Utility-based emergency service and power control scheme in multi-hop WIFI/LTE heterogeneous networks

In recent years, integration and heterogeneous of network have become the two major characteristics of the future evolution about wireless communication. In this paper, multi-hop WIFI/LTE networks and dual-mode single communication mobile terminals, i.e. integral association, are considered in flat converged network. With the constraint of Quality of Service (QoS) for emergency service and load balance, a distributed optimization algorithms is constructed by jointing power control, vertical handoff and routing. More specifically, the framework model of network is represented by a generalized network utility maximization (NUM) problem. Furthermore, achieving utility maximization is proved to be NP-hard. Then, a generic framework is given to simplify the problem to arrive a distributed optimization algorithm. Simulation results show that the distributed algorithm can approach the optimal solution. Compared with greedy algorithm, the proposed one is able to improve the network utility on the basis of ensuring load balancing as much as possible.

[1]  Cheng-Yan Kao,et al.  Applying the genetic approach to simulated annealing in solving some NP-hard problems , 1993, IEEE Trans. Syst. Man Cybern..

[2]  Jamil Y. Khan,et al.  Radio Resource Management of Composite Wireless Networks: Predictive and Reactive Approaches , 2012, IEEE Transactions on Mobile Computing.

[3]  T. Velmurugan,et al.  An optimized algorithm for vertical handoff in heterogeneous wireless networks , 2013, 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES.

[4]  Yang Du,et al.  An Adaptive Transmission Scheme Based on Emergency for Heterogeneous Network Convergence , 2011, 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing.

[5]  Brunilde Sansò,et al.  A Tabu Search Algorithm for the Location of Data Centers and Software Components in Green Cloud Computing Networks , 2013, IEEE Transactions on Cloud Computing.

[6]  Chung-Ju Chang,et al.  A Utility Function-based Access Selection Method for Heterogeneous WCDMA and WLAN Networks , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Michael D. Logothetis,et al.  A study on dynamic load balance for IEEE 802.11b wireless LAN , 2002 .

[8]  Jing Zhu,et al.  Multi-Radio Coexistence: Challenges and Opportunities , 2007, 2007 16th International Conference on Computer Communications and Networks.

[9]  Prasant Mohapatra,et al.  Integration Gain of Heterogeneous WiFi/WiMAX Networks , 2011, IEEE Transactions on Mobile Computing.

[10]  Wen Liu,et al.  Noisy Chaotic Neural Networks With Variable Thresholds for the Frequency Assignment Problem in Satellite Communications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[11]  V. Vaidehi,et al.  Always Best-Connected QoS integration model for the WLAN, WiMAX Heterogeneous Network , 2006, First International Conference on Industrial and Information Systems.

[12]  Yang Yang,et al.  Mobile cellular networks and wireless sensor networks: toward convergence , 2012, IEEE Communications Magazine.

[13]  Dusit Niyato,et al.  A Cooperative Game Framework for Bandwidth Allocation in 4G Heterogeneous Wireless Networks , 2006, 2006 IEEE International Conference on Communications.

[14]  J. McCall,et al.  Genetic algorithms for modelling and optimisation , 2005 .

[15]  Xuanli Wu,et al.  Load balancing algorithm with multi-service in heterogeneous wireless networks , 2011, 2011 6th International ICST Conference on Communications and Networking in China (CHINACOM).

[16]  Lipo Wang,et al.  Rule extraction by genetic algorithms based on a simplified RBF neural network , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[17]  Dong In Kim,et al.  Per Cluster Based Opportunistic Power Control for Heterogeneous Networks , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).