A new Multiobjective Artificial Bee Colony algorithm to solve a real-world frequency assignment problem

Artificial bee colony (ABC) is a recently introduced algorithm that models the behavior of honey bee swarm to address a multiobjective version for ABC, named Multiobjective Artificial Bee Colony algorithm (MO-ABC). We describe the methodology and results obtained when applying the new MO-ABC metaheuristic, which was developed to solve a real-world frequency assignment problem (FAP) in GSM networks. A precise mathematical formulation for this problem was used, where the frequency plans are evaluated using accurate interference information taken from a real GSM network. In this paper, our work is divided into two stages: In the first one, we have accurately tuned the algorithm parameters. Then, in the second step, we have compared the MO-ABC with previous versions of distinct multiobjective algorithms already developed to the same instances of the problem. As we will see, results show that this approach is able to obtain reasonable frequency plans when solving a real-world FAP. In the results analysis, we consider as complementary metrics the hypervolume indicator to measure the quality of the solutions to this problem as well as the coverage relation information.     

COMPARATIVE ANALYSIS OF A HYBRID DE ALGORITHM WITH THE VNS ALGORITHM AND ITS VARIATION SVNS TO SOLVE A REAL-WORLD FREQUENCY ASSIGNMENT PROBLEM

The Frequency Assignment is a very important task in the planning of the GSM networks, and it still continues to be a critical task for current (and future) mobile communication operators. In this work, we compare a hybrid Differential Evolution algorithm with the Variable Neighbourhood Search algorithm and also its variant Skewed Variable Neighbourhood Search to solve a real-world Frequency Assignment problem (FAP) in GSM Networks. The results that are shown use accurate interference information. That information was also adopted by other researchers and it represents a real GSM network, granting, therefore, an really important applicability. Furthermore, we have analyzed and compared our approach with other algorithms proposed so far to this problem. Hence, our approach using the SVNS algorithm has proven to be efficient in solving this problem, and permitted us to obtain good results. In fact, with this work we have contributed to the FAP problem with an additional comparison between approaches using metaheuristics based on trajectory (VNS and SVNS) and others based on population (DE).     

Contention based scheduling for femtocell access points in a densely deployed network environment

The proliferation of new data intensive devices has caused an enormous burden on wireless systems. A femtocell network is a promising new technology developed to meet these demands. Since each femtocell network consists of uncoordinated subnetworks that work independently, the interference between subnetworks can result in a significant degradation of the overall network capacity. In this paper, we address the interference problem between uncoordinated femtocell access points (FAPs) and propose a distributed FAP scheduling scheme in a densely deployed femtocell network where FAPs interfere with each other. In contrast to previous works that have focused on dynamic power and frequency management, our approach focuses on time sharing through FAP contention. Depending on the outcome of contention, our method selects a winning FAP to be the sole user of the next time frame. The approach operates in a fully distributed manner with help from mobile nodes (MNs). To implement this scheme, we develop a new synchronous frame structure, which uses special common control channels. Through simulations, we observe that the proposed scheme doubles the network capacity compared to the legacy non-contending scheme, and could serve as the basis for future standards on femtocell networks.     

基于重填化学反应优化解决无线网络动态最短选路优化问题

采用人工智能优化技巧轻易解决静态最短选路(SP)优化问题,但是随着无线通讯的发展,诸如移动Ad Hoc网络与无线传感网络等新式无线网络被大量广泛使用.在这些新式无线网络中,网络拓扑随着时间而不断变化从而导致最短选路优化问题被转变成动态优化问题.提出了一种新式的基于化学反应优化(CRO)的算法来解决这个问题.化学反应优化...     

A comprehensive survey on optimizing deep learning models by metaheuristics

Deep neural networks (DNNs), which are extensions of artificial neural networks, can learn higher levels of feature hierarchy established by lower level features by transforming the raw feature space to another complex feature space. Although deep networks are successful in a wide range of problems in different fields, there are some issues affecting their overall performance such as selecting appropriate values for model parameters, deciding the optimal architecture and feature representation and determining optimal weight and bias values. Recently, metaheuristic algorithms have been proposed to automate these tasks. This survey gives brief information about common basic DNN architectures including convolutional neural networks, unsupervised pre-trained models, recurrent neural networks and recursive neural networks. We formulate the optimization problems in DNN design such as architecture optimization, hyper-parameter optimization, training and feature representation level optimization. The encoding schemes used in metaheuristics to represent the network architectures are categorized. The evolutionary and selection operators, and also speed-up methods are summarized, and the main approaches to validate the results of networks designed by metaheuristics are provided. Moreover, we group the studies on the metaheuristics for deep neural networks based on the problem type considered and present the datasets mostly used in the studies for the readers. We discuss about the pros and cons of utilizing metaheuristics in deep learning field and give some future directions for connecting the metaheuristics and deep learning. To the best of our knowledge, this is the most comprehensive survey about metaheuristics used in deep learning field.

     

Performance of GSM networks with general packet radio services

Recently, most of the mobile network providers start to introduce general packet radio service (GPRS) in their existing GSM networks. GPRS is the technology that will enable more efficient Internet applications to run on mobile networks even before the installation of 3G systems. However, it is not yet clearly understood, how the new data services will affect the overall network performance. This paper provides a framework for analytical performance evaluation of a single GSM/GPRS cell based on a multidimensional Markov chain model. Important performance measures like new call and handover blocking probabilities, moments of the blocking period distributions, achievable average data rates and resource utilization are determined. Introducing a new connection admission control (CAC) algorithm, different partitioning strategies between GSM and GPRS resources are investigated. Finally, the influence of typical GPRS applications like Internet browsing on traditional GSM services has been studied.     

移动ad hoc网络中DOS攻击及其防御机制

移动ad hoc网络由于其动态拓扑、无线信道以及各种资源有限的特点,特别容易遭受拒绝服务(DOS)攻击．提出了移动ad hoc网络中一种新的DOS攻击模型——ad hoc flooding攻击及其防御策略．该攻击主要针对移动ad hoc网络中的按需路由协议,如AODV,DSR等．ad hoc flooding攻击是通过在网络中泛洪发送超量路由查询报文及数据报文,大量地占用网络通信及节点资源,以至于阻塞节点正常的通信．分析ad hoc flooding攻击之后,提出了两种防御策略：其一是邻居阻止,即当入侵者发送大量路由查询报文时,邻居节点降低对其报文的处理优先级,直至不再接收其报文．其二是路径删除,即目标节点将入侵者发送攻击报文的路径删除,以阻止其继续发送攻击报文．模拟实验证实,通过这两种方法的结合．能够有效地阻止网络中的ad hoc flooding攻击行为．     

GSM系统主要技术指标以及干扰的分析和优化

随着社会的发展,移动电话越来越普及,人们对通信质量的要求也越来越高。GSM系统作为第二代移动通信系统,在网络规模不断扩大的情况下,受频率资源的限制,频率复用度必然增加;由于规划或地理位置的原因,在多小区的情况下多会产生同频、邻频干扰;参数设置不当也会严重影响系统运行质量。所有这些都将使网络服务性能变差。为使网络资源能够合理配置和使用,这就要求移动运营商持续不断地进行网络优化,改善系统性能,提高自己的竞争力,这也是电信企业的生存基础。     

传感器网络中数据时新性移动设备的调度

为了在传感器网络中收集时间敏感性的数据,引入了移动设备来收集数据。提出了两种启发式算法,一种是基于货郎担问题的解法,将原问题分割成较小集合,然后逐步求解小问题,该算法适用于数据敏感性要求相对较低的应用;而当数据敏感性要求较高时,提出的贪婪式算法逐步建立移动设备的移动路径,即从基站(Sink)开始迭代选择代价值最小的节点,直到不能再添加节点进移动路径中。理论分析和模拟结果表明,提出的算法可以减少数据收集过程中所需要的移动设备的数目,而且大大节省了数据收集的总时间,从而可以应用在大规模网络中。     

A hybrid approach based on stochastic competitive Hopfield neural network and efficient genetic algorithm for frequency assignment problem

This paper presents a hybrid efficient genetic algorithm (EGA) for the stochastic competitive Hopfield (SCH) neural network, which is named SCH–EGA. This approach aims to tackle the frequency assignment problem (FAP). The objective of the FAP in satellite communication system is to minimize the co-channel interference between satellite communication systems by rearranging the frequency assignment so that they can accommodate increasing demands. Our hybrid algorithm involves a stochastic competitive Hopfield neural network (SCHNN) which manages the problem constraints, when a genetic algorithm searches for high quality solutions with the minimum possible cost. Our hybrid algorithm, reflecting a special type of algorithm hybrid thought, owns good adaptability which cannot only deal with the FAP, but also cope with other problems including the clustering, classification, and the maximum clique problem, etc. In this paper, we first propose five optimal strategies to build an efficient genetic algorithm. Then we explore three hybridizations between SCHNN and EGA to discover the best hybrid algorithm. We believe that the comparison can also be helpful for hybridizations between neural networks and other evolutionary algorithms such as the particle swarm optimization algorithm, the artificial bee colony algorithm, etc. In the experiments, our hybrid algorithm obtains better or comparable performance than other algorithms on 5 benchmark problems and 12 large problems randomly generated. Finally, we show that our hybrid algorithm can obtain good results with a small size population.     

SMS安全通信系统的研究与实现

随着短信的发展和使用,越来越多的用户使用无线移动网络进行重要数据的传输。但是,在GSM网络中,短信是以明文形式进行传送,这就使得信息在传输过程中极易受到不法分子的各种攻击,因此,必须寻求一种可靠的传输策略。该文针对该问题提出了一个安全解决方案,提出了一种基于认证与加解密的通信架构,确保信息传递的安全性。该方案已在智能手机上得到实现与验证。     

Elementary landscape decomposition of the frequency assignment problem

The Frequency Assignment Problem (FAP) is an important problem that arises in the design of radio networks, when a channel has to be assigned to each transceiver of the network. This problem is a generalization of the graph coloring problem. In this paper we study a general version of the FAP that can include adjacent frequency constraints. Using concepts from landscapes’ theory, we prove that this general FAP can be expressed as a sum of two elementary landscapes. Further analysis also shows that some subclasses of the problem correspond to a single elementary landscape. This allows us to compute the kind of neighborhood information that is normally associated with elementary landscapes. We also provide a closed form formula for computing the autocorrelation coefficient for the general FAP, which can be useful as an a priori indicator of the performance of a local search method.     

UMA方式实现固网与蜂窝网络融合的研究

UMA(Unlicensed Mobile Access)是一种使用ISM(Industrial,Scientific,Medical)频段的无线接入技术。文中分析了目前固网和移动网络存在的问题,并介绍了UMA技术实现固网与蜂窝网络融合的方式。介绍UMA方式是如何融入GSM/GPRS系统中(通过重新定义空中接口以及相关协议),使得固网资源得到充分利用,并且保证互连互通。     

UMTS: the fusion of fixed and mobile networking

The Universal Mobile Telecommunications System (UMTS) represents the emerging European standard for next generation cellular systems that transmit data as well as voice on a global basis. The UMTS goals involve the integration of evolved versions of today's second generation digital cellular systems, together with new terrestrial and satellite components. They also address a fusion of the mobile and fixed networks with a much greater role for intelligent network services. The integration scenarios take little account of the proliferation of IP based networks, and some system redesign is necessary to correct for this. To build on the strengths of GSM, the core UMTS network will evolve from the existing GSM service. UMTS support for data will probably be based on GPRS developed for GSM. Speeds available will vary from approximately 100 Kbps for a pre UMTS, GSM based system up to 2 Mbps for new UMTS radio access networks. Future mobile broadband systems may extend this up to 155 Mbps in restricted environments. The ETSI timetable for introducing these new systems shows the first equipment going into service in 2002, with full availability of third generation UMTS services by 2005     

Landmark-assisted location and tracking in outdoor mobile network

Modern mobile devices integrating sensors, like accelerometers and cameras, are paving the way to the definition of high-quality and accurate geolocation solutions based on the informations acquired by these sensors, and data collected and managed by GSM/3G networks. In this paper, we present a technique that provides geolocation and mobility prediction of mobile devices, mixing the location information acquired with the GSM/3G infrastructure and the results of a landmark matching achieved thanks to the camera integrated on the mobile devices. Our geolocation approach is based on an advanced Time-Forwarding algorithm and on database correlation technique over Received Signal Strength Indication (RSSI) data, and integrates information produced by a landmark recognition infrastructure, to enhance algorithm performances in those areas with poor signal and low accurate geolocation. Performances of the algorithm are evaluated on real data from a complex urban environment.     

A hybrid hopfield network-simulated annealing approach for frequency assignment in satellite communications systems.

A hybrid Hopfield network-simulated annealing algorithm (HopSA) is presented for the frequency assignment problem (FAP) in satellite communications. The goal of this NP-complete problem is minimizing the cochannel interference between satellite communication systems by rearranging the frequency assignment, for the systems can accommodate the increasing demands. The HopSA algorithm consists of a fast digital Hopfield neural network which manages the problem constraints hybridized with a simulated annealing which improves the quality of the solutions obtained. We analyze the problem and its formulation, describing and discussing the HopSA algorithm and solving a set of benchmark problems. The results obtained are compared with other existing approaches in order to show the performance of the HopSA approach.     

射频通信干扰技术的实践应用与分析

文章介绍了广播频段射频干扰的形成机理，干扰的种类以及在工作中遇到不同的干扰采取不同的补救措施。干扰，本质上是指未按频率分配规定的信号占据了合法信号的频率，造成合法信号无法正常工作。因此，对频域的分析过程，就是解决干扰问题的过程，也是广播网络优化工作的重要组成部分。解决干扰问题，不仅要对广播网络常见干扰有深刻的认识，还必须对现有广播制式的频率分配了如指掌。     

GSM与CDMA手机的在线测试技术

提供了一种利用无线测试工具包对CDMA与GSM手机进行功能测试的方法,手机功能测试包括了很多参数的测量。以CDMA手机的校验测试和GSM手机各种特征参数测试为例,验证了该测试系统的有效性和准确性。在CDMA手机的校验测试中,主要根据发射器/接收器功率与手机内部寄存器的初值是否一致来判断校验结果的正确性。在GSM手机测试中,我们通过时域、频域和调制域各种参数的测量验证了本手机测试系统的准确性。     

Design of multiband PIFA with low SAR value for all commercial mobile communication bands

A low profile planar inverted‐F antenna is proposed for mobile handset applications. Thus, our target is to introduce a new antenna that supports both services, the proposed antenna have broadband characteristic which includes all commercial service bands, GSM850/GSM900/GPS/GSM1800/GSM1900/WCDMA2100/802.11b/g/LTE2600 (824–2690 MHz) as well as 802.11a/n (5150–5825 MHz). Overall size of the antenna is 21 × 45 × 8 mm³ is well suited for mobile handsets due to its low profile, small size, wide bandwidth, the radiation patterns are satisfactorily omnidirectional across the antenna's operation bands, and good gain (the gain in some frequency bands is higher than 4 dBi). The antenna not only has a compact size, but also it supports a low specific absorption rate (SAR) radiation at all the operating frequencies. In addition, the proposed antenna is assessed using the finite difference time domain (FDTD) program written with MATLAB to validate the results. The antenna meets three challenging parameters: the compact size, the multiband operation including the low frequency bands, and the low SAR radiation. The measured results exhibit good agreement with the simulation results from CST and the FDTD program written with MATLAB. As a result, the designed antenna is suitable for small mobile devices and slim wireless applications. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:194–201, 2015.