无线供能反向散射通信中能耗最小化资源分配方法

针对无线供能反向散射通信网络,提出了一种满足传感设备通信需求及能量因果的专用能量站能耗最小化资源分配方法。在考虑非线性能量收集模型及不完美串行干扰消除基础上,通过联合优化专用能量站发射功率、传感设备反向散射通信时间、反向散射系数及其能量收集时间,构建了一个专用能量站能耗最小化的非凸多维资源分配问题。首先,构建辅助变量对反向散射系数与时间进行解耦,再利用目标函数是关于专用能量站发射功率的单调递减函数这一特性来设计一种基于二分法的迭代算法来获取原问题的最优解。仿真验证了所提算法的快速收敛性,同时,与同类算法相比,所提方法可为专用能量站节约更多的能量。     

云无线接入网络高能效功率分配和波束成形联合优化算法

针对云无线接入网络(C-RAN)的资源分配问题,该文采用max-min公平准则作为优化准则,以C-RAN用户的能量效率作为优化目标函数,在满足最大发射功率和最小传输速率约束条件下,通过最大化最差链路的能量效率来实现用户发射功率和无线远端射频单元(RRHs)波束成形向量的联合优化。上述优化问题属于非线性、分式规划问题,为了方便求解,首先将原优化问题转化为差分形式的优化问题,然后通过引入变量将差分形式的、非平滑优化问题转化为平滑优化问题。最终,提出一种双层迭代功率分配和波束成形算法。在仿真实验中,将该文算法与传统的非能效资源分配算法和能量效率最大化算法进行了比较,实验结果证明该文算法在改进C-RAN能量效率和提高资源分配公平性方面的有效性。     

Energy efficiency optimization algorithm for heterogeneous NOMA network based on imperfect CSI

In order to improve the suppression capability of parametric perturbation and energy efficiency (EE) of heterogeneous networks (HetNets),a robust resource allocation algorithm was proposed to maximize system EE for reducing cross-tier interference power in non-orthogonal multiple access (NOMA) based HetNets.Firstly,the resource optimization problem was formulated as a mixed integer and nonlinear programming one under the constraints of the interference power of macrocell users,maximum transmit power of small cell base station (BS),resource block assignment and the quality of service (QoS) requirement of each small cell user.Then,based on ellipsoid bounded channel uncertainty models,the original problem was converted into the equivalent convex optimization problem by using the convex relaxation method,Dinkelbach method and the successive convex approximation (SCA) method.The analytical solutions were obtained by using the Lagrangian dual approach.Simulation results verifiy that the proposed algorithm had better EE and robustness by comparing it with the existing algorithm under perfect channel state information.     

多标签无线供电反向散射通信网络能效优化算法

为了提高物联网(IoT)节点的运行周期和能量利用率,该文提出一种多标签无线供电反向散射通信网络能效最大化资源分配算法。考虑传输速率约束、能量收集约束以及发射功率约束,建立了基于系统能效最大化的资源分配模型。利用Dinkelbach理论、2次变换以及变量替换法,将原分式非凸问题转化为可求解的凸优化问题。通过拉格朗日对偶理论求得优化问题的全局最优解。仿真结果表明,该算法具有较好的收敛性和能效。     

Robust resource allocation for NOMA-assisted heterogeneous networks

As a promising technology to improve spectrum efficiency and transmission coverage, Heterogeneous Network (HetNet) has attracted the attention of many scholars in recent years. Additionally, with the introduction of the Non-Orthogonal Multiple Access (NOMA) technology, the NOMA-assisted HetNet cannot only improve the system capacity but also allow more users to utilize the same frequency band resource, which makes the NOMA-assisted HetNet a hot topic. However, traditional resource allocation schemes assume that base stations can exactly estimate direct link gains and cross-tier link gains, which is impractical for practical HetNets due to the impact of channel delays and random perturbation. To further improve energy utilization and system robustness, in this paper, we investigate a robust resource allocation problem to maximize the total Energy Efficiency (EE) of Small-Cell Users (SCUs) in NOMA-assisted HetNets under imperfect channel state information. By considering bounded channel uncertainties, the robust resource optimization problem is formulated as a mixed-integer and nonlinear programming problem under the constraints of the cross-tier interference power of macrocell users, the maximum transmit power of small base station, the Resource Block (RB) assignment, and the quality of service requirement of each SCU. The original problem is converted into an equivalent convex optimization problem by using Dinkelbach's method and the successive convex approximation method. A robust Dinkelbach-based iteration algorithm is designed by jointly optimizing the transmit power and the RB allocation. Simulation results verify that the proposed algorithm has better EE and robustness than the existing algorithms.     

User-centric energy efficiency fairness in backscatter-assisted wireless powered communication network

In order to address the unfair user-centric energy efficiency (EE) problem caused by channel difference in the backscatter-assisted wireless powered communication network,a resource allocation scheme was proposed.Firstly,a mixed integer nonconvex fractional programming problem was formulated to maximize the minimum user-centric EE,subject to the quality of service and energy-causality constraints.Based on the generalized fractional programming theory,the original problem was transformed into a mixed integer nonconvex subtraction problem.With the aid of the slack variable,the proof by contradiction,the auxiliary variable and the mixed integer nonconvex subtraction problem were further transformed into an equivalent convex problem.Finally,an iterative algorithm was proposed to obtain the optimal solutions.Computer simulations validated the quick convergence of the proposed iterative algorithm,and that the developed resource allocation scheme efficiently guarantees the fairness among users in terms of EE.     

基于上行多用户大规模MIMO系统能效优化算法

针对上行多用户大规模多输入多输出（MIMO）系统,提出了基于能效优化的资源分配方法。所提方法采用迫零(ZF)接收,以最大化系统能效下界为准则,系统功率消耗考虑电路功率消耗和发射功率消耗2部分,通过联合调整基站端的发射天线数和用户的数据速率来优化能效函数。首先,根据目标函数的性质,证明全局最优速率分配和天线数的存在性和唯一性,然后,根据分数规划的性质,把原始的分数最优化问题转换成减式形式,进而提出一种新的迭代算法。仿真结果表明,所提算法以较少迭代次数取得了接近最优算法的性能。     

Massive MIMO异构网的高能效资源分配

为满足第五代移动通信系统高频谱效率和高能量效率的需求,提出一种工作在不同频段下行两层异构网中的高能量效率资源分配方法,考虑用户数据率需求和基站最大发射功率。天线和传输带宽是影响系统能量效率的关键因素。通过研究宏基站和小基站的天线资源和带宽分配发现:当系统天线数很大时,发射功耗的影响可以忽略不计;给定带宽分配因子时,达到宏基站或微基站最大发射功率的天线分配因子几乎可以达到最高能效;给定天线分配因子时,系统平均总功耗是关于带宽分配因子的下凸函数,存在全局最优带宽分配因子使能效最高。仿真结果表明,与给定带宽和天线资源的异构网和小小区网络相比,所提出的异构网可以显著提高系统能量效率,而且在大量用户、高数据率需求时能效提升更明显。      

Spectrum efficiency sub-carrier and energy efficiency power allocation for downlink multi-user CoMP in multi-cell system

Coordinated multi-point transmission/reception （CoMP） was proposed currently as an effective technology to improve cell-edge throughput in next-generation wireless systems. Most of the existing work discussed clustering methods mostly to maximize the edge user throughput while neglecting the problem of energy efficiency, such as those algorithm clustering base stations （BSs） of better channel condition and BSs of worse channel condition together. In addition, BSs usually increase the transmit power to achieve higher throughput without any considering of interference caused to other users, that may result in energy waste. The authors focus on the throughput maximizing problem while fully considering energy saving problem in CoMP systems. A coefficient is defined to describe the fitness of clusters. Then a sub-carrier allocation algorithm with clustering method is put forward for CoMP downlink, which can save the transmit power of BS and increase the throughput. Furthermore a power allocation scheme is proposed based on non-cooperation game; in which the transmit power is decreased by BSs generally to reach the Nash equation （NE）. Simulation shows that the proposed sub-carrier allocation scheme and power allocation algorithm are better than the existing ones on users＇ throughput while consumes much less energy.     

基于能量效率的分布式星群下行链路功率分配方法研究

针对多波束卫星通信系统星上资源稀缺和能量利用效率不高的问题,本文提出了分布式星群网络下行链路中兼顾系统功耗和数据速率的功率分配方法,通过合理的资源分配来优化系统的能量效率.首先建立分布式星群功率分配模型,将复杂的分式问题转化为易于求解的减法形式问题,然后基于凸优化理论,提出功耗-数据速率权衡功率分配算法,并讨论了能量效率（energy efficiency）与频谱效率（spectral efficiency）之间的权衡关系.仿真结果验证了提出算法的有效性和EE-SE权衡关系,并分析了电路功耗对系统性能的影响.     

认知小蜂窝网络中基于干扰温度限制的下行能效资源分配算法

为最大化认知小蜂窝基站的能量效率,本文基于博弈论模型分析了下行联合频谱资源块和功率分配行为.在干扰受限环境下,多个基站采用分布式结构共享空闲频谱资源.为避免累加干扰损害主用户的通信,算法中引入了功率和干扰温度限制.由于具有耦合限制的分数形式的能量效用函数是非凸最优的,通过将其转化为等价的减数形式进行迭代求解.给定频谱资源块分配策略后,主博弈模型可被重新建模为便于求解发射功率的等价子博弈模型,并通过代价的形势解除耦合限制.仿真结果表明,本文所提算法能够收敛到纳什均衡,并有效提高了系统资源利用率和能量效率.     

Energy efficient power allocation for co-located antenna systems with D2D communication

This paper investigates the energy efficient resource allocation when adding dedicated device-to-device (D2D) communication in the co-located antenna systems (CAS). We consider the user equipments (UEs) are changing over time and the appropriate potential UEs to form D2D pairs are varying with time. Our optimization objective is to maximize the system’s energy efficiency (EE) with the constraints of the maximum transmit power of UEs and D2D pairs in different total power consumption models. Firstly, an algorithm is developed to choose appropriate potential UEs to form D2D pairs in this paper. Then we exploit fractional programming method to obtain optimal energy efficient power allocation solutions. Simulation results are provided to demonstrate the effectiveness of the developed D2D pairs choosing algorithm and the power allocation algorithm.     

基于NOMA的无线携能D2D通信鲁棒能效优化算法

针对频谱短缺、基站负荷过高、通信系统功耗较大等问题,考虑不完美的信道状态信息,该文提出一种基于非正交多址接入的无线携能(SWIPT)D2D网络鲁棒能效(EE)最大化资源分配算法(SREA).考虑用户的服务质量约束以及最大发射功率约束,基于随机信道不确定性建立鲁棒能效最大化资源分配模型.利用Dinkelbach和变量替换方法,将原NP-hard问题转换为确定性的凸优化问题,通过拉格朗日对偶理论求得解析解.仿真结果表明,所提算法在保证蜂窝用户通信质量的同时,能够有效提高D2D用户的能效性和鲁棒性能.     

认知小蜂窝网络中基于能效的下行资源分配算法

在认知小蜂窝网络框架下,对基于OFDMA技术的下行联合频谱资源块和功率分配问题进行了研究。小蜂窝基站在分布式结构下采用开放式接入方式共享空闲频谱资源以最大化其能量效率,基站间的竞争关系使系统资源的动态分配过程可建模为非合作博弈模型。由于最大化具有多个限制条件的分数形势的能量效用函数属于非凸最优问题,可通过将其转化为等价的减数形势,并从串行和并行迭代的角度进行求解。在给定资源块分配策略后,原有博弈模型可被重新建模为便于独立求解发射功率的等价子博弈模型。仿真结果表明,所提算法在干扰受限的通信环境下能收敛到纳什均衡,并有效提高了系统资源利用率和能量效率。     

基于NOMA的无线携能D2D通信鲁棒能效优化算法

针对频谱短缺、基站负荷过高、通信系统功耗较大等问题,考虑不完美的信道状态信息,该文提出一种基于非正交多址接入的无线携能(SWIPT)D2D网络鲁棒能效(EE)最大化资源分配算法(SREA)。考虑用户的服务质量约束以及最大发射功率约束,基于随机信道不确定性建立鲁棒能效最大化资源分配模型。利用Dinkelbach和变量替换方法,将原NP-hard问题转换为确定性的凸优化问题,通过拉格朗日对偶理论求得解析解。仿真结果表明,所提算法在保证蜂窝用户通信质量的同时,能够有效提高D2D用户的能效性和鲁棒性能。     

基于速率约束的OFDM中继链路能效最优资源分配策略

该文研究解码转发(DF)模式的OFDM中继链路的能效最大化资源分配问题。与现有典型的固定速率最小化发射功率或无约束最大化能效算法不同,该文考虑电路功率消耗的前提下,将问题建模为以最大化系统能效为目标,同时考虑用户最小速率需求、源节点S和中继节点R各自总发射功率约束下的联合子载波配对和最优功率分配问题。证明了速率和功率联合约束条件下中继链路全局能效最优解的唯一性,在此基础上提出一种低复杂度联合最优资源分配策略。仿真结果表明,该文所提方案能够在最小速率和S/R节点最大发射功率约束下自适应分配功率资源,实现系统能效最优,并能够降低链路的中断概率。     

基于可再生能量协作的雾无线接入网络资源分配

针对雾无线接入网络(Fog Radio Access Network,F-RAN)中能耗开销巨大的问题,提出了一种基于能量收集(Energy Harvesting,EH)约束的资源分配算法,从联合模式选择与功率分配两个方面进行了研究.首先建立传输模型和能量采集模型,根据功率约束和电费支出约束建立最优化问题;再使用分枝定界法对通信模式进行选择,利用吞吐量注水法对不同传输模式下的发射功率进行分配.仿真结果表明,提出的基于可再生能量协作的F-RAN的吞吐量和电网能量效率均高于传统F-RAN,具有经济和环境双重效益.     

基于资源分配和功率控制的D2D中继选择

为优化蜂窝用户通信与设备直传(D2D)中继通信共存下的同频干扰问题,满足蜂窝用户容量要求,提出了一种基于能效的联合资源分配和功率控制的D2 D中继选择算法.该算法首先对等效D2 D中继链路进行资源分配,减小算法复杂度的同时使得D2 D链路对蜂窝链路产生的干扰最小;然后以资源分配结果和功率控制算法为依据进行中继选择.该方案不仅考虑了D2 D中继链路的能效问题,而且还同时考虑到了对蜂窝链路的干扰问题.通过仿真验证,所提算法不仅能有效提升D2 D中继链路的能效值,同时降低了对蜂窝用户的干扰.     

基于不完美CSI的D2D通信网络鲁棒能效资源分配算法

针对设备到设备(D2D)直连通信网络传统最优资源分配算法在随机信道时延、信道估计误差影响下鲁棒性弱的问题,该文在考虑参数不确定性影响的条件下,提出D2D用户总能效最大的鲁棒资源分配算法。考虑干扰功率门限、用户最小速率需求、最大传输功率和子信道分配约束,建立了下垫式频谱共享模式下多用户D2D网络资源分配模型。基于有界信道不确定性模型,利用最坏准则方法将原非凸鲁棒资源分配问题转换为确定性的凸优化问题。然后利用拉格朗日对偶理论求得资源分配的解析解。仿真结果表明所提出的算法具有很好的鲁棒性。     

Proportional-fair energy-efficient radio resource allocation for OFDMA smallcell networks

This paper investigates the energy-efficient radio resource allocation problem of the uplink smallcell networks. Different from the existing literatures which focus on improving the energy efficiency (EE) or providing fairness measured by data rates, this paper aims to provide fairness guarantee in terms of EE and achieve EE-based proportional fairness among all users in smallcell networks. Specifically, EE-based global proportional fairness utility optimization problem is formulated, taking into account each user’s quality of service, and the cross-tier interference limitation to ensure the macrocell transmission. Instead of dealing with the problem in forms of sum of logarithms directly, the problem is transformed into a form of sum of ratios firstly. Then, a two-step scheme which solves the subchannel and power allocation separately is adopted, and the corresponding subchannel allocation algorithm and power allocation algorithm are devised, respectively. The subchannel allocation algorithm is heuristic, but can achieve close-to-optimal performance with much lower complexity. The power allocation scheme is optimal, and is derived based on a novel method which can solve the sum of ratios problems efficiently. Numerical results verify the effectiveness of the proposed algorithms, especially the capability of EE fairness provisioning. Specifically, it is suggested that the proposed algorithms can improve the fairness level among smallcell users by 150–400 % compared to the existing algorithms.