{"title":"多天线节点多中继干扰网络中的分布式多流波束形成","authors":"C. M. Yetis, Ronald Y. Chang","doi":"10.1109/ICCNC.2019.8685603","DOIUrl":null,"url":null,"abstract":"In this paper, multi-stream transmission in interference networks aided by multiple amplify-and-forward (AF) relays in the presence of direct links is studied. The objective is to minimize the sum power of transmitters and relays by distributed transmit beamforming optimization under the stream signal-to-interference-plus-noise-ratio (SINR) target constraints. We utilize alternating direction method of multipliers (ADMM) algorithm for distributed implementation. The optimization problem is a well-known non-convex NP-hard quadratically constrained quadratic program (QCQP), which, after semi-definite relaxation (SDR), can be optimally solved via ADMM. The convergence rate, computational complexity, and message exchange load of the proposed algorithm are shown to outperform the existing distributed algorithm.","PeriodicalId":161815,"journal":{"name":"2019 International Conference on Computing, Networking and Communications (ICNC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distributed Multi-Stream Beamforming in Multi-Relay Interference Networks with Multi-Antenna Nodes\",\"authors\":\"C. M. Yetis, Ronald Y. Chang\",\"doi\":\"10.1109/ICCNC.2019.8685603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, multi-stream transmission in interference networks aided by multiple amplify-and-forward (AF) relays in the presence of direct links is studied. The objective is to minimize the sum power of transmitters and relays by distributed transmit beamforming optimization under the stream signal-to-interference-plus-noise-ratio (SINR) target constraints. We utilize alternating direction method of multipliers (ADMM) algorithm for distributed implementation. The optimization problem is a well-known non-convex NP-hard quadratically constrained quadratic program (QCQP), which, after semi-definite relaxation (SDR), can be optimally solved via ADMM. The convergence rate, computational complexity, and message exchange load of the proposed algorithm are shown to outperform the existing distributed algorithm.\",\"PeriodicalId\":161815,\"journal\":{\"name\":\"2019 International Conference on Computing, Networking and Communications (ICNC)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computing, Networking and Communications (ICNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCNC.2019.8685603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computing, Networking and Communications (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCNC.2019.8685603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed Multi-Stream Beamforming in Multi-Relay Interference Networks with Multi-Antenna Nodes
In this paper, multi-stream transmission in interference networks aided by multiple amplify-and-forward (AF) relays in the presence of direct links is studied. The objective is to minimize the sum power of transmitters and relays by distributed transmit beamforming optimization under the stream signal-to-interference-plus-noise-ratio (SINR) target constraints. We utilize alternating direction method of multipliers (ADMM) algorithm for distributed implementation. The optimization problem is a well-known non-convex NP-hard quadratically constrained quadratic program (QCQP), which, after semi-definite relaxation (SDR), can be optimally solved via ADMM. The convergence rate, computational complexity, and message exchange load of the proposed algorithm are shown to outperform the existing distributed algorithm.