Dynamic RAT selection for multiple calls in heterogeneous wireless networks using group decision-making technique

Existing radio access technology (RAT)-selection algorithms for heterogeneous wireless networks (HWNs) do not consider the problem of RAT selection for a group of calls from a multimode terminal (MT). Multimode terminals (MTs) for next generation wireless networks have the capability to support two or more classes of calls simultaneously. When a new call is initiated on an MT already having an ongoing call in an HWN, the current RAT may no longer be suitable for the two calls (incoming call and the existing call). Thus, a new RAT may be more suitable for the two calls. The problem of RAT selection for two or more calls from an MT in an HWN is a group decision problem. This paper addresses the problem of RAT selection for a group of calls from an MT in an HWN by using the modified TOPSIS group decision-making technique. The paper proposes a dynamic RAT-selection algorithm that selects the most suitable RAT for a single call or group of calls from an MT in an HWN. The algorithm considers users’ preferences for individual RATs, which vary with each class of calls, in making RAT selection decisions in an HWN. A user’s preference for each of the available RATs is specified by weights assigned by the user to RAT selection criteria for different classes of calls. Based on the assigned weights, the proposed algorithm aggregates individual calls’ weights specified by the user to make a RAT-selection decision for a group of calls. In order to reduce the frequency of vertical handover, the proposed algorithm uses RAT preference margin in making RAT selection decisions. RAT preference margin is a measure of the degree to which the newly preferred RAT is better than the current RAT. Performance of the proposed algorithm is evaluated through numerical simulations. Results are given to show the effectiveness of the proposed RAT-selection algorithm.     

Investigation on MDP-based radio access technology selection in heterogeneous wireless networks

The new generation of wireless networks is characterized by heterogeneity i.e. the coexistence of two or more radio access technologies (RAT) in the same geographical area. While this coexistence of RATs offers various advantages, it also imposes many challenges for the network operator, whose aim is to maximize the generated revenue while satisfying the customers’ increasing demands. One important mechanism in heterogeneous wireless networks (HWN) is the RAT selection. It is normally triggered when a new call arrives, and provides the decision on whether the call can be admitted or not, and by which RAT it has to be served. Different approaches can be used to tackle the problem of RAT selection in HWNs. In this paper, we study Markov Decision Process (MDP)-based RAT selection in a cellular/WLAN heterogeneous network where the maximization of the revenue is considered as objective. An optimal RAT selection policy is therefore derived. The performance of the optimal scheme is evaluated in comparison with two other policies, namely Cellular-First policy and Load Balancing policy.     

Network Selection Decisions for Multiple Calls Based on Consensus Level

Next generation multimode terminals have the capability to support different classes of calls simultaneously as well as the ability to connect to two or more radio access technologies (RATs), at the same time, in a heterogeneous wireless network. For a mobile terminal having multiple classes of simultaneous handoff calls (such as file download and video sessions), RAT selection decisions can be made independently for individual calls in the group or jointly for the entire group of calls. Both independent and group RAT selection decisions for multiple calls have advantages and disadvantages. Existing RAT selection algorithms have focused on RAT selection decisions for single calls. Therefore, this paper investigates independent call and group call RAT selection decisions for multiple calls in heterogeneous wireless networks, and proposes a scheme that makes RAT selection decisions for multiple calls based on a consensus level among the multiple calls to be admitted. When this consensus level is among multiple calls to be admitted into a particular RAT and is equal to or above a certain threshold value, a group decision is used. Otherwise, independent decisions are made. The performance of the proposed RAT selection scheme is evaluated in a three service three RAT heterogeneous network, supporting multihomed terminals. Simulation results are given to show the effectiveness of the proposed scheme.     

A semi-Markov decision process-based joint call admission control for inter-RAT cell re-selection in next generation wireless networks

In the next generation wireless networks (NGWNs), where different radio access technologies (RAT) will coexist and work in collaboration to provide ubiquitous access, a mechanism called Joint Call Admission Control (JCAC) will play an important role by deciding whether or not an incoming service request will be accepted according to an admission constraint as well as determining in which RAT (among the available) it will be connected. In this paper, we propose an optimal JCAC for inter-RAT cell re-selection problem also referred to as initial RAT selection in co-located wireless networks, which supports both real-time services and non-real-time services. To properly meet the JCAC goals, we propose a cost function that weigh two criteria: the blocking cost function, which takes into account the priority of each service class in each RAT, and the alternative acceptance cost, which reflects the multiplicity of RATs working in a collaborative fashion, mandatory in NGWN. We use the framework of Semi-Markov Decision Process (SMDP) to formulate the optimization problem and the value iteration algorithm to compute the optimal policy. Our model still takes into consideration the ratio between the radius of the co-located RATs and shows how it may impact on optimal initial RAT selection. Numerical results, supported by an analysis of the structure of the optimal policy, show that the proposed optimal JCAC selects for real-time service class the biggest RAT and for non-real-time service class the smallest one. This optimal JCAC policy is ratified by the current trend in the design of NGWN and also follows the 3rd Generation Partnership Project (3GPP) expectations.     

软件定义网络的异构无线网络资源分配框架

针对各种智能设备在移动蜂窝网络中的普及及移动流量需求日益增长的问题,研究控制无线电带宽并将其分配给多个无线电用户设备,提出了一个基于软件定义网络（SDN）的资源分配框架,以及LTE/WLAN多无线电网络中异构资源分配算法。该框架将SDN范式应用到LTE-WLAN集成网络的异构资源分配,并进行了扩展,以整体的方式分配LTE/WLAN多无线电网络中的异构射频带宽。通过将集中式解决方案的功能分解到指定的网络实体的方式,来处理异构资源。模拟实验表明,所提框架可以较好地平衡网络吞吐量和用户公平性,且算法收敛性较好。     

Radio resource allocation problems for OFDMA cellular systems

Orthogonal frequency division multiple-access (OFDMA) manages to efficiently exploit the inherent multi-user diversity of a cellular system by performing dynamic resource allocation. Radio resource allocation is the technique that assigns to each user in the system a subset of the available radio resources (mainly power and bandwidth) according to a certain optimality criterion on the basis of the experienced link quality. In this paper we address the problem of resource allocation in the downlink of a multi-cellular OFDMA system. The allocation problem is formulated with the goal of minimizing the transmitted power subject to individual rate constraint for each user. Exact and heuristic algorithms are proposed for the both the single-cell and the multi-cell scenario. In particular, we show that in the single-cell scenario the allocation problem can be efficiently solved following a network flow approach. In the multi-cell scenario we assume that all cells use the same frequencies and therefore the allocation problem is complicated by the presence of strong multiple access interference. We prove that the problem is strongly NP-hard, and we present an exact approach based on an MILP formulation. We also propose two heuristic algorithms designed to be simple and fast. All algorithms are tested and evaluated through an experimental campaign on simulated instances. Experimental results show that, although suboptimal, a Lagrangian-based heuristic consisting in solving a series of minimum network cost flow problems is attractive for practical implementation, both for the quality of the solutions and for the small computational times.     

Efficient allocation of resources in multiple heterogeneous Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are useful for a wide range of applications, from different domains. Recently, new features and design trends have emerged in the WSN field, making those networks appealing not only to the scientific community but also to the industry. One such trend is the running different applications on heterogeneous sensor nodes deployed in multiple WSNs in order to better exploit the expensive physical network infrastructure. Another trend deals with the capability of accessing sensor generated data from the Web, fitting WSNs in novel paradigms of Internet of Things (IoT) and Web of Things (WoT). Using well-known and broadly accepted Web standards and protocols enables the interoperation of heterogeneous WSNs and the integration of their data with other Web resources, in order to provide the final user with value-added information and applications. Such emergent scenarios where multiple networks and applications interoperate to meet high level requirements of the user will pose several changes in the design and execution of WSN systems. One of these challenges regards the fact that applications will probably compete for the resources offered by the underlying sensor nodes through the Web. Thus, it is crucial to design mechanisms that effectively and dynamically coordinate the sharing of the available resources to optimize resource utilization while meeting application requirements. However, it is likely that Quality of Service (QoS) requirements of different applications cannot be simultaneously met, while efficiently sharing the scarce networks resources, thus bringing the need of managing an inherent tradeoff. In this paper, we argue that a middleware platform is required to manage heterogeneous WSNs and efficiently share their resources while satisfying user needs in the emergent scenarios of WoT. Such middleware should provide several services to control running application as well as to distribute and coordinate nodes in the execution of submitted sensing tasks in an energy-efficient and QoS-enabled way. As part of the middleware provided services we present the Resource Allocation in Heterogeneous WSNs (SACHSEN) algorithm. SACHSEN is a new resource allocation heuristic for systems composed of heterogeneous WSNs that effectively deals with the tradeoff between possibly conflicting QoS requirements and exploits heterogeneity of multiple WSNs.     

Development of Web services-based Multidisciplinary Design Optimization framework

The defining characteristic of a Multidisciplinary Design Optimization (MDO) strategy or method, compared to the more traditional, sequential approach to conducting design work, is that the contributions of all mutually influential disciplines are concurrently taken into account. Therefore, a framework that allows the implementation of MDO methods must be an environment for design synthesis. It is also desired that the user of an MDO framework be capable of efficiently integrating and managing the resources distributed over heterogeneous platforms. This paper proposes a Web services-based MDO framework that enables the synthesis of available disciplinary and cross-disciplinary resources for MDO via the Globus Toolkit. Examples of organic and autonomous execution of MDO methods are presented to highlight the effectiveness of modern automation techniques, such as workflow management system and agent technology. The salient features of a planned collaborative design environment, which will be built through Web-based user interfaces, are discussed last.     

Immune optimization algorithm for solving joint call admission control problem in next-generation wireless network

The integration of radio access networks with different radio access technologies (RATs) is one of the remarkable characteristics of the next-generation wireless networks (NGWNs). In NGWN, the users with multi-network interface terminals should be able to select independently radio access network to obtain the best service. Therefore, joint call admission control (JCAC) schemes are required to select the most appropriate radio access network (RAN) for incoming calls. We propose an immune algorithm-based JCAC (IA-JCAC) scheme with users centric in order to enhance user's satisfaction. However, JCAC algorithms with users centric can lead to highly unbalanced traffic load among the available RANs in NGWN because users act independently, and most of them may prefer to be connected through a particular RAN. Highly unbalanced traffic load in NGWN will result in high overall call blocking/dropping probability and poor radio result utilization. To solve this problem, we employ dynamic pricing for balancing traffic load among available RANs in heterogeneous wireless networks where users' preferences are considered in decision-making on RAT selection. The proposed IA-based JCAC scheme is compared with another scheme that does not use the dynamic pricing on the performance. The simulation result shows the effectiveness of the proposed IA-JCAC scheme is improved significantly.     

Optimizing energy efficiency of a multi-radio mobile device in heterogeneous beyond-4G networks

In this paper, we address the operation of a multi-radio mobile device in heterogeneous wireless deployments. We assume that such a device may efficiently control its radio interfaces when using the available radio access technologies. In particular, we investigate the potential of flexible transmit power allocation and develop a provably optimal power control scheme that strictly maximizes the energy efficiency of the mobile device, while at the same time satisfies the minimum required level of the user data rate. When compared against simpler (heuristic) power control strategies, our solution always demonstrates the best energy efficiency of the multi-radio device by enabling collaborative operation between several radio technologies, which makes it a useful benchmark for the future integrated beyond-4G wireless networks.     

NR在60GHz定位过程的隐藏节点规避方法

60GHz非授权频段因其波长短、频段宽的无线传播特性可实现更高的定位信号测量精度,因此5G NR-U设备基于60GHz频段进行高精度定位倍受关注;但是由于5G网络是多网异构共存的,存在众多不同无线接入技术（RAT,radio access technology）的设备,潜在的隐藏节点多,即使5G NR-U设备采用先听后说（LBT,listen before talk）方式接入60GHz无线信道,仍无法有效规避隐藏节点,有时会严重干扰定位信号传输而影响定位性能;针对以上隐藏节点问题,文中提出对定位信号资源集中的多个定位信号资源分别配置不同的空间关系,接收端根据定位信号的测量结果实时动态调整其空间关系,尽可能多地规避潜在的隐藏节点;仿真验证结果表明所提方法可将定位信号的测量精度提升了约27%,显著降低定位误差。     

基于认知无线电技术的动态频谱分配方案研究

随着物联网的发展,人们能够更加方便快捷地利用智能终端,随时随地接入到无线网络中进行业务数据传输.然而,激增的移动用户数量和业务的带宽需求,使得无线频谱资源日益稀缺,现有固定式频谱分配方案面临巨大挑战.面向物联网发展,如何满足用户的高移动性和呈爆炸式增长的业务传输需求成为物联网研究的重点.认知无线电技术,一方面允许用户终端自适应感知所处环境的频谱资源空闲信息,为用户营造一个无缝的接入环境,保证用户的高移动性;另一方面通过动态频谱分配有效地解决了频谱资源稀缺和现有授权频谱资源利用率低的问题,为用户的海量数据传输提供保证.作者基于认知无线电技术,提出了一个用户终端和网络端共同参与决策的两级动态频谱分配框架结构,并提出了两级动态频谱分配方案.该方案设计包含:空闲频谱资源排序选择算法和集中式的联合优化匹配算法.通过用户终端和网络端的协同工作,文中所提出的两级动态频谱分配方案能够有效满足用户的高移动性和业务传输服务质量需求,实现空闲频谱资源利用率和频谱间切换概率的联合优化,为移动用户的海量数据传输提供保证.仿真实验结果表明,与传统图匹配方法相比较,该方案能够平均提高全网服务质量有效吞吐量70%,平均降低频谱间切换概率56%.     

Call admission control policies in cellular wireless networks with spectrum renting

Radio spectrum is scarce and precious resource in wireless networks. To efficiently utilize radio spectrum, a wireless network can rent radio channels from another wireless network and returns back the rented channels when the rented channels are required to be withdrawn. The rental and withdrawal of radio channels result in two phenomena: (i) variable number of radio channels in a wireless network and (ii) call dropping due to the channel withdrawal. Call admission control aims to provide good quality-of-services for mobile users while efficiently utilize radio channels. Many call admission control policies in the previous literatures were studied without the two phenomena. In this paper, we study three call admission control policies, namely, fixed-reservation policy, single-threshold policy and multiple-threshold policy in a wireless network which rents channels from another wireless network. We develop numerical analyses to analyze and compare the performances of the three call admission control policies. Numerical results show that the multiple-threshold policy produces higher throughput than the single-threshold and fixed-reservation policies under the same constraint of quality-of-services.     

Cognitive radio network security: A survey

Recent advancements in wireless communication are creating a spectrum shortage problem on a daily basis. Recently, Cognitive Radio (CR), a novel technology, has attempted to minimize this problem by dynamically using the free spectrum in wireless communications and mobile computing. Cognitive radio networks (CRNs) can be formed using cognitive radios by extending the radio link features to network layer functions. The objective of CRN architecture is to improve the whole network operation to fulfil the user's demands anytime and anywhere, through accessing CRNs in a more efficient way, rather than by just linking spectral efficiency. CRNs are more flexible and exposed to wireless networks compared with other traditional radio networks. Hence, there are many security threats to CRNs, more so than other traditional radio environments. The unique characteristics of CRNs make security more challenging. Several crucial issues have not yet been investigated in the area of security for CRNs. A typical public key infrastructure (PKI) scheme which achieves secure routing and other purposes in typical ad hoc networks is not enough to guarantee the security of CRNs under limited communication and computation resources. However, there has been increasing research attention on security threats caused specifically by CR techniques and special characteristics of CR in CRNs. Therefore, in this research, a survey of CRNs and their architectures and security issues has been carried out in a broad way in this paper.     

PicoRadio supports ad hoc ultra-low power wireless networking

Technology advances have made it conceivable to build and deploy dense wireless networks of heterogeneous nodes collecting and disseminating wide ranges of environmental data. Applications of such sensor and monitoring networks include smart homes equipped with security, identification, and personalization systems; intelligent assembly systems; warehouse inventory control; interactive learning toys; and disaster mitigation. The opportunities emerging from this technology give rise to new definitions of distributed computing and the user interface. Crucial to the success of these ubiquitous networks is the availability of small, lightweight, low-cost network elements, which the authors call PicoNodes. The authors present a configurable architecture that enables these opportunities to be efficiently realized in silicon. They believe that this energy-conscious system design and implementation methodology will lead to radio nodes that are two orders of magnitude more efficient than existing solutions     

EasiTest:多Radio异构无线传感器网络测试平台

设计并实现了一种多Radio的异构无线传感器网络综合测试平台系统EasiTest,该平台采用了两种不同性能、功能的测试节点,可以支持大规模、异构传感器网络综合性能测试以及应用性研究.平台内采用了结构复杂、功能完备的多Radio的EZ271作为中高速测试节点,以及以 WiFi作为测试通道的EZ521作为中低速测试节点;系统提供传感/测试数据收集、数据管理、资源分配、服务器状态检查、节点状态检查与参数配置以及资源注册共享等功能模块,保障用户能够方便快捷地实现功能实验;通过友好的 Web访问页面,用户能够模拟真实的网络环境对多种类,如802.15.4,802.11协议等,以及多层次,如 MAC层、路由层、应用层等的网络协议研究成果进行灵活的综合实验验证,从而能够有效地提高无线传感器网络技术的研究效率.     

Instant overbooking framework for cognitive radio networks

In recent years, new emerging wireless technologies necessitate more spectrum resources compared to before. Related to this fact, cognitive radio and its capabilities provide promising functionalities in efficient management of the spectrum. In this paper, to maximize both spectrum utilization and revenue of network operators, we propose an Instant Overbooking Framework for Cognitive Radio networks (IOFCR) where different overbooking policies can be employed. Besides, the framework includes policies in order to decide which requesting secondary users (SUs) can be denied and which Active SUs can be ejected when a primary user (PU) activity is sensed. The effects of different pricing strategies used in a booking interval are also analyzed. To evaluate IOFCR, we use performance measures such as total net revenue, spectrum utilization, overbooking limit, number of free blocks, average service period, percentage of denied SUs forwarding their booking request and percentage of ejected Active SUs. In addition to being a first overbooking framework for Cognitive Radio Networks that takes several system parameters like PU on-rate, Active SU on-rate and Requesting SU show-rate into the account, to the best of our knowledge, this paper makes key contributions concerning the pricing policies, denial of requesting SUs, ejection and priority levels of active SUs. Finally, we numerically analyze the IOFCR performance by conducting numerous simulations and show the efficiency and validity in accordance with comprehensive measures mentioned above.     

Modeling and analysis of nano-sized GMRs based on Co,NiFe and Ni materials

Magnetic simulation method is introduced to analyze giant magnetoresistances(GMRs)in nanoscale for nano-sized biosensors.A spin valve model with special gridding corresponding to the exchange interaction length is proposed to study the influence of easy axes,exchange coefcients,pinning fields and feature widths on magnetization reversals and hysteresis characteristics of nano-sized GMRs with diferent pinned layer and free layer materials of Co,NiFe and Ni.The switching field is found to be almost linear with the pinning field and decrease with the absolute exchange coefcients and the feature widths for the nano-sized GMRs.The increase rate of each depends on the spin valve stacks.Further investigations into variations of the magnetization distribution reveal that the initial magnetization distribution and the magnetization reversal mode depend greatly on easy axes and materials The dependence on easy axes based mainly on the magnetocrystalline anisotropy is illustrated in detail.     

基于中间模型的异构数据资源语义映射方法

异构数据资源的语义映射,是大数据时代数据集成与共享研究中的一个关键问题。围绕语义搜索的应用需求,针对海量异构数据资源到领域知识本体的语义映射问题,提出基于中间模型的映射算法,通过模型解析转换、映射规则设计、映射策略选择、映射关系表达等最终获得二者的映射关系。系统面向用户提供基于知识本体的统一视图,屏蔽了底层数据资源的异构性,保证了用户对异构数据资源的透明访问和准确理解,提供了一种灵活、通用、可扩展的语义集成机制,为准确高效的语义搜索应用提供支持。     

High-Level Design Approach for the Specification of Cognitive Radio Equipments Management APIs

Cognitive Radio (CR) equipments are radio devices that support the smart facilities offered by future cognitive networks. Even if several categories of equipments exist (terminal, base station, smart PDA, etc.), each requiring different processing capabilities (and associated cost or power consumption), these equipments have to integrate also a set of new capabilities as regards CR support, in addition to the usual radio signal processing elements. This implies real-time radio adaptation and sensing capabilities, but not only. We assert that it is necessary to add inside the radio equipments some management facilities for that purpose, and we propose in this paper a high-level design approach for the specification of a management framework. This includes a set of designing rules, based on hierarchical units that are distributed over three levels, and the associated APIs necessary to efficiently manage CR features inside a CR equipment. The proposed architecture is called HDCRAM (Hierarchical and Distributed Cognitive Architecture Management). HDCRAM is an extension of a former hierarchical and distributed reconfiguration management (HDReM) architecture, which is derived from our previous research on Software Defined Radio (SDR). The HDCRAM adds to the HDReM’s reconfiguration management facilities the necessary new management features, which enable the support of sensing and decision making facilities. It consists in the combination of one Cognitive Radio Management Unit (CRMU) with each Reconfiguration Management Unit (ReMU) distributed within the equipment. Each of these CRMU is in charge of the capture, the interpretation and the decision making according to its own goals. In this Cognitive Radio context, the term “decision” refers to the adaptation of the radio parameters to the equipment’s environment. This paper details the HDCRAM’s management functionality and structure. Moreover, in order to facilitate the early design phase of the management specification, which is new in radio design, HDCRAM has also been modeled with a meta-programming language based on UML. But beyond the first objective of high-level specification, we have also derived a simulator from the obtained meta-model, thanks to the use of an executable language. This gives the opportunity to specify the CR needs and play a wide variety of scenarios, in order to validate the CR equipment’s design. This approach provides high-level design facilities for the specification of cognitive management APIs inside a cognitive radio equipment.