基于SDP松弛的干扰资源优化分配技术研究
发布时间：2019-03-12 16:53
【摘要】：提出一种基于semidefinite programming(简称SDP)松弛的干扰资源优化分配算法。在问题优化过程中首先对模型中非凸的约束条件进行松弛,变为凸约束,将原来的数学模型转化成SDP求解形式,利用内点算法对松弛后的模型求解。该算法利用解析的手段使得干扰资源优化分配问题中的NP难问题在多项式时间内得以解决,并且有较高的可靠性。仿真结果验证了算法的有效性。
[Abstract]:An optimal resource allocation algorithm based on semidefinite programming (SDP) relaxation is proposed. In the process of optimization, the non-convex constraints in the model are relaxed and changed into convex constraints. The original mathematical model is transformed into a SDP solution, and the relaxed model is solved by using the interior point algorithm. The algorithm makes use of analytic method to solve the difficult NP problem in the optimal allocation of interference resources in polynomial time, and has high reliability. Simulation results show that the algorithm is effective.
【作者单位】： 电子工程学院;
【分类号】：TN972
，
本文编号：2438979
[Abstract]:An optimal resource allocation algorithm based on semidefinite programming (SDP) relaxation is proposed. In the process of optimization, the non-convex constraints in the model are relaxed and changed into convex constraints. The original mathematical model is transformed into a SDP solution, and the relaxed model is solved by using the interior point algorithm. The algorithm makes use of analytic method to solve the difficult NP problem in the optimal allocation of interference resources in polynomial time, and has high reliability. Simulation results show that the algorithm is effective.
【作者单位】： 电子工程学院;
【分类号】：TN972
，
本文编号：2438979
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