Pseudo-Lattice Treatment for Subspace Aligned Interference Signals

In this paper, we propose a channel transformation technique for joint decoding of desired and interfering signals in an interference alignment scenario consisting of K users with multiple antennas. Our technique, i.e., pseudo-lattice treatment, is based on the compute-and-forward framework. Our technique can be implemented to provide decoding gains with low complexity for subspace aligned interference signals. We evaluate the performance of the system through simulations that show the performance gain attained by using our pseudo-lattice method over subspace decoding techniques for interference alignment in lowand medium-SNR conditions.

[1]  Frank R. Kschischang,et al.  An Algebraic Approach to Physical-Layer Network Coding , 2010, IEEE Transactions on Information Theory.

[2]  Shlomo Shamai,et al.  A layered lattice coding scheme for a class of three user Gaussian interference channels , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[3]  Abhay Parekh,et al.  The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels , 2008, IEEE Transactions on Information Theory.

[4]  Michael Gastpar,et al.  Compute-and-Forward: Harnessing Interference Through Structured Codes , 2009, IEEE Transactions on Information Theory.

[5]  Michael L. Overton,et al.  A quadratically convergent method for minimizing a sum of euclidean norms , 1983, Math. Program..

[6]  Jinho Choi,et al.  Interference Alignment over Lattices for MIMO Interference Channels , 2011, IEEE Communications Letters.

[7]  Giuseppe Caire,et al.  Integer-forcing interference alignment , 2013, 2013 IEEE International Symposium on Information Theory.

[8]  Syed Ali Jafar,et al.  Interference Alignment and Spatial Degrees of Freedom for the K User Interference Channel , 2007, 2008 IEEE International Conference on Communications.

[9]  Gregory W. Wornell,et al.  Lattice-reduction-aided detectors for MIMO communication systems , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[10]  Meir Feder,et al.  Signal codes , 2008, Proceedings 2003 IEEE Information Theory Workshop (Cat. No.03EX674).

[11]  Yinyu Ye,et al.  An Efficient Algorithm for Minimizing a Sum of Euclidean Norms with Applications , 1997, SIAM J. Optim..

[12]  Kyoung-Jae Lee,et al.  Linear precoder designs for K-user interference channels , 2010, IEEE Transactions on Wireless Communications.

[13]  Dirk Wübben,et al.  Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[14]  Michael L. Overton,et al.  An Efficient Primal-Dual Interior-Point Method for Minimizing a Sum of Euclidean Norms , 2000, SIAM J. Sci. Comput..

[15]  G. David Forney,et al.  Multidimensional constellations. II. Voronoi constellations , 1989, IEEE J. Sel. Areas Commun..

[16]  Syed Ali Jafar,et al.  Approaching the Capacity of Wireless Networks through Distributed Interference Alignment , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[17]  Meir Feder,et al.  Shaping methods for low-density lattice codes , 2009, 2009 IEEE Information Theory Workshop.