The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this...The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)relay.First,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the relay.The original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution directly.First,we use fractional programming to convert the EE maximization problem as a series of subtraction form subproblems.Then,variable substitution and block coordinate descent(BCD)method are used to handle the sub-problems.Next,a resource allocation algorithm is proposed to maximize the EE of the systems.Finally,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.展开更多
研究基于能量采集的大规模多输入多输出(multiple-input multiple-output,MIMO)系统能效优化问题。保证用户服务质量、能量塔发射功率限制和能量采集时间约束下,为实现上行大规模MIMO系统能效最大化,对能量塔发射功率、能量采集时间进...研究基于能量采集的大规模多输入多输出(multiple-input multiple-output,MIMO)系统能效优化问题。保证用户服务质量、能量塔发射功率限制和能量采集时间约束下,为实现上行大规模MIMO系统能效最大化,对能量塔发射功率、能量采集时间进行联合优化。该问题属于非凸优化问题,首先通过分式规划理论将原优化问题等价转换,然后采用块坐标下降(block coordinate descent,BCD)方法,对能量塔发射功率、能量采集时间、系统能效进行迭代求解,提出了一种基于能量采集的大规模MIMO系统的联合优化能效算法(energy-efficient power and time allocation algorithm,EPTA)。仿真结果表明,在保证用户服务质量的情况下,与均时最小QoS保证算法(time-averaged minimum QoS guaranteed algorithm,TA-QoSA)、吞吐量资源分配算法(throughput maximization based power and time algorithm,TPTA)相比,该算法提高了系统能效。展开更多
将大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)技术与无线能量传输(Wireless Power Transfer,WPT)技术相结合,能够帮助实现节能降耗,契合国内外绿色通信发展浪潮。针对WPT技术在大规模MIMO研究领域的应用问题,总结了当前...将大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)技术与无线能量传输(Wireless Power Transfer,WPT)技术相结合,能够帮助实现节能降耗,契合国内外绿色通信发展浪潮。针对WPT技术在大规模MIMO研究领域的应用问题,总结了当前携能大规模MIMO技术的研究现状及发展趋势,从频效、能效、安全性等多个方面对携能大规模MIMO资源分配算法进行综述,探讨了学术界在携能大规模MIMO资源分配算法上的重要研究成果。在现有算法研究进展分析的基础上,对当前研究中携能大规模MIMO资源分配算法研究情况存在的问题进行分析,并对未来的发展方向进行了展望。展开更多
随着第五代移动通信技术(5th Generation Mobile Communication Technology,5G)网络的大规模商业化部署,超5G(Beyond 5G,B5G)和第六代移动通信技术(6th Generation Mobile Communication Technology,6G)逐渐成为研究热点。非正交多址接...随着第五代移动通信技术(5th Generation Mobile Communication Technology,5G)网络的大规模商业化部署,超5G(Beyond 5G,B5G)和第六代移动通信技术(6th Generation Mobile Communication Technology,6G)逐渐成为研究热点。非正交多址接入(Non-Orthogonal Multiple Access,NOMA)作为一种新型接入技术,有望成为B5G和6G网络中的关键多址接入技术。与此同时,多载波通信具有抗频率选择性衰落和高频谱效率的特点,因此将多载波技术与NOMA相结合成为B5G和6G的一个重要研究方向。从能效、功耗以及速率方面概述了多载波非协作NOMA、多载波协作NOMA的资源分配问题。探讨当前研究存在的一些缺陷与不足,并展望多载波NOMA系统资源分配问题的未来研究方向。展开更多
基金partially supported by the National Natural Science Foundation of China under Grant 61701064Chongqing Natural Science Foundation under Grant cstc2019jcyj-msxmX0264Sichuan Science and Technology Program under Grant 2022YFQ0017。
文摘The massive connectivity and limited energy pose significant challenges to deploy the enormous devices in energy-efficient and environmentally friendly in the Internet of Things(IoT).Motivated by these challenges,this paper investigates the energy efficiency(EE)maximization problem for downlink cooperative non-orthogonal multiple access(C-NOMA)systems with hardware impairments(HIs).The base station(BS)communicates with several users via a half-duplex(HD)amplified-and-forward(AF)relay.First,we formulate the EE maximization problem of the system under HIs by jointly optimizing transmit power and power allocated coefficient(PAC)at BS,and transmit power at the relay.The original EE maximization problem is a non-convex problem,which is challenging to give the optimal solution directly.First,we use fractional programming to convert the EE maximization problem as a series of subtraction form subproblems.Then,variable substitution and block coordinate descent(BCD)method are used to handle the sub-problems.Next,a resource allocation algorithm is proposed to maximize the EE of the systems.Finally,simulation results show that the proposed algorithm outperforms the downlink cooperative orthogonal multiple access(C-OMA)scheme.
文摘研究基于能量采集的大规模多输入多输出(multiple-input multiple-output,MIMO)系统能效优化问题。保证用户服务质量、能量塔发射功率限制和能量采集时间约束下,为实现上行大规模MIMO系统能效最大化,对能量塔发射功率、能量采集时间进行联合优化。该问题属于非凸优化问题,首先通过分式规划理论将原优化问题等价转换,然后采用块坐标下降(block coordinate descent,BCD)方法,对能量塔发射功率、能量采集时间、系统能效进行迭代求解,提出了一种基于能量采集的大规模MIMO系统的联合优化能效算法(energy-efficient power and time allocation algorithm,EPTA)。仿真结果表明,在保证用户服务质量的情况下,与均时最小QoS保证算法(time-averaged minimum QoS guaranteed algorithm,TA-QoSA)、吞吐量资源分配算法(throughput maximization based power and time algorithm,TPTA)相比,该算法提高了系统能效。
文摘将大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)技术与无线能量传输(Wireless Power Transfer,WPT)技术相结合,能够帮助实现节能降耗,契合国内外绿色通信发展浪潮。针对WPT技术在大规模MIMO研究领域的应用问题,总结了当前携能大规模MIMO技术的研究现状及发展趋势,从频效、能效、安全性等多个方面对携能大规模MIMO资源分配算法进行综述,探讨了学术界在携能大规模MIMO资源分配算法上的重要研究成果。在现有算法研究进展分析的基础上,对当前研究中携能大规模MIMO资源分配算法研究情况存在的问题进行分析,并对未来的发展方向进行了展望。
文摘随着第五代移动通信技术(5th Generation Mobile Communication Technology,5G)网络的大规模商业化部署,超5G(Beyond 5G,B5G)和第六代移动通信技术(6th Generation Mobile Communication Technology,6G)逐渐成为研究热点。非正交多址接入(Non-Orthogonal Multiple Access,NOMA)作为一种新型接入技术,有望成为B5G和6G网络中的关键多址接入技术。与此同时,多载波通信具有抗频率选择性衰落和高频谱效率的特点,因此将多载波技术与NOMA相结合成为B5G和6G的一个重要研究方向。从能效、功耗以及速率方面概述了多载波非协作NOMA、多载波协作NOMA的资源分配问题。探讨当前研究存在的一些缺陷与不足,并展望多载波NOMA系统资源分配问题的未来研究方向。
