基于SDP松弛的干擾資源優(yōu)化分配技術研究
發(fā)布時間:2019-03-12 16:53
【摘要】:提出一種基于semidefinite programming(簡稱SDP)松弛的干擾資源優(yōu)化分配算法。在問題優(yōu)化過程中首先對模型中非凸的約束條件進行松弛,變?yōu)橥辜s束,將原來的數學模型轉化成SDP求解形式,利用內點算法對松弛后的模型求解。該算法利用解析的手段使得干擾資源優(yōu)化分配問題中的NP難問題在多項式時間內得以解決,并且有較高的可靠性。仿真結果驗證了算法的有效性。
[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.
【作者單位】: 電子工程學院;
【分類號】:TN972
,
本文編號: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.
【作者單位】: 電子工程學院;
【分類號】:TN972
,
本文編號:2438979
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