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My primary research interest is Cross-layer Optimization for Multiuser Multiple-Input Multiple-Output (MIMO) networks with interference. Currently, I am focusing on the joint optimization between physical layer, link/MAC layer, and routing layer for various networks settings with co-channel interfered MIMO links. The objective of my research is to understand the fundamental issues of interference-limited multiuser MIMO systems, design centralized and distributed algorithms for finding optimal solutions, and most importantly, provide information-theoretic insights for MIMO systems design.
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1. Multiuser MIMO Ad Hoc Networks with Interference
Maximizing the total mutual information of multiuser multiple-input multiple-output (MIMO) systems with interference is a well-known and challenging problem. In this project, we consider the power control problem of finding the maximum sum of mutual information for \emph{ad hoc} networks with mutually interfered MIMO links. We propose a new and powerful global optimization method using a branch-and-bound framework coupled with the reformulation-linearization technique (BB/RLT). The proposed BB/RLT is the first such method that guarantees finding a global optimum for multiuser MIMO systems with interference. To reduce the complexity of BB/RLT, we propose a modified branch-and-bound (BB) variable selection strategy to accelerate the convergence process. Numerical examples are also given to demonstrate the efficiency of the proposed solution.
2. Cross-Layer Optimization of Multiuser MIMO Networks
Cross-layer optimization on multipath/multihop routing and power control/allocation in wireless ad hoc networks with co-channel interfered MIMO links is a more challenging problem, and very little research has been conducted in this area thus far. To solve this problem, we develop a mathematical solution procedure, which combines Lagrangian decomposition method, gradient projection method, and subgradient method. We also propose an algorithm to recover high quality primal feasible solutions from the Lagrangian dual problem. To demonstrate the efficacy of our proposed solution procedure, we compare the performance of our Lagrangian dual method and that of a heuristic method, where the network layer performs shortest hop routing and the link layer employs independent water-filling, respectively. Numerical results show that our proposed solution procedure is consistently and significantly better than the heuristic that does not take cross-layer optimization into consideration.
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