Z. Mohammadi;M. Soleimanpour Moghadam;S. Talebi;H. Ahmadi
{"title":"共享频谱合作网络:基于线性规划的方法","authors":"Z. Mohammadi;M. Soleimanpour Moghadam;S. Talebi;H. Ahmadi","doi":"10.1109/LNET.2024.3350434","DOIUrl":null,"url":null,"abstract":"This letter investigates a desirable power allocation scheme for shared spectrum networks and formulate it as a constrained optimization model that falls into the nonlinear class fractional programming problems. The investigation focuses on different solutions for the problem under consideration. The first investigated approach utilizes the convex optimization problem (COP) equivalent from of the problem by employing the Charnes-Cooper transformation. This approach finds the optimal solution and thus is the most appropriate from a viewpoint of optimality. The second approach employs the approximate linear programming (LP). From the complexity point of view, the LP problem can be cast as the benchmark. Our proposed linear model has lower complexity with an acceptable accuracy leading to decreasing the time delay to make the final decision on the availability. Simulation results indicate a higher coherence between the two latter approaches and the superior performance than the state-of-the-art literature in different system parameter.","PeriodicalId":100628,"journal":{"name":"IEEE Networking Letters","volume":"6 2","pages":"77-81"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shared Spectrum Cooperative Networks: A Linear Programming-Based Approach\",\"authors\":\"Z. Mohammadi;M. Soleimanpour Moghadam;S. Talebi;H. Ahmadi\",\"doi\":\"10.1109/LNET.2024.3350434\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter investigates a desirable power allocation scheme for shared spectrum networks and formulate it as a constrained optimization model that falls into the nonlinear class fractional programming problems. The investigation focuses on different solutions for the problem under consideration. The first investigated approach utilizes the convex optimization problem (COP) equivalent from of the problem by employing the Charnes-Cooper transformation. This approach finds the optimal solution and thus is the most appropriate from a viewpoint of optimality. The second approach employs the approximate linear programming (LP). From the complexity point of view, the LP problem can be cast as the benchmark. Our proposed linear model has lower complexity with an acceptable accuracy leading to decreasing the time delay to make the final decision on the availability. Simulation results indicate a higher coherence between the two latter approaches and the superior performance than the state-of-the-art literature in different system parameter.\",\"PeriodicalId\":100628,\"journal\":{\"name\":\"IEEE Networking Letters\",\"volume\":\"6 2\",\"pages\":\"77-81\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Networking Letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10382184/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Networking Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10382184/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Shared Spectrum Cooperative Networks: A Linear Programming-Based Approach
This letter investigates a desirable power allocation scheme for shared spectrum networks and formulate it as a constrained optimization model that falls into the nonlinear class fractional programming problems. The investigation focuses on different solutions for the problem under consideration. The first investigated approach utilizes the convex optimization problem (COP) equivalent from of the problem by employing the Charnes-Cooper transformation. This approach finds the optimal solution and thus is the most appropriate from a viewpoint of optimality. The second approach employs the approximate linear programming (LP). From the complexity point of view, the LP problem can be cast as the benchmark. Our proposed linear model has lower complexity with an acceptable accuracy leading to decreasing the time delay to make the final decision on the availability. Simulation results indicate a higher coherence between the two latter approaches and the superior performance than the state-of-the-art literature in different system parameter.