Resource Allocation Optimization of UAVs-Enabled Air-Ground Collaborative Emergency Network in Disaster Area

doi:10.23940/ijpe.19.08.p13.21332144

Abstract

Abstract: This paper aims to improve the efficiency of UAVs-enabled air-ground collaborative emergency networks through resource allocation optimization. The bandwidth assignment, UAVs' flight trajectories, and transmission power were jointly optimized to maximize the achievable signal rate of all terminal receivers in the downlink. The block coordinate descent method and successive convex approximation were utilized to solve the established mixed-integer non-convex optimization problem. Then, an emergency communication scenario was designed to run different emulation experiments, which were used to verify that the proposed algorithm was effective. Numerous results showed that the proposed algorithm can attain great performances in this scenario. Compared with single factor optimizing strategies, the users' signal rate can be improved by 5%-28% through joint optimization.

Key words: UAV, air-ground collaborative network, resource allocation, signal rate maximization, non-convex problem, mix-integer optimization

Lei Wu and Weijian Wang. Resource Allocation Optimization of UAVs-Enabled Air-Ground Collaborative Emergency Network in Disaster Area [J]. Int J Performability Eng, 2019, 15(8): 2133-2144.

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References

[1] Y. Zeng, R. Zhang,T. J. Lim, “Wireless Communications with Unmanned Aerial Vehicles: Opportunities and Challenges,” IEEE Communications Magazine, Vol. 54, No. 5, pp. 36-42, 2016
[2] M. Mozaffari, W. Saad, M. Bennis,M. Debbah, “Drone Small Cells in the Clouds: Design, Deployment and Performance Analysis,” inProceedings of 2015 IEEE Global Communications Conference, pp. 1-6, IEEE, 2015
[3] C. T. Cicek, H. Gultekin, B. Tavli,H. Yanikomeroglu, “UAV Base Station Location Optimization for Next Generation Wireless Networks: Overview and Future Research Directions,” inProceedings of the 1^st IEEE Unmanned Vehicle Systems (UVS) Conference, 2018
[4] M. Mozaffari, W. Saad, M. Bennis, Y. H. Nam,M. Debbah, “A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems,” IEEE Communications Surveys & Tutorials, Vol. 21, No. 3, pp. 2334-2360, 2019
[5] A. Al-Hourani, S. Kandeepan,S. Lardner, “Optimal LAP Altitude for Maximum Coverage,” IEEE Wireless Communications Letters, Vol. 3, No. 6, pp. 569-572, 2014
[6] M. Mozaffari, W. Saad, M. Bennis,M. Debbah, “Efficient Deployment of Multiple Unmanned Aerial Vehicles for Optimal Wireless Coverage,” IEEE Communications Letters, Vol. 20, No. 8, pp. 1647-1650, 2016
[7] R. I.Bor-Yaliniz, A. El-Keyi, and H. Yanikomeroglu, “Efficient 3-D Placement of an Aerial Base Station in Next Generation Cellular Networks,” inProceedings of 2016 IEEE International Conference on Communications (ICC), pp. 1-5, IEEE, 2016
[8] Y. Zeng, R. Zhang,T. J. Lim, “Throughput Maximization for UAV-Enabled Mobile Relaying Systems,” IEEE Transactions on Communications, Vol. 64, No. 12, pp. 4983-4996, 2016
[9] Y. Zeng and R. Zhang, “Energy-Efficient UAV Communication with Trajectory Optimization,” IEEE Transactions on Wireless Communications, Vol. 16, No. 6, pp. 3747-3760, 2017
[10] J. Lyu, Y. Zeng,R. Zhang, “Cyclical Multiple Access in UAV-Aided Communications: A Throughput-Delay Tradeoff,” IEEE Wireless Communications Letters, Vol. 5, No. 6, pp. 600-603, 2016
[11] Z. Xue, J. Wang, G. Ding, H. B. Zhou,Q. H. Wu, “Maximization of Data Dissemination in UAV-Supported Internet of Things,” IEEE Wireless Communications Letters, Vol. 8, No. 1, pp. 185-188, 2019
[12] Q. Wu, Y. Zeng,R. Zhang, “Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks,” IEEE Transactions on Wireless Communications, Vol. 17, No. 3, pp. 2109-2121, 2018
[13] Z. Xue, J. Wang, G. Ding, H. B. Zhou,Q. H. Wu, “Cooperative Data Dissemination in Air-Ground Integrated Networks,” IEEE Wireless Communications Letters, Vol. 8, No. 1, pp. 209-212, 2019
[14] Y. Xu and W. Yin, “A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion,” SIAM Journal on Imaging Sciences, Vol. 6, No. 3, pp. 1758-1789, 2013
[15] S. Boyd and L. Vandenberghe, “Convex Optimization,” Cambridge University Press, Cambridge, U.K, 2004
[16] P. Jain and P.Kar, “Non-Convex Optimization for Machine Learning,” Foundations and Trends® in Machine Learning, Vol. 10, No. 3-4, pp. 142-336, 2017