Optimization of energy efficiency for the full-duplex massive MIMO systems

The energy efficiency（EE） for the full-duplex massive multi-input multi-output（MIMO） system is investigated. Given the transmit powers of both the uplink and the downlink, the closed-form solutions of the optimal number of antennas and the maximum EE are achieved in the high regime of the signal-to-noise ratio（SNR）. It is shown that the optimal number of antennas and the maximum EE gets larger with the increase in user numbers. To further improve the EE, an optimization algorithm with low complexity is proposed to jointly determine the number of antennas and the transmit powers of both the uplink and the downlink. It is shown that, the proposed algorithm can achieve the system performance very close to the exhaustive search.

Energy Efficiency Optimization for D2D Communications Based on SCA and GP Method

In this paper, we propose an energy-efficient power control scheme for device-to-device(D2D) communications underlaying cellular networks, where multiple D2D pairs reuse the same resource blocks allocated to one cellular user. Taking the maximum allowed transmit power and the minimum data rate requirement into consideration, we formulate the energy efficiency maximization problem as a non-concave fractional programming(FP) problem and then develop a two-loop iterative algorithm to solve it. In the outer loop, we adopt Dinkelbach method to equivalently transform the FP problem into a series of parametric subtractive-form problems, and in the inner loop we solve the parametric subtractive problems based on successive convex approximation and geometric programming method to obtain the solutions satisfying the KarushKuhn-Tucker conditions. Simulation results demonstrate the validity and efficiency of the proposed scheme, and illustrate the impact of different parameters on system performance.

Proportional Fairness-Based Energy-Efficient Power Allocation in Downlink MIMO-NOMA Systems with Statistical CSI

In this paper, proportional fairness(PF)-based energy-efficient power allocation is studied for multiple-input multiple-output(MIMO) non-orthogonal multiple access(NOMA) systems. In our schemes, statistical channel state information(CSI) is utilized for perfect CSI is impossible to achieve in practice. PF is used to balance the transmission efficiency and user fairness. Energy efficiency(EE) is formulated under basic data rate requirements and maximum transmitting power constraints. Due to the non-convex nature of EE, a two-step algorithm is proposed to obtain sub-optimal solution with a low complexity. Firstly, power allocation is determined by golden section search for fixed power. Secondly total transmitting power is determined by fractional programming method in the feasible regions. Compared to the performance of MIMO-NOMA without PF constraint, fairness is obtained at expense of decreasing of EE.

Energy Efficient Resource Allocation in Timesharing Multiuser Systems with Hybrid Energy Harvesting Transmitter

An energy effi cient resource allocation scheme in timesharing multiuser system with a hybrid energy harvesting transmitter is studied in this paper. Specially, the operation energy of system is supplied by constant energy and energy harvesting, which harvests energy from external environment. Our goal is to maximize the energy effi ciency of timesharing multiuser systems by considering jointly allocation of transmission time and power control in an off-line manner. The original nonconvex objective function is transformed into convex optimization problem via the fractional programming approach. Then, we solve the convex problem by Lagrange dual decomposition method. Simulation results show that the proposed energy efficient resource allocation scheme has a better performance than the scheme which decomposes optimization problem into two parts(power allocation, time allocation) to solve iteratively.

Energy-Efficient Target Channel Sequence Design for Spectrum Handoffs in Cognitive Radio Networks

Cognitive radio is considered as an efficient way to improve the spectrum efficiency. As one of its key technologies,spectrum handoff can guarantee the transmission continuity of secondary users(SUs). In this paper,we address a new and more generalized spectrum handoff problem in cognitive radio networks(CRNs),by considering simultaneously energy efficiency,multiple spectrum handoffs and multiple channels. Furthermore,effects of the primary users'(PUs')arrival and service rate on the target channel sequence selection are also considered. In order to obtain the energy-efficient target channel sequence,we firstly analyze the energy consumption and the number of delivered bits per hertz in the spectrum handoff process,and formulate a ratio-type energy efficiency optimization problem,which can be transformed into a parametric problem by utilizing fractional programming. Then,we propose an algorithm combining dynamic programming with bisection(DPB)algorithm to solve the energy efficiency optimization problem. Our simulation results verify that the designed target channel sequence has better performance than the existing algorithms in terms of energy efficiency.

Energy-Efficient Sensing and Transmission for Multi-Hop Relay Cognitive Radio Sensor Networks

How to achieve transmissions in an energy-efficient way in multi-hop decode and forward(DF) relay cognitive radio sensor networks(CRSNs) is important since sensor nodes in CRSNs are usually battery powered. This paper aims to maximize energy efficiency(EE) by joint optimizing sensing time and power allocation in multi-channels & multihops DF relay CRSNs under constraints on outage probability and sensing performance. First, we design a channel selection scheme for sensing according to the available probabilities of multi channels. Second, we analyze the expected throughput and energy consumption and formulate the EE problem as a concave/concave fractional program. Third, coordinate ascent and Charnes-Cooper Transformation(CCT) methods are used to transform the nonlinear fractional problem into an equivalent concave problem. Subsequently, the closed form of outage probability is derived and the convergence rate of the iterative algorithm is analyzed. Finally, simulation results show that the proposed scheme can achieve effective EE.

Energy Efficient Modelling of a Network

Most of the networks are generally less energy efficient and most of the time resources are underutilized. Even resources of busy networks are also underutilized and thus networks show energy inefficient management system. This paper focuses on how to obtain minimum resources for the current situation of the network to maintain connectivity, power saving and quality of service. Four different models are proposed in this perspective with different purposes and functions. These models determine the minimum resources under certain constrains. Two types of services namely, "minimum bandwidth" and "trivial file transfer" are considered. For "minimum bandwidth" service, minimum edge, minimum delay and minimum change models are proposed. Here data rate switch and enable/disable of edges are placed in these models for power saving strategy. Another model, multi flow is proposed for "trivial file transfer" service. It is proposed for transferring files through multiple flows in multiple paths from source to destination. All models except multi flow model are mixed integer programming optimization problem.

IRS辅助的MISO系统安全节能通信方案

智能反射面(Intelligent Reflecting Surface,IRS)是提高未来B5G/6G网络安全节能通信的一项革命性技术。本文针对IRS辅助下行多输入单输出(Multiple Input Single Output,MISO)系统的高安全风险与高能耗问题,分析了发送端发射波束成形和IRS相移矩阵对系统安全节能通信的影响,构建合法用户保密率约束下的系统发射功率最小化问题。针对该非凸多变量耦合问题,提出一种基于逐次凸逼近(successive convex approximation,SCA)的二阶锥规划算法迭代求解问题。与传统迭代优化算法不同,该算法在每次迭代中同时更新所有优化变量,并最终获得原问题的次优解。仿真结果表明,相较于无IRS方案、随机相移方案与SDR迭代优化方案三种基准方案,所提算法均在保证合法用户保密质量的同时实现了更低的发射功率,证明了本文算法的有效性与IRS在未来安全节能通信系统中的巨大潜力。

学习驱动的分布式异构混合流水车间批量流能效调度优化

本文研究了分布式异构混合流水车间批量流能效调度问题,其中每个工厂的加工效率不同,工件可以分割成若干子批进入加工系统.以最大完成时间和总能耗为优化目标,建立了混合整数规划模型.本文提出了一种学习驱动的多目标进化算法,包括学习驱动的全局搜索和局部搜索.引入Q学习作为学习引擎,以种群和非支配解集的评价作为环境反馈信号,通过不断的学习来动态指导搜索操作的选择;基于问题特征,设计了算法的状态集、动作集和奖励机制.Q学习的引入能够及时感知当前搜索的状态,减少搜索操作的盲目性,提高搜索的效率.通过对仿真数据集的测试,表明所提出算法能够有效地求解分布式异构混合流水车间批量流能效调度问题.

A hierarchical multi-purpose roller shade controller to enhance indoor comfort and energy efficiency

Building envelope is the sole interface with outdoors that can lie in the level of integrating control strategies to enhance occupant's comfort and building performance. However, in the literature, there is still a lack of multi-purpose control strategies which can balance diverse and antagonistic aspects of occupant comfort while keeping the building energy consumption under control. Therefore, this research proposed an integrated simulation-based workflow using EnergyPlus and Python-based package, OpyPlus, to adjust a roller shade for single occupied office space in a hot and arid climate. The developed system aims to improve both occupant's visual and thermal comfort considering daylight level, potential glare at occupant's field of view, view to outdoor satisfaction, and Fanger PMV method, and then, managing the HVAC system in favor of enhancing building energy efficiency. Furthermore, the controller's performance was compared to multiple fixed controls and another multi-agent control scenario from visual and thermal comfort and energy performance perspectives. The developed control system could perform effectively to provide a glare-free view and higher thermally comfortable indoor environment by 99% for the occupant across the year, while improving the heating and cooling loads. The research provides novel insights and potential future integrations for facade designers and building operators.

Low Complexity Energy Optimization Algorithm for Massive MIMO systems

We consider the problem of nearly optimal energy efficiency in massive(Multiinput Multi-output) MIMO systems. Considering the correlated channel in practice, we derive the ergodic expression with zero-forcing precoding and analyze the simplified antennas selection method. Aiming at optimizing the energy efficiency, the closed form expressions of the nearly optimal number of transmit antennas and transmit power are given under the circuit consumption model. The joint solution of the number of transmit antennas and transmit power was replaced to only solve transmit power. Based on the expression only related with transmit power, we give an energy efficiency optimization algorithm. The simulation results show that the proposed algorithm can achieve nearly optimal energy efficiency with fast convergence speed.

基于动态规划法的原油管道外输系统运行能耗优化

随着油田的不断开发以及输油设备的长期运行,输油站内机泵、加热炉等耗能设备与输量产生不匹配的现象,致使外输系统整体耗能呈现逐年增涨的趋势。针对上述问题,建立以外输系统总能耗费用为目标函数的原油管道外输系统优化模型,通过外输系统热力水力计算以及约束条件确定外输系统内各站进站参数允许区间进而反算得到外输运行参数方案合集,采用动态规划法通过输油站设备能效计算对输油泵和加热炉的设备组合方案进行优化,选取当前输量下总能耗费用最低的方案作为优化的最优结果。通过此方法对某外输系统进行优化,总能耗费用降低约16%。

能效最优准则下无人机空中高度的优化算法

利用无人机(unmanned aerial vehicle,UAV)组建空中移动基站,可为地面终端用户提供更灵活、高效的接入服务。受UAV覆盖范围和有限能量的约束,研究如何建立能效最优的UAV部署算法至关重要。为此,提出能效最优准则下无人机空中高度的优化算法(optimal energy efficient based aerial altitude optimization,EEAO)。先在满足用户最小速率要求和UAV高度的约束条件下,构建能效最优的高度优化的目标函数。同时,定义能效时不仅考虑UAV的通信能耗,还考虑UAV在垂直爬升和悬停阶段的能耗。再分别利用和序列凸规划法(sequential convex programming,SCP)和单调分式规划法(monotonic fractional programming,MFP)求解目标函数,获取能效最优的UAV高度值。性能分析表明,基于SCP法求解的最优高度值与基于MFP法求解的最优高度值相近。同时,相比于不考虑悬停阶段UAV的能耗,考虑悬停阶段UAV的能耗可提升网络能效。

User scheduling and power allocation for downlink multi-cell multi-carrier NOMA systems

In Non-Orthogonal Multiple Access(NOMA),the best way to fully exploit the benefits of the system is the efficient resource allocation.For the NOMA power domain,the allocation of power and spectrum require solving the mixed-integer nonlinear programming NP-hard problem.In this paper,we investigate user scheduling and power allocation in Multi-Cell Multi-Carrier NOMA(MCMC-NOMA)networks.To achieve that,we consider Weighted Sum Rate Maximization(WSRM)and Weighted Sum Energy Efficiency Maximization(WSEEM)problems.First,we tackle the problem of user scheduling for fixed power using Fractional Programming(FP),the Lagrange dual method,and the decomposition method.Then,we consider Successive Pseudo-Convex Approximation(SPCA)to deal with the WSRM problem.Finally,for the WSEEM problem,SPCA is utilized to convert the problem into separable scalar problems,which can be parallelly solved.Thus,the Dinkelbach algorithm and constraints relaxation are used to characterize the closed-form solution for power allocation.Extensive simulations have been implemented to show the efficiency of the proposed framework and its superiority over other existing schemes.

常导高速磁浮列车节能速度曲线鲁棒优化研究

列车速度曲线的优化是轨道交通节省运营成本的重要途径之一,鲁棒优化方法有助于克服速度曲线节能优化中的不确定因素。针对常导高速磁浮列车节能速度曲线优化,首先将区间划分为若干区段,进而将列车运行控制的停车点步进机制、列车悬浮运行的阻力特性、区间限速、运行时分与乘坐舒适性要求以及列车总重的不确定性纳入鲁棒优化模型,并结合三项引理将其重构为带二次项和区间数的混合整数规划(MIP)问题。联合Gurobi求解器以及基于可接受目标函数值波动范围的鲁棒优化方法讨论求解算法。借助仿真算例检验模型与算法的有效性,分析列车总重、运行时分以及区段划分对运行能耗的影响。研究结果显示:列车总重取最大值时所得悲观速度曲线与列车总重取最小时所得乐观速度曲线存在差异,优化速度曲线时有必要考虑列车总重的不确定性;列车总重取最小与最大时,鲁棒速度曲线分别较悲观速度曲线和乐观速度曲线节能2.222%和7.087%;在大多数情况下,鲁棒速度曲线能够克服悲观速度曲线的保守特性;放松对运行时分的要求有助于降低列车运行能耗;选择合适的区段划分间隔有助于获取更优的节能速度曲线。所提出方法可为常导高速磁浮列车节能速度曲线的获取提供有效手段,对其他制式轨道交通列车速度曲线的优化也有参考价值。

基于变质心高度策略仿人机器人变步长步态规划

针对仿人机器人步态切换越障需求,提出一种基于变质心高度策略的变步长步态规划方法。首先,分析质心(CoM)高度变化对机器人步态的影响,将1个步行周期分为3个阶段,包括质心下降、上升和定高度过程,规划质心高度轨迹。然后,规划零力矩点(ZMP)参考轨迹,基于变高度倒立摆模型,通过托马斯算法解算质心轨迹。为了增强鲁棒性,考虑到机器人越障时步行参数变化的步态切换需求,提出一个具有等式约束的二次规划问题,求解质心优化轨迹。最后,以NAO机器人为实验平台,进行变步长步行对比实验。结果表明:所提出的基于变质心高度策略的步态规划方法,能够实现机器人大步幅变步长稳定步行,实现步态平滑切换,相比于恒定质心高度方法,所提方法的步行平均能耗降低约10%。

基于中继和智能反射面协同的无人机传输方法

无人机(Unmanned aerial vehicle,UAV)通信和智能反射面(Intelligent reflecting surface,IRS)辅助通信是未来6G移动通信空地传输的典型场景,有机协同无人机和智能反射面辅助通信能够提升空地通信网络的传输性能。本文采用无人机全双工中继和搭载在其上的智能反射面被动反射共同协助空地传输,通过发射机的功率控制和智能反射面反射单元数目的联合优化,提升了系统能量效率。仿真结果表明,本文所提的方法优于单独采用无人机中继或者智能反射面辅助通信场景下的系统性能。

Measurement of energy efficiency based on frontier approaches

The improvement of energy efficiency has played an important role in the global low-carbon economy and the sustainable development process.There are many methodologies for estimating energy efficiency in academia.This article introduces four frontier methods for energy efficiency evaluation:nonparametric data envelopment analysis(DEA),parametric linear programming,stochastic frontier analysis(SFA),and the meta-frontier approach.The advantages and disadvantages of these methods are discussed.Finally,suggestions for model selection in energy efficiency measurement are offered.

中日能效标准标识制度浅析比较

能效标准标识制度一直是世界各国用以提高终端能源利用效率的重要节能手段和措施之一。本文通过对日本能效标准标识制度的研究,结合目前我国能效标准标识的法律基础、实施模式和实施现状,在比较分析的基础上,旨在总结经验,发掘问题,为我国标准标识工作提供有益启示。

移动中继协助下终端直通中面向能效的联合中继选择和资源分配方案

在移动中继协助下的终端直通(Device-to-Device,D2D)中,由于频带复用,D2D链路与已有蜂窝链路会产生同频干扰。另外,考虑到终端设备功率受限,该文提出一种联合功率控制、信道分配和移动中继选择方案最大化D2D链路总能量效率。原问题为分数规划问题,可转化为通过Dinkelbach算法求解的参数规划问题,此外,上述参数规划问题可进一步分解为功率控制子问题和联合优化信道分配与移动中继选择子问题。其中,功率控制子问题属于DC(Difference-of-Concave)规划问题,其一般意义下为NP-hard难题,可借助序列凸优化方法得到有效的近似解,基于上述结果,联合优化信道分配与移动中继选择子问题可转化为二分图中的最大匹配问题,继而借助匈牙利算法在多项式时间内求得最优解。通过仿真,验证了该方案在优化能量效率的效果。