PROJECT TITLE :

Per-Stream MSE Based Linear Transceiver Design for MIMO Interference Channels With CSI Error

ABSTRACT:

This paper studies the linear transceiver style for multi-stream multiple-input-multiple-output (MIMO) interference channels with imperfect channel state info (CSI). Two CSI error models are thought-about. The identical coding and modulation scheme is assumed for all users and knowledge streams. In the primary model, where the CSI error is statistical, we have a tendency to minimize the average most per-stream mean sq. error (MSE). Within the second model, where the CSI error is norm bounded, the worst-case maximum per-stream MSE is optimized. Since the issues don't seem to be jointly convex, the alternate optimization approach is adopted to get suboptimal transceivers. For the statistical CSI error, a low-complexity algorithm utilizing Lagrangian duality is proposed, that encompasses a semi-closed form solution and will be implemented distributively. Compared with the classical algorithm using the second-order-cone programming, the proposed algorithm significantly reduces the computational complexity while not sacrificing the performance. For the bounded CSI error, we tend to gift 2 approaches. One uses S-procedure to get constant problem and the opposite one solves an approximated problem. Simulation results demonstrate the robustness of the proposed algorithms and their improved performance over the add-MSE and the most per-user MSE based strategies. The lower complexity of the Lagrangian duality based mostly algorithm is also verified numerically.