{"title":"基于MRC检测器的多单元大规模MIMO的能源效率资源优化","authors":"K. N. R. Surya, V. Prasad, V. Bhargava","doi":"10.1109/WCNC.2016.7564657","DOIUrl":null,"url":null,"abstract":"In this paper, resource allocation for energy-efficient communications in a pilot-contaminated uplink multi-cell massive MIMO system with MRC detectors is investigated. The problem of maximizing energy efficiency (EE) of data transmissions in the system is studied by optimizing the number of antennas per BS, the pilot signal power, and the data signal power. The considered optimization problem takes into account the circuit power consumption, pilot contamination, and budget constraints in the number of antennas per Base Station (BS) and the average transmission power per symbol. The resulting optimization problem has a non-convex fractional objective function which is difficult to solve in its original form. Therefore, principles from fractional programming are used to first transform the problem into an equivalent parametric form and then to derive an iterative resource allocation algorithm. In each iteration, an alternating optimization technique is used to solve the objective function by decomposing it into a sequence of solvable difference of convex (D.C) programming subproblems. Simulation results show that higher EE levels can be achieved by optimizing the pilot and data powers separately. Also, increasing the number of antennas per BS with the power budget may or may not be energy-efficient, depending on the range of operation.","PeriodicalId":436094,"journal":{"name":"2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Resource optimization for energy efficiency in multi-cell massive MIMO with MRC detectors\",\"authors\":\"K. N. R. Surya, V. Prasad, V. Bhargava\",\"doi\":\"10.1109/WCNC.2016.7564657\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, resource allocation for energy-efficient communications in a pilot-contaminated uplink multi-cell massive MIMO system with MRC detectors is investigated. The problem of maximizing energy efficiency (EE) of data transmissions in the system is studied by optimizing the number of antennas per BS, the pilot signal power, and the data signal power. The considered optimization problem takes into account the circuit power consumption, pilot contamination, and budget constraints in the number of antennas per Base Station (BS) and the average transmission power per symbol. The resulting optimization problem has a non-convex fractional objective function which is difficult to solve in its original form. Therefore, principles from fractional programming are used to first transform the problem into an equivalent parametric form and then to derive an iterative resource allocation algorithm. In each iteration, an alternating optimization technique is used to solve the objective function by decomposing it into a sequence of solvable difference of convex (D.C) programming subproblems. Simulation results show that higher EE levels can be achieved by optimizing the pilot and data powers separately. Also, increasing the number of antennas per BS with the power budget may or may not be energy-efficient, depending on the range of operation.\",\"PeriodicalId\":436094,\"journal\":{\"name\":\"2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC.2016.7564657\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC.2016.7564657","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Resource optimization for energy efficiency in multi-cell massive MIMO with MRC detectors
In this paper, resource allocation for energy-efficient communications in a pilot-contaminated uplink multi-cell massive MIMO system with MRC detectors is investigated. The problem of maximizing energy efficiency (EE) of data transmissions in the system is studied by optimizing the number of antennas per BS, the pilot signal power, and the data signal power. The considered optimization problem takes into account the circuit power consumption, pilot contamination, and budget constraints in the number of antennas per Base Station (BS) and the average transmission power per symbol. The resulting optimization problem has a non-convex fractional objective function which is difficult to solve in its original form. Therefore, principles from fractional programming are used to first transform the problem into an equivalent parametric form and then to derive an iterative resource allocation algorithm. In each iteration, an alternating optimization technique is used to solve the objective function by decomposing it into a sequence of solvable difference of convex (D.C) programming subproblems. Simulation results show that higher EE levels can be achieved by optimizing the pilot and data powers separately. Also, increasing the number of antennas per BS with the power budget may or may not be energy-efficient, depending on the range of operation.