{"title":"Distributed fractional programming in matched multiple access channels","authors":"A. Zappone, Eduard Axel Jorswieck, Amir Leshem","doi":"10.1109/SAM.2016.7569619","DOIUrl":null,"url":null,"abstract":"This work deals with the problem of distributed resource allocation in MIMO MC MAC networks. The assignment between users and subcarriers is allocated together with the users' transmit powers for energy efficiency maximization, by means of a novel approach which merges the popular Dinkelbach's algorithm with stable matching. A distributed algorithm is presented, which can be implemented in a fully decentralized way. The algorithm has low computational complexity which comes at the price of weaker optimality properties. Additionally, a novel energy consumption model, which explicitly accounts for the energy consumption due to feedback transmissions, is employed and it is shown that the proposed distributed algorithm can improve the energy efficiency compared to state of the art centralized resource allocation algorithms.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAM.2016.7569619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This work deals with the problem of distributed resource allocation in MIMO MC MAC networks. The assignment between users and subcarriers is allocated together with the users' transmit powers for energy efficiency maximization, by means of a novel approach which merges the popular Dinkelbach's algorithm with stable matching. A distributed algorithm is presented, which can be implemented in a fully decentralized way. The algorithm has low computational complexity which comes at the price of weaker optimality properties. Additionally, a novel energy consumption model, which explicitly accounts for the energy consumption due to feedback transmissions, is employed and it is shown that the proposed distributed algorithm can improve the energy efficiency compared to state of the art centralized resource allocation algorithms.
本文研究了MIMO MC - MAC网络中的分布式资源分配问题。该方法将常用的Dinkelbach算法与稳定匹配相结合,结合用户的发射功率对用户和子载波的分配进行优化,以实现效率最大化。提出了一种分布式算法,可以完全去中心化地实现。该算法具有较低的计算复杂度,但代价是较弱的最优性。此外,采用了一种新的能源消耗模型,该模型明确考虑了反馈传输造成的能源消耗,结果表明,与目前最先进的集中式资源分配算法相比,所提出的分布式算法可以提高能源效率。