaces , 1971, Milestones in Matrix Computation.

[12]  Syed Ali Jafar,et al.  Interference Alignment and Degrees of Freedom of the $K$-User Interference Channel , 2008, IEEE Transactions on Information Theory.

[13]  T. Kaiser,et al.  3D hybrid EM ray-tracing deterministic UWB channel model, simulations and measurements , 2008, 2008 IEEE International Conference on Ultra-Wideband.

[14]  Robert W. Heath,et al.  Interference alignment via alternating minimization , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[15]  R. Berry,et al.  Minimum Mean Squared Error interference alignment , 2009, 2009 Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers.

[16]  Peter Pirsch,et al.  Real-time stereo vision system using semi-global matching disparity estimation: Architecture and FPGA-implementation , 2010, 2010 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation.

[17]  Robert W. Heath,et al.  The Feasibility of Interference Alignment Over Measured MIMO-OFDM Channels , 2009, IEEE Transactions on Vehicular Technology.

[18]  Aki Happonen,et al.  Low-complexity Inverse Square Root Approximation for Baseband Matrix Operations , 2011 .

[19]  Thomas Zwick,et al.  Antenna optimization for time-variant MIMO systems , 2011, Proceedings of the 5th European Conference on Antennas and Propagation (EUCAP).

[20]  Zhi Ding,et al.  Best-Effort Interference Alignment in OFDM Systems with Finite SNR , 2011, 2011 IEEE International Conference on Communications (ICC).

[21]  José Antonio García-Naya,et al.  Experimental validation of Interference Alignment techniques using a multiuser MIMO testbed , 2011, 2011 International ITG Workshop on Smart Antennas.

[22]  Mohammed El-Absi,et al.  Antenna selection for Interference Alignment based on subspace Canonical Correlation , 2012, 2012 International Symposium on Communications and Information Technologies (ISCIT).

[23]  T. Zwick,et al.  Maximum capacity antenna design for an indoor MIMO-UWB communication system , 2012, ISAPE2012.

[24]  Thomas Kaiser,et al.  Artificial diversity for UWB MB-OFDM Interference Alignment based on real-world channel models and antenna selection techniques , 2012, 2012 IEEE International Conference on Ultra-Wideband.

[25]  Holger Blume,et al.  Hardware-accelerated design space exploration framework for communication systems , 2014 .