Energy-Efficient Resource Optimization for Massive MIMO Networks Considering Network Load

This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output (MIMO) network in which each base station (BS) is equipped with a large number of antennas and each base station (BS) adapts the number of antennas to the daily load profile (DLP). This paper takes into consideration user location distribution (ULD) variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO system. ULD variation is modeled by dividing the cell into two coverage areas with different user densities: boundary focused (BF) and center focused (CF) ULD. All cells are assumed identical in terms of BS configurations, cell loading, and ULD variation and each BS is modeled as an M/G/m/m state dependent queue that can serve a maximum number of users at the peak load. Together with energy efficiency (EE) we analyzed deployment and spectrum efficiency in our adaptive massive MIMO system by evaluating the impact of cell size, available bandwidth, output power level of the BS, and maximum output power of the power amplifier (PA) at different cell loading. We also analyzed average energy consumption on an hourly basis per BS for the model proposed for data traffic in Europe and also the model proposed for business, residential, street, and highway areas.     

A PSO based Energy Efficient Coverage Control Algorithm for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are large-scale and high-density networks that typically have coverage area overlap. In addition, a random deployment of sensor nodes cannot fully guarantee coverage of the sensing area, which leads to coverage holes in WSNs. Thus, coverage control plays an important role in WSNs. To alleviate unnecessary energy wastage and improve network performance, we consider both energy efficiency and coverage rate for WSNs. In this paper, we present a novel coverage control algorithm based on Particle Swarm Optimization (PSO). Firstly, the sensor nodes are randomly deployed in a target area and remain static after deployment. Then, the whole network is partitioned into grids, and we calculate each grid’s coverage rate and energy consumption. Finally, each sensor nodes’ sensing radius is adjusted according to the coverage rate and energy consumption of each grid. Simulation results show that our algorithm can effectively improve coverage rate and reduce energy consumption     

A scheduling scheme for wireless sensor networks based on social insect colonies

Sensor networks employ a large amount of wireless sensor nodes to provide sensing power with high redundancy. Such redundancy makes sensor networks robust under changing environments. However, without proper scheduling, the surplus sensing power will cost tremendous energy consumption to the wireless sensor nodes. A scheduling scheme based on social insect colonies is proposed here. The proposed scheme is a kind of adaptive 'periodic on-off' scheduling scheme that uses only local information for making scheduling decisions. The scheme is evaluated in terms of averaged detection delay, target 3-coverage hit-rate and energy consumption per successful target detection. Simulation results show that, when comparing with other generic scheduling schemes, the proposed scheme can reduce energy consumption from a minimum of 7.49% to a maximum of 90.81% and improve the target hit-rate from a minimum of 15.7% to a maximum of 58.9%. Optimisation of the network lifetime and other performances is possible by adjusting some parameters.     

基于粒子群算法的水声通信网络能量优化方法

水声通信网络节点功耗是影响网络节点寿命的重要因素之一。针对水声通信网络的能量优化问题,基于网络节点发射功率与传输距离的非线性关系,结合改进的粒子群算法建立了一种能量优化方法。该方法改进了网络模型,在网络运行中根据存活节点数量和节点剩余能量的变化情况,自适应动态优化每个节点的信息传输路径。仿真结果表明,所提优化方法能有效降低网络节点总功耗,延缓首个节点的死亡,减缓网络中节点的死亡速率,也即减缓了网络有效覆盖面积随着网络运行而减小的速率。     

Improved power-saving medium-access protocol for IEEE 802.11e QoS-enabled wireless networks

The performance of a new pointer-based medium-access control protocol that was designed to significantly improve the energy efficiency of user terminals in quality-of-service-enabled wireless local area networks was analysed. The new protocol, pointer- controlled slot allocation and resynchronisation protocol (PCSARe), is based on the hybrid coordination function-controlled channel access mode of the IEEE 802.11e standard. PCSARe reduces energy consumption by removing the need for power-saving stations to remain awake for channel listening. Discrete event network simulations were performed to compare the performance of PCSARe with the non-automatic power save delivery (APSD) and scheduled-APSD power- saving modes of IEEE 802.11e. The simulation results show a demonstrable improvement in energy efficiency without significant reduction in performance when using PCSARe. For a wireless network consisting of an access point and eight stations in power-saving mode, the energy saving was up to 39% when using PCSARe instead of IEEE 802.11e non-APSD. The results also show that PCSARe offers significantly reduced uplink access delay over IEEE 802.11e non-APSD, while modestly improving the uplink throughput. Furthermore, although both had the same energy consumption, PCSARe gave a 25% reduction in downlink access delay compared with IEEE 802.11e S-APSD.     

重庆市公共建筑实现节能75%设计目标的围护结构热工参数研究

为了实现重庆市公共建筑节能75%的目标,使用建筑能耗模拟软件PKPM,分析重庆市公共建筑围护结构的节能潜力。建立了3种基本公共建筑模型,分别为:办公类模型、宾馆类模型以及商场类模型。模拟研究的围护结构主要是建筑外墙、外窗以及屋顶。通过改变围护结构的热工性能参数,制定出能耗模拟方案。模拟得出公共建筑在不同热工性能的围护结构下的能耗数据,从而分析得出不同热工性能的围护结构对建筑能耗的影响。据此提出重庆地区公共建筑外墙、外窗及屋面等围护结构热工参数的建议取值。此外,还对照明对公共建筑能耗的影响进行模拟,得出降低照明能耗可以有效降低建筑能耗的结论。     

Nature Inspired Improved Firefly Algorithm for Node Clustering in WSNs

Wireless Sensor Networks (WSNs) comprises low power devices that are randomly distributed in a geographically isolated region. The energy consumption of nodes is an essential factor to be considered. Therefore, an improved energy management technique is designed in this investigation to reduce its consumption and to enhance the network’s lifetime. This can be attained by balancing energy clusters using a meta-heuristic Firefly algorithm model for network communication. This improved technique is based on the cluster head selection technique with measurement of the tour length of fireflies. Time Division Multiple Access (TDMA) scheduler is also improved with the characteristics/behavior of fireflies and also executed. At last, the development approach shows the progression of the network lifetime, the total number of selected Cluster Heads (CH), the energy consumed by nodes, and the number of packets transmitted. This approach is compared with Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Low Energy Adaptive Clustering Hierarchy (LEAH) protocols. Simulation is performed in MATLAB with the numerical outcomes showing the efficiency of the proposed approach. The energy consumption of sensor nodes is reduced by about 50% and increases the lifetime of nodes by 78% more than AODV, DSR and LEACH protocols. The parameters such as cluster formation, end to end delay, percentage of nodes alive and packet delivery ratio, are also evaluated... The anticipated method shows better trade-off in contrast to existing techniques.     

Green5G: Enhancing Capacity and Coverage in Device-to-Device Communication

With the popularity of green computing and the huge usage of networks, there is an acute need for expansion of the 5G network. 5G is used where energy efficiency is the highest priority, and it can play a pinnacle role in helping every industry to hit sustainability. While in the 5G network, conventional performance guides, such as network capacity and coverage are still major issues and need improvements. Device to Device communication (D2D) communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques. The issue of energy utilization in the IoT based system is a significant exploration center. Energy optimization in D2D communication is an important point. We need to resolve this issue for increasing system performance. Green IoT speaks to the issue of lessening energy utilization of IoT gadgets which accomplishes a supportable climate for IoT systems. In this paper, we improve the capacity and coverage of 5G technology using Multiple Inputs Multiple Outputs (MU-MIMO). MU-MIMO increases the capacity of 5G in D2D communication. We also present all the problems faced by 5G technology and proposed architecture to enhance system performance.     

火电机组脱硫超低排放运行能耗分析与节能运行展望

完成超低排放改造后,脱硫系统运行能耗大幅增加,脱硫厂用电率平均值为1.40%,折合供电煤耗约为4.4 g/（kW·h）。随着火电企业经营压力加重,超低排放运行时必须同时兼顾节能和减排双重目标。基于此,选取了33台不同工艺（单塔、双塔）的600 MW级机组作为研究对象,从脱硫厂用电率和单位脱硫能耗2方面分析了运行能耗情况,并重点分析了能耗影响因素。最后,从开展能效对标管理、脱硫系统运行优化、关键设备节能改造、浆液品质把控、精细化检修、合理使用脱硫添加剂等角度,对脱硫运行节能进行了展望。     

部分负荷下冷水机组运行方案的优化

冷水机组系统在部分负荷运行时,可选择调节冷水机组台数或每台冷水机组的运行功率来应对负荷的变化,但不同运行方案有不同的能耗。以某厂螺杆式冷水机组为例,测试不同负荷下冷水机组的性能参数,分析其总COP值,与现行运行方案下的冷水机组能耗相比,得到机组运行优化方案。结果表明,采用新运行方案,相对原运行方案可分别节能12％和23％。     

土壤源VRF空调系统冬季运行特性实验研究

以土壤源VRF空调系统为研究对象,利用土壤源VRF实验台对其冬季运行特性进行了实验研究,分析在不同开机率时,小时制热量、小时耗功量、机组COP随部分负荷率的变化规律。结果表明:小时制热量与小时耗功量随开机率的升高基本呈现增大趋势,且耗功量对开机率的变化更为敏感;不论室内机的开启率为何值,小时制热量随部分负荷率的增大而增大,小时耗功量、机组COP随部分负荷率的增加呈现下凹、上凸的变化趋势,即土壤源VRF空调机组在部分负荷运行条件下具有较为良好的节能性。     

Transmitter-Receiver Path Selection for Cell Range Extension Using Multi-Hop D2D

Conventional approach of dealing with more users per coverage area in cellular networks implies densifying the amount of (Access Point) AP which will eventually result in a larger carbon footprint. In this paper, we propose a base station off-loading and cell range extension (CRE) scheme based on multi-hop device-to-device (MHD2D) path selection between transmitter and receiver node. The paper also provides derivations of upper and lower bounds for energy efficiency, capacity, and transmit power. The proposed path selection scheme is inspired by the foraging behavior of honey bees. We present the algorithm as a modified variant of the artificial bee colony algorithm (MVABC). The proposed optimization problem is modeled as a minimization problem where we optimize the Energy Efficiency (EE). The proposed path selection MVABC is compared with the Genetic Algorithm (GA) and also with classical artificial bee colony (ABC) through simulations and statistical analysis. The student’s t-test, p-value, and standard error of means (SEM) clearly show that MVABC based path selection out-performs the GA and classical ABC schemes. MVABC based approach is 66% more efficient when compared with classic ABC and about 62% efficient when compared with GA based scheme.     

Controlled deployments for wireless sensor networks

In wireless sensor networks (WSNs), the operation of sensor nodes has to rely on a limited supply of energy (such as batteries). To support long lifetime operation of WSNs, an energy-efficient way of sensor deployment and operation of the WSNs is necessary. A new controlled layer deployment (CLD) protocol to guarantee coverage and energy efficiency for a sensor network is proposed. CLD outperforms previous similar protocols in that it can achieve the same performances and guarantee full area coverage and connection using a smaller number of sensors. It can also ameliorate the 'cascading problem' that reduces the whole network lifetime. Finally, analysis and simulation results show that CLD can use fewer sensor nodes for coverage and also increases the lifetime of the sensor network when compared with the probing environment and adapting sleeping (PEAS) protocol.     

Power optimised channel coding in wireless sensor networks using low-density parity-check codes

Energy consumption of low-density parity-check (LDPC) codes in different implementations is evaluated. Decoder's complexity is reduced by finite precision representation of messages, that is, quantised LDPC decoder, and replacement of function blocks with look-up tables. It is shown that the decoder's energy consumption increases exponentially with the number of quantisation bits. For the sake of low-power consumption, 3-bit magnitude and 1-sign bit representation for messages are used in the decoder. It is concluded that high-rate Gallager codes are as energy efficient as the Reed-Solomon codes, which till now have been the first choice for wireless sensor networks (WSNs). Finally, it is shown that using LDPC codes in WSNs can be justified even more by applying the idea of trading the transmitter power with the decoder energy consumption. By exploiting the trade-off inherent in iterative decoding, the network lifetime is increased up to four times with the 3-6 regular LDPC code. Hence, it is inferred that the LDPC codes are more efficient than the block and the convolutional codes.     

Architectural design of a sensory node controller for optimized energy utilization in sensor networks

The increasing complexity of manufacturing machines and the continued demand for high productivity have led to growing applications of sensor networks to enable more reliable, timely, and comprehensive information gathering from the machines being monitored. An effective and efficient utilization of sensor networks requires new sensor designs that enable adaptive event-driven information gathering based on the condition of the machines, as well as a coordinated information distribution adjusted to the available communication bandwidth of the network. This paper investigates several fundamental aspects regarding the architectural design of a sensory node controller (SNOC). The SNOC is the key element in a large-scale sensor network that coordinates the operation of individual sensors and the communication among various sensing clusters to realize distributed intelligent sensing. A parametric SNOC design that dynamically adjusts the power supply and the data-acquisition procedure to reduce the overall energy consumption of the sensor network is presented. Considerations on both the hardware and software aspects of the design to achieve energy efficiency are described, and analytical formulations are derived. Simulation results for a sensor network consisting of 40 SNOCs, each coordinating eight physical sensors, have shown that the design is able to reduce the energy consumption by about 43%, as compared to traditional techniques. A prototype SNOC was designed and implemented, based on the platform of a commercially available microcontroller, and experimentally tested for its ability to dynamically adjust the power consumption. The study has provided a concrete input to the design optimization and experimental realization of an SNOC-based sensor network for machine-system monitoring.     

微通道换热器在空调器上的应用研究

试验研究空气流量和流路设计对微通道换热器换热量的影响。测试结果表明,空气流量增加47％后,换热量增加10．6％;流路设计变化后,换热能力差别1．8％。将某机型铜管换热器更换成微通道换热器后,A工况能效提高0．22w／w,功耗降低4％,制冷剂充注量减少21．4％。指出整机的通风设计对微通道换热器有很大的影响,顶出风和侧出风机型需要采用不同的微通道结构设计。认为微通道换热器是应对国家2级能效要求的一个很好的技术解决方案;分析限制微通道换热器推广使用的一些因素。     

燃料电池汽车能量管理系统运用复合模糊逻辑控制的研究

合理分配不同动力源的输出功率是燃料电池汽车能量管理的重要环节。针对"燃料电池+蓄电池（FC+B）"混合动力汽车,提出一种用复合模糊逻辑控制的能量管理策略。该策略根据负载需求功率、蓄电池当前荷电状态（state of charge,SOC）以及目标区SOC动态调整功率分配。通过MATLAB/Simulink对所提出的复合模糊逻辑控制进行验证。仿真结果证明,当蓄电池SOC适中时（以H_SOC表示荷电状态值,当H_SOC=60%时）,SOC在复合模糊逻辑控制策略与功率追踪策略下变化基本相同,但前者的氢耗量减少0.54 g;当蓄电池初始SOC较低或较高时（分别以H_SOC=39.8%和H_SOC=80.2%为例）,相较于功率追踪策略,该策略使蓄电池SOC逐渐接近目标区。运用复合模糊逻辑控制可以降低混合动力系统的总能耗,提高系统的效率,控制更加灵活,具有一定的实用价值。     

涡旋式压缩机中间补气技术

对带有中间补气功能的涡旋式压缩机理论循环进行分析,针对在不同蒸发温度下采用中间补气对涡旋式压缩机的能力、功率、排气温度及能效比的影响进行试验研究与分析。结果显示,与普通涡旋式压缩机相比,带有中间补气功能的压缩机在蒸发温度由-5℃到-20℃之间变化时,其能力提升约15%～30%,能效比提升约9%～19%,功耗仅上升约10%。     

Optical image encryption using a jigsaw transform for silhouette removal in interference-based methods and decryption with a single spatial light modulator

Interference-based optical encryption schemes have an inherent silhouette problem due to the equipollent nature of the phase-only masks (POMs) generated using an analytical method. One of the earlier methods suggested that removing the problem by use of exchanging process between two masks increases the computational load. This shortcoming is overcome with a noniterative method using the jigsaw transformation (JT) in a single step, with improved security because the inverse JT of these masks, along with correct permutation keys that are necessary to decrypt the original image. The stringent alignment requirement of the POMs in two different arms during the experiment is removed with an alternative method using a single spatial light modulator. Experimental results are provided to demonstrate the decryption process with the proposed method.     

电站锅炉烟气余热利用技术方案研究

超临界电站锅炉排烟热损失量很大,对锅炉尾部烟气余热进行回收利用可以有效提高电厂的热经济性,减少煤耗,降低环境污染。目前火电厂最广泛提高烟气余热利用效率的方式是加装低温省煤器装置。对某超临界机组锅炉余热利用技术进行研究,分析不同低温省煤器布置方案,提出采用双级低温省煤器回收电站锅炉余热利用技术方案,即采用低温烟气与低加凝结水换热技术、前置式空气预热器与低温省煤器组合的能源梯级利用方式,实现最优节能及最佳投资收益。