Vaishnavi Kasuluru, Luis Blanco, Miguel Angel Vazquez, Cristian J. Vaca-Rubio, Engin Zeydan
{"title":"在 SINR 约束条件下最大限度降低 O-RAN 中无蜂窝大规模多输入多输出的功耗","authors":"Vaishnavi Kasuluru, Luis Blanco, Miguel Angel Vazquez, Cristian J. Vaca-Rubio, Engin Zeydan","doi":"arxiv-2409.04135","DOIUrl":null,"url":null,"abstract":"This paper deals with the problem of energy consumption minimization in Open\nRAN cell-free (CF) massive Multiple-Input Multiple-Output (mMIMO) systems under\nminimum per-user signal-to-noise-plus-interference ratio (SINR) constraints.\nConsidering that several access points (APs) are deployed with multiple\nantennas, and they jointly serve multiple users on the same time-frequency\nresources, we design the precoding vectors that minimize the system power\nconsumption, while preserving a minimum SINR for each user. We use a simple,\nyet representative, power consumption model, which consists of a fixed term\nthat models the power consumption due to activation of the AP and a variable\none that depends on the transmitted power. The mentioned problem boils down to\na binary-constrained quadratic optimization problem, which is strongly\nnon-convex. In order to solve this problem, we resort to a novel approach,\nwhich is based on the penalized convex-concave procedure. The proposed approach\ncan be implemented in an O-RAN cell-free mMIMO system as an xApp in the\nnear-real time RIC (RAN intelligent Controller). Numerical results show the\npotential of this approach for dealing with joint precoding optimization and AP\nselection.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Minimizing Power Consumption under SINR Constraints for Cell-Free Massive MIMO in O-RAN\",\"authors\":\"Vaishnavi Kasuluru, Luis Blanco, Miguel Angel Vazquez, Cristian J. Vaca-Rubio, Engin Zeydan\",\"doi\":\"arxiv-2409.04135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper deals with the problem of energy consumption minimization in Open\\nRAN cell-free (CF) massive Multiple-Input Multiple-Output (mMIMO) systems under\\nminimum per-user signal-to-noise-plus-interference ratio (SINR) constraints.\\nConsidering that several access points (APs) are deployed with multiple\\nantennas, and they jointly serve multiple users on the same time-frequency\\nresources, we design the precoding vectors that minimize the system power\\nconsumption, while preserving a minimum SINR for each user. We use a simple,\\nyet representative, power consumption model, which consists of a fixed term\\nthat models the power consumption due to activation of the AP and a variable\\none that depends on the transmitted power. The mentioned problem boils down to\\na binary-constrained quadratic optimization problem, which is strongly\\nnon-convex. In order to solve this problem, we resort to a novel approach,\\nwhich is based on the penalized convex-concave procedure. The proposed approach\\ncan be implemented in an O-RAN cell-free mMIMO system as an xApp in the\\nnear-real time RIC (RAN intelligent Controller). Numerical results show the\\npotential of this approach for dealing with joint precoding optimization and AP\\nselection.\",\"PeriodicalId\":501280,\"journal\":{\"name\":\"arXiv - CS - Networking and Internet Architecture\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Networking and Internet Architecture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.04135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Networking and Internet Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minimizing Power Consumption under SINR Constraints for Cell-Free Massive MIMO in O-RAN
This paper deals with the problem of energy consumption minimization in Open
RAN cell-free (CF) massive Multiple-Input Multiple-Output (mMIMO) systems under
minimum per-user signal-to-noise-plus-interference ratio (SINR) constraints.
Considering that several access points (APs) are deployed with multiple
antennas, and they jointly serve multiple users on the same time-frequency
resources, we design the precoding vectors that minimize the system power
consumption, while preserving a minimum SINR for each user. We use a simple,
yet representative, power consumption model, which consists of a fixed term
that models the power consumption due to activation of the AP and a variable
one that depends on the transmitted power. The mentioned problem boils down to
a binary-constrained quadratic optimization problem, which is strongly
non-convex. In order to solve this problem, we resort to a novel approach,
which is based on the penalized convex-concave procedure. The proposed approach
can be implemented in an O-RAN cell-free mMIMO system as an xApp in the
near-real time RIC (RAN intelligent Controller). Numerical results show the
potential of this approach for dealing with joint precoding optimization and AP
selection.