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.

Intelligent handoff decision in radio heterogeneous network

Abstract： In order to improve the accuracy of vertical handoff decision for radio heterogeneous network, this paper proposes an intelligent adaptive multi-criteria vertical handoff （AMVHO） decision algorithm. This algo- rithm uses a fuzzy inference system （FIS） and a modified Elman neural network （MENN）. The FIS adopts the crucial criteria of vertical handoff as input variables and makes handoff decision based on the defined rule base. The MENN helps to predict the number of users of the after-handoff network, which is a pivotal variable of the FIS. Simulation results show that, compared with the conventional method, the AMVHO decision algorithm a- chieves better performance in guaranteeing the quality of service （QoS） of the after-handoff communication.

Genetic approach for Cell-by-Cell dynamic spectrum allocation in the heterogeneous scenario

In this paper,a genetic algorithm (GA) is investigated to deal with cell-by-cell dynamic spectrumallocation (DSA) in the heterogeneous scenario with temporal and spatial traffic demand changes,whichis also known as a difficult combinatorial optimization problem.A new two-dimensional chromosome encodingscheme is defined according to characteristics of the heterogeneous scenario,which prevents forminginvalid solutions during the genetic operation and enables much faster convergence.A novel randomcoloring gene generation function is presented which is the basic operation for initialization and mutationin the genetic algorithm.Simulative comparison demonstrates that the proposed GA-based cell-by-cellDSA outperforms the conventional contiguous DSA scheme both in terms of spectral efficiency gain andquality of service (QoS) satisfaction.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.

Genetic algorithm for autonomic joint radio resource management in end-to-end reconfigurable systems

This article presents the genetic algorithm （GA） as an autonomic approach for the joint radio resource management （JRRM） amongst heterogeneous radio access technologies （RATs） in the end-to-end reconfigurable systems. The joint session admission control （JOSAC） and the bandwidth allocation are combined as a specific decision made by the operations of the genetic algorithm with certain advisable modifications. The proposed algorithm is triggered on the following two conditions When a session is initiated, it is triggered for the session to camp on the most appropriate RAT and select the most suitable bandwidth for the desired service. When a session terminates, it is also used to adjust the distribution of the ongoing sessions through the handovers. This will increase the adjustment frequency of the JRRM controller for the best system performance. Simulation results indicate that the proposed autonomic JRRM scheme not only effectively reduces the handover times, but also achieves well trade-off between the spectrum utility and the blocking probability.