Non-cooperative game for network access selection in heterogeneous integrated networks

The integration of different heterogeneous access networks is one of the remarkable characteristics of the next generation network,in which users with multi-network interface terminals can independently select access network to obtain the most desired service.A kind of unified quantification model of non-monotone quality of service(QoS) and a model of non-cooperative game between users and networks are proposed for heterogeneous network access selection.An optimal network pricing mechanism could be formulated by using a novel strategy which is used in this non-cooperative game model to balance the interests of both the users and the networks.This access network selection mechanism could select the most suitable network for users,and it also could provide the basis when formulating QoS standards in heterogeneous integrated networks.The simulation results show that this network selection decision-making algorithm can meet the users' demand for different levels service in different scenes and it can also avoid network congestion caused by unbalanced load.

Energy-efficient Scheme for Multiple Access Network Selection Using Principal Component Analysis

This paper brings forward a novel dynamic multiple access network selection scheme(NDMAS),which could achieve less energy loss and improve the poor adaptive capability caused by the variable network parameters.Firstly,a multiple access network selection mathematical model based on information theory is presented.From the perspective of information theory,access selection is essentially a process to reduce the information entropy in the system.It can be found that the lower the information entropy is,the better the system performance fulfills.Therefore,this model is designed to reduce the information entropy by removing redundant parameters,and to avoid the computational cost as well.Secondly,for model implementation,the Principal Component Analysis(PCA) is employed to process the observation data to find out the related factors which affect the users most.As a result,the information entropy is decreased.Theoretical analysis proves that system loss and computational complexity have been decreased by using the proposed approach,while the network QoS and accuracy are guaranteed.Finally,simulation results show that our scheme achieves much better system performance in terms of packet delay,throughput and call blocking probability than other currently existing ones.

Dynamic Target Wireless Network Selection Technique Using Fuzzy Linguistic Variables

Even though various wireless Net- work Access Technologies （NATs） with dif- ferent specifications and applications have been developed in the recent years, no single wireless technology alone can satisfy the any- time, anywhere, and any service wire- less-access needs of mobile users. A real seamless wireless mobile environment is only realized by considering vertical and horizontal handoffs together. One of the major design issues in heterogeneous wireless networks is the support of Vertical Handoff （VHO）. VHO occurs when a multi-interface enabled mobile terminal changes its Point of Attachment （PoA） from one type of wireless access technology to another, while maintaining an active session. In this paper we present a novel multi-criteria VHO algorithm, which chooses the target NAT based on several factors such as user preferences, system parameters, and traf- tic-types with varying Quality of Service （QoS） requirements. Two modules i.e., VHO Neces- sity Estimation （VHONE） module and target NAT selection module, are designed. Both modules utilize several ＂weighted＂ users＇ and system＇s parameters. To improve the robust- ness of the proposed algorithm, the weighting system is designed based on the concept of fuzzy linguistic variables.

Access network selection strategy using position prediction in heterogeneous wireless networks

Access network selection(ANS)strategy is one of the most important issues in future heterogeneous networks.The current solutions for this issue are not very efficient because they do not consider the motion scenarios and cannot predict the next location for mobile node.In this paper,an effective ANS strategy based on global positioning system(GPS)is proposed.Making use of information such as position coordinates and moving velocity acquired by GPS,the ANS proposed can predict the next point of attachment for mobile node(MN),assist existing ANS strategy to make more reasonable decision,and achieve better performance.

Secure resource allocation against colluding eavesdropping in a user-centric cell-free massive multiple-input multiple-output system

We investigate the resource allocation problem of a cell-free massive multiple-input multiple-output system under the condition of colluding eavesdropping by multiple passive eavesdroppers.To address the problem of limited pilot resources,a scheme is proposed to allocate the pilot with the minimum pollution to users based on access point selection and optimize the pilot transmission power to improve the accuracy of channel estimation.Aiming at the secure transmission problem under a colluding eavesdropping environment by multiple passive eavesdroppers,based on the local partial zero-forcing precoding scheme,a transmission power optimization scheme is formulated to maximize the system’s minimum security spectral efficiency.Simulation results show that the proposed scheme can effectively reduce channel estimation error and improve system security.

A novel approach for radio resource management in multi-dimensional heterogeneous 5G networks

A GRA-BKP(Grey Relational Analysis-Bounded Knapsack Problem)scheme was proposed for the radio resource management of the 5G networks.It consists of two steps,access selection and admission control.The former step was executed via GRA,whereas the latter problem was formulated as a bounded knapsack problem.Accordingly,an optimal solution of the BKP was given for access selection a greedy algorithm,GRA-Greedy,was proposed for admission control.The simulation results show that the GRA-BKP scheme can effectively increase system profit and decrease the drop-ping probability compared with the existing scheme.In addition,GRA-Greedy achieves comparable perform-ance with the optimal solution GRA-DP,but its computational complexity is much lower than that of the latter.