A TRUST MECHANISM-BASED CHANNEL ASSIGNMENT AND ROUTING SCHEME IN COGNITIVE WIRELESS MESH NETWORKS WITH INTRUSION DETECTION

Cognitive Wireless Mesh Networks(CWMN) is a novel wireless network which combines the advantage of Cognitive Radio(CR) and wireless mesh networks.CWMN can realize seamless in-tegration of heterogeneous wireless networks and achieve better radio resource utilization.However,it is particularly vulnerable due to its features of open medium,dynamic spectrum,dynamic topology,and multi-top routing,etc..Being a dynamic positive security strategy,intrusion detection can provide powerful safeguard to CWMN.In this paper,we introduce trust mechanism into CWMN with intrusion detection and present a trust establishment model based on intrusion detection.Node trust degree and the trust degree of data transmission channels between nodes are defined and an algorithm of calcu-lating trust degree is given based on distributed detection of attack to networks.A channel assignment and routing scheme is proposed,in which selects the trusted nodes and allocates data channel with high trust degree for the transmission between neighbor nodes to establish a trusted route.Simulation re-sults indicate that the scheme can vary channel allocation and routing dynamically according to network security state so as to avoid suspect nodes and unsafe channels,and improve the packet safe delivery fraction effectively.

Optimal Power Allocation for Multiuser OFDM-Based Cognitive Heterogeneous Networks

Heterogeneous network(HetNet) as a promising technology to improve spectrum efficiency and system capacity has been concerned by many scholars, which brings huge challenges for power allocation and interference management in multicell network structures. Although some works have been done for power allocation in heterogeneous femtocell networks, most of them focus centralized schemes for single-cell network under interference constraint of macrocell user. In this paper, a sum-rate maximization based power allocation algorithm is proposed for a downlink cognitive Het Net with one macrocell network and multiple microcell networks. The original power allocation optimization problem with the consideration of cross-tier interference constraint, maximum transmit power constraint of microcell base station and inter-cell interference of microcell networks is converted into a geometric programming problem which can be solved by Lagrange dual method in a distributed way. Simulation results demonstrate the performance and effectiveness of the proposed algorithm by comparing with the equal power allocation scheme.

A Resource Scheduling Scheme for Spectrum Aggregation in Cognitive Radio Based Heterogeneous Networks

In spectrum aggregation(SA), two or more component carriers(CCs) of different bandwidths in different bands can be aggregated to support wider transmission bandwidth. The current resource scheduling schemes for spectrum aggregation are not optimal or suitable for CR based heterogeneous networks(Het Nets). Consequently, the authors propose a novel resource scheduling scheme for spectrum aggregation in CR based Het Nets, termed as cognitive radio based resource scheduling(CR-RS) scheme. CR-RS has a three-level structure. Under a dynamic traffic model, an equivalent throughput of the CCs based on the knowledge of primary users(PUs) is given. On this basis, the CR users data transmission time of each CC is equal in CR-RS. The simulation results show that CR-RS has the better performance than the current resource scheduling schemes in the CR based Het Nets. Meanwhile, CR-RS is also effective in other spectrum aggregation systems which are not CR based HetNets.

Self-Coexistence Strategy in Heterogeneous Cognitive Radio Networks

Different from general cognitive wireless networks, there is no centralized scheduling and management infrastructure among heterogeneous cognitive networks. Multiple cells may operate in the same vicinity resulting in unfair spectrum occupation time (when the cells belong to different industries) and degraded performance of the cellular networks. A distributed self-coexistence mechanism is necessary. In this paper, we take the self-coexistence of multi users in heterogeneous scenarios as the problem of spectrum allocation in non-cooperative mode. Hence we propose Fair Self-Coexistence Strategy (FSCS). In this strategy, not only the fairness of occupation time is considered, but also different competitive priority metric based on Quality of Service (QoS) is adopted. Each cognitive cell independently completes the spectrum allocation process, by use of sensing techniques and perceptual information about neighboring network cells. The simulation experiment results show that our spectrum allocation strategy guarantees the fairness among the heterogeneous secondary networks. And in the resource scarce environment, our strategy can effectively achieve the differentiation competition results.

Study on QoS and Communications Capacity in Heterogeneous Network Convergence

To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to be considered and solved in heterogeneous network convergence.Key technologies for a secured QoS and communications capacity analysis under heterogeneous environment are important subjects for research.Key technologies for a secured QoS are mainly on radio resource management algorithms covering Call Admission Control(CAC) algorithm,vertical handover algorithm,heterogeneous resource allocation algorithm and network selection algorithm.The applications of a novel multi-hop in heterogeneous convergence system serve the purposes of network coverage expansion,transmission power reduction,system communication capacity and throughput increase.

Capacity analysis of based-regular-topologies cognitive wireless mesh networks with power control

Capacity analysis is a fundamental and essential work for evaluating the performance of cognitive wireless mesh network （CWMN） which is considered a promising option for the future network. Power control is an efficient way to avoid interference and improve capacity of wireless mesh networks. In this paper, a quantitative result of the per-node average throughput capacity of CWMN with power control is deduced for the first time, which is much helpful for understanding the limitations of CWMN. Firstly, under the large-scale channel fading model and protocol interference model, a closed-form expression for the maximum channel capacity of each node with power control is presented, under the constraint that the interference tolerated by the primary users （PUs） does not exceed a threshold. And then, with the deduced channel capacity result, the per-node average throughput capacity of CWMN is derived based on two regular topologies, i.e. square topology and triangle topology. The simulation results indicate that the capacity is effectively improved with power control, and affected by topology, tolerated interference threshold, the number of cognitive users （CUs） and primary users （PUs）.

Capacity analysis for cognitive heterogeneous networks with ideal/non-ideal sensing

目的:针对认知异构网络中频谱的动态性和干扰的复杂性,利用随机几何理论进行干扰分析并提出网络容量的闭式表达式,为认知异构网络的性能分析提供理论基础。创新:利用随机几何理论分析认知异构网络中复杂的干扰问题,并提出干扰和网络容量的闭式表达式。方法:采用"分而治之"的方法,一方面,针对频谱使用的动态性,利用离散时间马尔可夫链对主用户(宏基站用户)进行建模,得到主用户离开和到达概率,并考虑理想/非理想感知情况,分别计算出两种情况下主用户和次用户的数量;另一方面,针对用户位置的随机性,利用齐次泊松点过程对基站和用户进行建模,再采用随机几何理论对干扰进行分析,提出计算干扰的闭式表达式。最后,利用以上两部分结果分别求出理想/非理想感知情况下网络容量的闭式表达式。结论:利用随机几何理论分析认知异构网络中的干扰和容量具有可行性和准确性;理想感知情况下得到的网络容量要大于非理想感知的情况。

Virtual 5G Network Embedding in a Heterogeneous and Multi-Domain Network Infrastructure

The pursuit of the higher performance mobile communications forces the emergence of the fifth generation mobile communication(5G). 5G network, integrating wireless and wired domain, can be qualified for the complex virtual network work oriented to the cross-domain requirement. In this paper, we focus on the multi-domain virtual network embedding in a heterogeneous 5G network infrastructure, which facilitates the resource sharing for diverse-function demands from fixed/mobile end users. We proposed the mathematical ILP model for this problem.And based on the layered-substrate-resource auxiliary graph and an effective six-quadrant service-type-judgment method, 5G embedding demands can be classified accurately to match different user access densities. A collection of novel heuristic algorithms of virtual 5G network embedding are proposed. A great deal of numerical simulation results testified that our algorithm performed better in terms of average blocking rate, routing latency and wireless/wired resource utilization, compared with the benchmark.

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio(CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques.However,cognitive radio networks(CRNs)may also impose some challenges due to the ever increasing complexity of network architecture,the increasing complexity with configuration and management of large-scale networks,fluctuating nature of the available spectrum,diverse Quality-of-Service(QoS)requirements of various applications,and the intensifying difficulties of centralized control,etc.Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm.In this paper,fundamentals of CR,including spectrum sensing,spectrum management,spectrum mobility and spectrum sharing,have been surveyed,with their paradigms of self-organization being emphasized.Variant aspects of selforganization paradigms in CRNs,including critical functionalities of Media Access Control(MAC)- and network-layer operations,are surveyed and compared.Furthermore,new directions and open problems in CRNs are also identified in this survey.

Network capacity analysis for cellular based cognitive radio VANET in urban grid scenario

The spectrum scarcity of VANETs(Vehicular Ad hoc Networks)can be alleviated by spectrum sharing technology.We present a framework of CCR-VANETs(Cellular-based Cognitive-radio Vehicular Ad hoc Networks).In CCR-VANETs,cellular network performs as primary network while VANET shares the downlink spectrum of cellular network.We consider a scalable urban grid scenario in which vehicles detect available spectrum holes and opportunistically access them according to a carrier-sensing multiple-access protocol.To restrict vehicles'interference to primary receivers,we set a square preservation region around each particular street block where an active base station is located.The number of street blocks in the preservation region is calculated with the practical assumption that vehicles only know the locations of primary transmitters.We analyze the aggregate interference power from primary and secondary networks,then derive the lower-bound of downlink capacity for the primary network and lower-bound of V2V(Vehicle-to-Vehicle)channel capacity for the secondary network respectively.The numerical results demonstrate the impacts of di erent network parameters on inter-networks interference level and network capacities.

End-to-end utility-based resource allocation for multi-RAT nodes in heterogeneous cognitive wireless networks

This paper studies the problem of effective resource allocation for multi-radio access technologies （Multi-RAT） nodes in heterogeneous cognitive wireless networks （HCWNs）. End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.

Inter-cell downlink co-channel interference management through cognitive sensing in heterogeneous network for LTE-A

Heterogeneous network for long term evolution advanced（LTE-A） creates severe interference.It is an urgent task to overcome the interference in macro cellular with low-power base stations（BSs）,such as relay,pico,and femto called subnet nodes.In this paper,the cognitive interference model in interference zone（IZ） of the practical heterogeneous scenario is proposed.Based on investigation of interaction between the macro BS and subnet nodes in this model,the strategy framework of the cognitive critical ratio and power reward factor is set up for interference management aiming to get the maximum net saving power.The study of interference management is transformed into a multiple objective non-linear programming（MONLP） of the maximum saving power for the macro BS and subnet nodes.To facilitate the best compromise solution for both,the MONLP is changed into single objective programming and genetic algorithm（GA） is employed to obtain the global optimum solution.In addition,the practical implementation using the proposed algorithm in heterogeneous network for LTE-A is designed.Finally,numerical evaluation is used to test the applicability of the proposed algorithm,and system level simulation results demonstrate the effectiveness of the proposed interference management scheme.

Capacity-Optimized Access Scheduling Control for Heterogeneous MANETs with MIMO Links

Multiple-input and multiple-output (MIMO) technique can significantly improve transmission reliability and bandwidth efficiency in wireless networks. However, many upper layer aspects of MIMO links, especially in mobile networks with heterogeneous antennas and strong interference environments, need further investigation. In this paper, we study its impact on medium access and network capacity. Since MIMO links can enhance physical layer capacity and co-channel interference suppression that affects network access scheduling directly, we develop a capacity-optimized access scheduling control (COASC) scheme for mobile ad hoc networks (MANETs) with MIMO links. We formulate the distributed scheduling taking the key of optimization into design to improve the network capacity and transmission reliability. Simulation results are presented to show the effectiveness of the proposed scheme.

Throughput Optimization in Cognitive Radio Networks Ensembling Physical Layer Measurement

Wireless networks are developed under the fashion of wider spectrum utilization （e.g., cognitive radio） and multi-hop communication （e.g., wireless mesh networks）. In these paradigms, how to effectively allocate the spectrum to different transmission links with minimized mutual interference becomes the key concern. In this paper, we study the throughput optimization via spectrum allocation in cognitive radio networks （CRNs）. The previous studies incorporate either the conflict graph or SINR model to characterize the interference relationship. However, the former model neglects the accumulative interference effect and leads to unwanted interference and sub-optimal results, while the work based on the latter model neglects its heavy reliance on the accuracy of estimated RSS （receiving signal strength） among all potential links. Both are inadequate to characterize the complex relationship between interference and throughput. To this end, by considering the feature of CRs, like spectrum diversity and non-continuous OFDM, we propose a measurement-assisted SINR-based cross-layer throughput optimization solution. Our work concerns features in different layers： in the physical layer, we present an efficient RSS estimation algorithm to improve the accuracy of the SINR model; in the upper layer, a flow level SINR-based throughput optimization problem for WMNs is modelled as a mixed integer non-linear programming problem which is proved to be NP-hard. To solve this problem, a centralized （1 -ε）-optimal algorithm and an efficient distributed algorithm are provided. To evaluate the algorithm performance, the real-world traces are used to illustrate the effectiveness of our scheme.

Heterogeneous Quality of Experience Guarantees Over Wireless Networks

Quality of experience(Qo E), which is very critical for the experience of users in wireless networks, has been extensively studied. However, due to different human perceptions, quantifying the effective capacity of wireless network subject to diverse Qo E is very difficult, which leads to many new challenges regarding Qo E guarantees in wireless networks. In this paper, we formulate the Qo E guarantees model for cellular wireless networks. Based on the model, we convert the effective capacity maximization problem into the equivalent convex optimization problem. Then, we develop the optimal Qo E-driven power allocation scheme, which can maximize the effective capacity. The obtained simulation results verified our proposed power allocation scheme, showing that the effective capacity can be significantly increased compared with that of traditional Qo E guarantees based schemes.

Joint bandwidth allocation and power control with interference constraints in multi-hop cognitive radio networks

We investigate the bandwidth allocation and power control schemes in orthogonal frequency division multiplexing (OFDM) based multi-hop cognitive radio networks,and the color-sensitive graph coloring (CSGC) model is viewed as an efficient solution to the spectrum assignment problem. We extend the model by taking into account the power control strategy to avoid interference among secondary users and adapt dynamic topology. We formulate the optimization problem encompassing the channel allocation,power control with the interference constrained below a tolerable limit. The optimization objective with two different optimization strategies focuses on the routes rather than the links as in traditional approaches. A heuristic solution to this nondeterministic polynomial (NP)-hard problem is presented,which performs iterative channel allocation according to the lowest transmission power that guarantees the link connection and makes channel reuse as much as possible,and then the transmission power of each link is maximized to improve the channel capacity by gradually adding power level from the lowest transmission power until all co-channel links cannot satisfy the interference constraints. Numerical results show that our proposed strategies outperform the existing spectrum assignment algorithms in the performance of both the total network bandwidth and minimum route bandwidth of all routes,meanwhile,saving the transmission power.

Cognitive Congestion Control for Data Portals with Variable Link Capacity

Network congestion, one of the challenging tasks in communication networks, leads to queuing delays, packet loss, or the blocking of new connections. In this study, a data portal is considered as an application-based network, and a cognitive method is proposed to deal with congestion in this kind of network. Unlike previous methods for congestion control, the proposed method is an effective approach for congestion control when the link capacity and information inquiries are unknown or variable. Using sufficient training samples and the current value of the network parameters, available bandwidth is adjusted to distribute the bandwidth among the active flows. The proposed cognitive method was tested under such situations as unexpected variations in link capacity and oscillatory behavior of the bandwidth. Based on simulation results, the proposed method is capable of adjusting the available bandwidth by tuning the queue length, and provides a stable queue in the network.