Efficient computation of the Pareto boundary for the two-user single-stream MIMO interference channel

We consider a two-user multiple-input multiple-output (MIMO) interference channel (IC), where a single data stream is transmitted and each receiver applies the minimum mean square error (MMSE) filter. In this paper, we study an open problem on the computation of the Pareto boundary of the achievable rate region by optimal joint transmit/receive beamforming design. The Pareto boundary can be divided by two turning points into the weak Pareto boundary and the strict Pareto boundary. The weak Pareto boundary and turning points can be computed exactly. For the strict Pareto boundary, we propose a computationally efficient method called iterative alternating algorithm (IAA) to maximize the rate of one user while the rate of the other user is fixed. Numerical simulations show that the IAA provides a better lower bound on the strict Pareto boundary compared with the existing methods.

[1]  Erik G. Larsson,et al.  Complete Characterization of the Pareto Boundary for the MISO Interference Channel , 2008, IEEE Transactions on Signal Processing.

[2]  Shuzhong Zhang,et al.  New results on Hermitian matrix rank-one decomposition , 2011, Math. Program..

[3]  Zhi-Quan Luo,et al.  Semidefinite Relaxation of Quadratic Optimization Problems , 2010, IEEE Signal Processing Magazine.

[4]  W W Cooper,et al.  PROGRAMMING WITH LLINEAR FRACTIONAL , 1962 .

[5]  Antonio De Maio,et al.  Semidefinite programming, matrix decomposition, and radar code design , 2010, Convex Optimization in Signal Processing and Communications.

[6]  Shuguang Cui,et al.  Optimal distributed beamforming for MISO interference channels , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

[7]  Erik G. Larsson,et al.  Efficient computation of the Pareto boundary for the MISO interference channel with perfect CSI , 2010, 8th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks.

[8]  Pan Cao,et al.  On the Pareto Boundary for the Two-User Single-Beam MIMO Interference Channel , 2012, ArXiv.

[9]  Shuguang Cui,et al.  Cooperative Interference Management With MISO Beamforming , 2009, IEEE Transactions on Signal Processing.

[10]  Robert W. Heath,et al.  Interference Aware-Coordinated Beamforming System in a Two-Cell Environment , 2009 .

[11]  Emil Björnson,et al.  Pareto Characterization of the Multicell MIMO Performance Region With Simple Receivers , 2011, IEEE Transactions on Signal Processing.

[12]  Daniel Pérez Palomar,et al.  Fractional QCQP With Applications in ML Steering Direction Estimation for Radar Detection , 2011, IEEE Transactions on Signal Processing.

[13]  Erik G. Larsson,et al.  Competition Versus Cooperation on the MISO Interference Channel , 2008, IEEE Journal on Selected Areas in Communications.

[14]  Zhi-Quan Luo,et al.  An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).