带局部搜索的动态多群体自适应差分进化算法及函数优化

 提出将一种改进的差分进化算法——带局部搜索的动态多群体自适应差分进化算法(DMSDELS)应用于函数优化.该算法将种群中的个体随机动态分成多个子群体,以增强个体间的信息交换;变异操作中,选择最优个体为基向量,差分向量的方向选择有利于搜索的方向,以提高收敛速度;变异尺度因子F与交叉概率CR采用自适应机制,以平衡局部搜索与全局搜索;部分优秀个体搜索达到指定代数进入局部搜索,以加快收敛.通过对13个benchmark典型复杂函数进行测试,并与其他七种优化算法进行比较,仿真结果表明:DMSDELS算法具有较高的搜索精度和收敛性,且具有较强的跳出局部最优解能力.     

Power consumption analysis of video streaming in 4G LTE networks

Video streaming, one of the most popular technologies for online video playback, has already been applied to 4G LTE networks. Previous work has been devoted to understanding the power consumption in general 4G LTE networks, while it is still unclear how the online video streaming makes impact on the power performance of mobile devices. Inspired by this, this paper investigates the relationship between the mobile device’s power performance characteristics and the behaviours of video streaming in 4G LTE networks. There are many natural issues/questions that are clearly interesting and important, while it is non-trivial to answer these issues/questions exactly (e.g., where is the energy saving room? how much is it?). To address a series of issues like the above, we formulate our energy models together with an algorithm that can assist our analysis. Particularly, we design a systematic platform, and conduct a comprehensive and also deep analysis on the power consumption of video streaming in 4G LTE networks. Our experiments reveal us a series of valuable findings—the saving room in the network part is large (from 41.86 to 69.62%), the number of RRC tails and the transmission pattern could be promising for optimizing the power consumption, for example.     

LTE/EPS在4G移动通信的演进研究

4G以其在通信范围、通信质量和支持高速数据媒体业务等方面的优势引领着移动通信的方向,为适应业务带宽、传输时延及网络覆盖等需要,第三代合作伙伴计划（3GPP）标准委员会启动了长期演进计划（LTE）和演进分组系统（EPS）,并设计提出全IP的LTE/EPS架构。LTE系统主要研究新的物理层的传输方案、先进的天线技术和灵活的带宽,EPS从系统整体角度考虑未来移动通信的特征,将二者进行结合,可从系统结构演进的整体角度分析未来移动通信的网络发展趋势。     

微分进化算法在雷达网抗干扰优化中的应用研究

建立了区域雷达网优化布站数学模型,分析了雷达网在干扰前后威力区的变化,采用新的雷达网威力区计算方法,新算法将可布站区域划分为若干小格,以雷达探测区覆盖层数标记每一小格,通过统计不同覆盖层数的小格数,计算雷达网威力区面积.给出了微分进化算法在该优化问题中的求解过程,并将迭代过程与遗传算法进行比较,仿真结果表明微分进化算法在收敛速度上具有明显优势.最后,针对雷达网受干扰后威力区收缩,提出了重新部署网内雷达或增加网内雷达数量两种解决方案,仿真结果证明所提方案是有效可行的.     

Introduction of a Novel Hybrid Weighted Exponential Logarithm-Maximum Throughput (HWEL-MT) Scheduler for QoS Improvement of LTE/4G Cellular Networks

The real-time broadcast of multimedia contents such as VoIP and video traffics in recent cellular networks is increasingly becoming common. In this regard, LTE networks with the objective of providing high speed data along with QoS assurance have been introduced. To perform this, schedulers in order to allocate of the resources to the traffics are used as channel-aware/QoS-aware. The most important and effective schedulers are EXP RULE and E2M RULE for this type of networks but still requires improving of QoS parameters to reach an optimal level of performance. In this paper aims to improve the packet loss rate (PLR), latency and throughput parameters especially and improve the other QoS parameters generally in the downlink LTE networks, a new scheduler called Hybrid Weighted Exponential Logarithm-Maximum Throughput (HWEL-MT) RULE method has been proposed. By performing simulations and comparisons between output results of EXP-Rule, E2M RULE and HWEL-MT RULE schedulers for VoIP, video and best effort traffics, we have totally concluded that the proposed HWEL-MT scheduler is able to improve PLR, delay, throughput, fairness and spectral efficiency more than two other examined methods. The results have been presented and compared by implementing a LTE network included 5–70 mobile users in open source LTE-Sim software.     

LTE网络4扇区部署性能分析和优化建议

在移动通信站址资源日益稀缺的背景下,LTE网络4扇区部署是一种提高站址利用率、单站覆盖范围的方案.在介绍了LTE网络4扇区部署的基本概念和主要干扰问题的基础上,分别通过理论分析和验证测试论述了4扇区部署对网络质量的影响;并对解决4扇区干扰问题的两种优化技术手段——SFN合并优化技术和RF优化技术分别进行了简要介绍;而后借助现网站点的仿真结果对比了两者的优化增益;最后提出了4扇区建设和优化建议.     

Design of Digital FIR Filters Using Differential Evolution Algorithm

The differential evolution (DE) algorithm is a new heuristic approach with three main advantages: it finds the true global minimum of a multimodal search space regardless of the initial parameter values, it has fast convergence, and it uses only a few control parameters. The DE algorithm, which has been proposed particularly for numeric optimization problems, is a population-based algorithm like the genetic algorithms and uses similar operators: crossover, mutation, and selection. In this work, the DE algorithm has been applied to the design of digital finite impulse response filters, and its performance has been compared to that of the genetic algorithm and least squares method.     

Novel Low-Complexity Partial Transmit Sequences Scheme for PAPR Reduction in OFDM Systems Using Adaptive Differential Evolution Algorithm

A low-complexity partial transmit sequence (PTS) technique for reducing the peak-to-average power ratio (PAPR) of an orthogonal frequency division multiplexing signal is presented. However, the conventional PTS scheme requires an exhaustive searching over all combinations of allowed phase factors. Consequently, the computational complexity increases exponentially with the number of the subblocks. This paper presents a novel approach to the PAPR problem to reduce computational complexity based on the relationship between phase weighing factors and transmitted bit vectors. In this paper, we aim to obtain the desirable PAPR reduction with the low computational complexity. Since the process of searching the optimal phase factors can be categorized as combinatorial optimization with some variables and constraints, we propose a novel scheme, which is based on a stochastic optimization technique called modified differential evolution, to search the optimal combination of phase factors with low complexity. To validate the analytical results, extensive simulations have been conducted, showing that the proposed schemes can achieve significant reduction in computational complexity while keeping good PAPR reduction.     

改进的差异进化多目标优化算法在靶场测控方案优化设计中的应用

针对在靶场测控方案优化设计中常存在的非线性函数优化难,局部搜索能力弱,约束条件复杂等问题,给出了一种改进的求解策略,即差异进化算法。在介绍差异进化算法基本原理的基础上,对算法中交叉因子和变异因子这两个主要控制参数的取值方法进行了改进,同时改进约束条件的收敛方法,提高了差异进化算法的优化性能。最后对靶场高炮武器系统直接射击测控方案进行优化设计,并做了仿真试验。通过指标对比和数值分析表明,算法求解效率高,收敛速度快,全局搜索能力强。     

Using Clustering via Soccer League Competition Algorithm for Optimizing Power Consumption in WSNs (Wireless Sensor Networks)

Wireless Personal Communications - WSNs consist of small sensor nodes which have limited battery power, limited processing capability and limited memory unit. Self-organization and the lack of...     

基于跨层设计的Macro-Femto异构网络下行链路功率消耗最小化(英文)

Based on the cross-layer design, the power-optimization problem of Macro-Femto Heterogeneous Networks (HetNets) has been formulated. The constraints of power and resource block allocation in the physical layer, delay and target data rate in the medium access control layer, urgent queue length in the network layer, and packet error rate in the transport layer, have been considered. The original problem is non-deterministic polynomial time hard, which cannot be solved practically. After the restrictions of upper layers are translated into constraints with physical layer parameters, and the integer restrictions are relaxed, the original problem can be decomposed into convex optimization subproblems. The optimal solutions of resource block allocation and power allocation can be obtained by using the Lagrangian optimization. Simulation results show that the proposed scheme is better than both the round robin algorithm and the max-min one in terms of energy efficiency, throughput and service fairness. The round robin algorithm and the max-min one only focus on the user fairness rather than quality of service fairness. Compared to the round robin scheme (the max-min one), the proposed scheme improves the energy efficiency 58.85% (62.41%), the throughput 19.09% (25.25%), the service fairness 57.69% (35.48%).     

A Differential Game Model of Automatic Load Balancing in LTE Networks

In this paper, load balancing problem is investigated and a new game theory automatic load balancing scheme in LTE networks is proposed based on non-cooperative differential game. Optimal load allocated to each cell is formulated as a Nash Equilibrium in this paper. It is proved that the non-cooperative differential game algorithm is applicable and the optimal load solution can be achieved. Simulation results show that system capacity is increased and load unbalancing caused inappropriate load allocation is decreased.     

Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm

In modern communication system error-control coding scheme is used to elevate the immunity of noisy communication channel. Turbo code (TC) is considered as one of the significant channel coding schemes which approaches to the Shannon limit. An upgraded version of TC named as 3 dimensional turbo code (3D-TC) has been emerged as a challenging research area in recent past. Meanwhile, considerable improvement in bit error rate (BER) performance of the TC has been achieved by incorporating suitable optimization algorithms. Motivated by above research trends, a modified symbiotic organisms search (MSOS) algorithm has been proposed by changing the organism structure and selection criteria of a newly developed symbiotic organisms search (SOS) algorithm. Subsequently the proposed MSOS has been used to design an improved 3D-TC. Here an optimal power allocation scheme of a new class of 3 dimensional turbo encoder has been investigated to improve its BER characteristics mainly in high SNR regions. Furthermore, the BER performance of the proposed 3D-TC code has been compared with conventional 2D serially concatenated and parallel concatenated turbo code as well as conventional 3D-TC. Finally, the BER performance of the proposed MSOS optimized 3D-TC has been compared with the SOS optimized 3D-TC and harmony search optimized 3D-TC.     

基于插值算子自适应混合差分进化算法的八木天线优化设计

本文采用插值算子自适应混合差分进化算法对六元八木天线进行优化设计。首先介绍了插值算子自适应混合差分进化算法的原理和实现流程,然后采用该算法优化设计了六元八木天线的增益,以振子的长度和振子的间距为优化变量,获得优于其它算法的结果。考虑工程实际的匹配阻抗问题,同时优化八木天线的增益和阻抗,同样获得了较优的结果。结果表明该方法可有效应用于八木天线的工程设计当中,为该类天线设计提供了新的设计方法。     

一种用于分群OFDM超宽带网络的功率分配新算法

提出了一种用于分群OFDM超宽带网络的功率分配新算法。该算法在保证总通信容量最大的同时,为每个群分配一个特定的功率,使当前子频带的通信容量最大。理论分析和仿真结果表明,该功率分配算法具有良好的性能和相对较低的复杂度,在高速率数据传输中有着良好的应用前景。     

Nonlinear System Control Using Adaptive Neural Fuzzy Networks Based on a Modified Differential Evolution

This study presents an adaptive neural fuzzy network (ANFN) controller based on a modified differential evolution (MODE) for solving control problems. The proposed ANFN controller adopts a functional link neural network as the consequent part of the fuzzy rules. Thus, the consequent part of the ANFN controller is a nonlinear combination of input variables. The proposed MODE learning algorithm adopts an evolutionary learning method to optimize the controller parameters. For design optimization, a new criterion is introduced. A hardware-in-the loop control technique is developed and applied to the designed ANFN controller using the MODE learning algorithm. The proposed ANFN controller with the MODE learning algorithm (ANFN-MODE) is used in two practical applications—the planetary-train-type inverted pendulum system and the magnetic levitation system. The experiment is developed in a real-time visual simulation environment. Experimental results of this study have demonstrated the robustness and effectiveness of the proposed ANFN-MODE controller.      

4G LTE技术在煤矿的应用

介绍4G LTE技术的现状、优势;介绍BBU+RRU分体式基站覆盖模式,并将该模式引入到煤矿通信系统中,并说明该模式的优缺点。     

Shape Reconstruction of a Perfectly Conducting Scatterer Using Differential Evolution and Particle Swarm Optimization

The shape reconstruction of a perfectly conducting 2-D scatterer by inverting transverse magnetic scattered field measurements is investigated. The reconstruction is based on evolutionary algorithms that minimize the discrepancy between measured and estimated scattered field data. A closed cubic B-spline expansion is adopted to represent the scatterer contour. Two algorithms have been examined the differential-evolution (DE) algorithm and the particle swarm optimization (PSO). Numerical results indicate that the DE algorithm outperforms the PSO in terms of reconstruction accuracy and convergence speed. Both techniques have been tested in the case of simulated measurements contaminated by additive white Gaussian noise.     

基于二进制差分进化算法的MIMO 雷达阵列优化

针对智能优化算法在MIMO雷达稀疏阵列优化中具有条件约束和局部收敛等问题,本文提出一种参数自适应的二进制差分进化(Adaptive Binary Differential Evolution,ABDE)算法。首先,提出一种规范化的编码方式,解决阵元数和孔径约束问题。通过依次添加、去除阵元,并判断操作对目标函数值的影响来决定阵元位置。其次,改进差分进化算法。借鉴和声搜索(Harmony Search,HS)算法,引入随机扰动,从而增加种群的多样性。通过定义一种二进制差分变异方式BDE/best/1,使父代信息尽量多地传递给子代。然后,提出参数自适应调整策略。利用logistic函数,构造S型的种群进化曲线。最后,MIMO雷达阵列优化设计实验验证了算法的有效性。