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K-node connected power efficient topologies in wireless networks: a semidefinite programming approach

机译:无线网络中的K节点连接的高能效拓扑:一种半定程序设计方法

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We consider the problem of survivable minimum power bidirectional topology optimization in wireless networks. Two optimization problems are considered, minimization of the total transmit power and minimization of the maximum transmit power, subject to arbitrary K-node connectivity constraints. In this paper, we take an algebraic view of graph connectivity which is defined as the second smallest eigenvalue of the Laplacian matrix of a graph. Since the algebraic connectivity of a graph is known to be a lower bound on its node and edge connectivities, we impose a constraint on the algebraic connectivity to ensure that the solution is K-connected. Given the special properties of the Laplacian matrix of a graph, it is possible to express the algebraic connectivity requirement as a positive semidefinite constraint. Using this result, we show how the optimization problems can be formulated as 0/1 semidefinite programs (SDP's), which can be solved exactly using an SDP solver within a branch-and-bound framework. Linear and semidefinite relaxations of the 0/1 constraints are also discussed. These relaxations are useful for generating lower bounds on the exact 0/1 SDP models.
机译:我们考虑了无线网络中可生存的最小功率双向拓扑优化问题。考虑了两个优化问题,即总发射功率的最小化和最大发射功率的最小化,这取决于任意的K节点连接性约束。在本文中,我们采用图连通性的代数视图,其被定义为图的拉普拉斯矩阵的第二最小特征值。由于已知图的代数连通性是其节点和边缘连通性的下限,因此我们对代数连通性施加了约束,以确保解决方案是K连通的。给定图的拉普拉斯矩阵的特殊性质,可以将代数连通性要求表示为正半定约束。使用此结果,我们显示了如何将优化问题表达为0/1半定程序(SDP),可以在分支定界框架内使用SDP求解器精确地解决这些问题。还讨论了0/1约束的线性和半确定松弛。这些松弛对于在精确的0/1 SDP模型上生成下界很有用。

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