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A New Fairness Index and Novel Approach for QoS-Aware Resource Allocation in LTE Networks Based on Utility Functions | ||
AUT Journal of Electrical Engineering | ||
مقاله 3، دوره 47، شماره 2، اسفند 2015، صفحه 19-25 اصل مقاله (2.14 M) | ||
نوع مقاله: Research Article | ||
شناسه دیجیتال (DOI): 10.22060/eej.2015.579 | ||
نویسندگان | ||
M. J. Rezaei1؛ M. F. Sabahi* 2؛ K. Shahtalebi2؛ R. Mahin Zaeem3؛ R. Sadeghi4 | ||
1MSc. Student, Electrical Engineering Department, University of Isfahan, Isfahan, Iran. | ||
2Assistant Professor, Electrical Engineering Department, University of Isfahan, Isfahan, Iran. | ||
3MSc. Student, Electrical Engineering Department, University of Isfahan, Isfahan, Iran | ||
4Assistant Professor, Department of Electrical Engineering, Dolatabad Branch, Islamic Azad University, Isfahan, Iran | ||
چکیده | ||
Resource allocation techniques have recently appeared as a widely recognized feature in LTE networks. Most of existing approaches in resource allocation focus on maximizing network’s utility functions. The great potential of utility function in improving resource allocation and enhancing fairness and mean opinion score (MOS) indexes has attracted large efforts over the last few years. In this paper, a new fairness index is proposed to measure resource allocation performance for real-time/delay-tolerant applications. This index can suggest a new approach for resource allocation. There are several methods in resource allocation of cellular networks which employ fairness index for performance evaluation. Here, we focus on utility-function-based resources allocation and related algorithms. According to the suggested method, the base station (BS) allocates resources based on different services requirements. Appropriate utility function for each application is defined, and the requested quality-of-services (QoS) are satisfied through solving the corresponding optimization problem. The new well-defined fairness index shows that the proposed method has a good performance for different real-time/delay-tolerant applications. Additionally, numerical results show that this approach is able to improve other important indicators such as throughput and MOS as well. | ||
کلیدواژهها | ||
Resource allocation؛ Fairness Index؛ MOS؛ Throughput؛ Utility Function | ||
عنوان مقاله [English] | ||
A New Fairness Index and Novel Approach for QoS-Aware Resource Allocation in LTE Networks Based on Utility Functions | ||
نویسندگان [English] | ||
M. J. Rezaei1؛ M. F. Sabahi2؛ K. Shahtalebi2؛ R. Mahin Zaeem3؛ R. Sadeghi4 | ||
1MSc. Student, Electrical Engineering Department, University of Isfahan, Isfahan, Iran. | ||
2Assistant Professor, Electrical Engineering Department, University of Isfahan, Isfahan, Iran. | ||
3MSc. Student, Electrical Engineering Department, University of Isfahan, Isfahan, Iran | ||
4Assistant Professor, Department of Electrical Engineering, Dolatabad Branch, Islamic Azad University, Isfahan, Iran | ||
چکیده [English] | ||
Resource allocation techniques have recently appeared as a widely recognized feature in LTE networks. Most of existing approaches in resource allocation focus on maximizing network’s utility functions. The great potential of utility function in improving resource allocation and enhancing fairness and mean opinion score (MOS) indexes has attracted large efforts over the last few years. In this paper, a new fairness index is proposed to measure resource allocation performance for real-time/delay-tolerant applications. This index can suggest a new approach for resource allocation. There are several methods in resource allocation of cellular networks which employ fairness index for performance evaluation. Here, we focus on utility-function-based resources allocation and related algorithms. According to the suggested method, the base station (BS) allocates resources based on different services requirements. Appropriate utility function for each application is defined, and the requested quality-of-services (QoS) are satisfied through solving the corresponding optimization problem. The new well-defined fairness index shows that the proposed method has a good performance for different real-time/delay-tolerant applications. Additionally, numerical results show that this approach is able to improve other important indicators such as throughput and MOS as well. | ||
کلیدواژهها [English] | ||
Resource allocation, Fairness Index, MOS, Throughput, Utility Function | ||
مراجع | ||
[1] Araniti, Giuseppe, et al. “Evaluating the Performanceof Multicast Resource Allocation Policies over LTE Systems.” arXiv preprint arXiv, pp. 1-6, June 2015. [2] Y.L Lee, et al. “Recent advances in radio resourcemanagement for heterogeneous LTE/LTE-A networks.” Communications Surveys & Tutorials,vol. 16, no 4 ,pp. 2142-2180, June 2014. [3] E.B. Rodrigues. “Adaptive radio resourcemanagement for OFDMA-based macro-andfemtocell networks.” Diss. Universitat Politècnica deCatalunya, 2011. [4] G. Gómez, et al. “Towards a qoe-driven resourcecontrol in lte and lte-a networks.” Journal of Computer Networks and Communications, 2013. [5] P. Xue, et al. “Radio resource management withproportional rate constraint in the heterogeneous networks.” Wireless Communications, IEEE Trans.,vol. 11, no. 3, pp. 1066-1075, Mar. 2012. [6] C. Huang, et al. “Radio resource management ofheterogeneous services in mobile WiMAX systems [Radio Resource Management and ProtocolEngineering for IEEE 802.16].” WirelessCommunications, IEEE Trans., vol. 14, no. 1, pp. 20-26, Feb. 2007. [7] P. Ameigeiras, et al. “QoE oriented cross-layerdesign of a resource allocation algorithm in beyond 3G systems.” Computer Communications, vol. 33, no.5, pp. 571-582, 2010. [8] X. Pei, et al. “Radio-resource management andaccess-control mechanism based on a novel economic model in heterogeneous wirelessnetworks.” vehicular technology, IEEE Trans., vol.59, no. 6, pp. 3047-3056, Jul. 2010. [9] M.J. Neely, M. Eytan, and L. Chih-Ping. “Fairnessand optimal stochastic control for heterogeneous networks.” Networking, IEEE/ACM Trans., vol. 16,no. 2, pp. 396-409, Apr. 2008. [10] J.Jin, W. Wei-Hua, and P. Marimuthu. “Utility max–min fair resource allocation for communication networks with multipath routing.” ComputerCommunications, vol. 32, no. 17, pp. 1802-1809, 2009. [11] M. Ghorbanzadeh, A. Abdelhadi, and Ch. Clancy.“A utility proportional fairness radio resource block allocation in cellular networks.” Computing,Networking and Communications (ICNC), 2015International Conference on. IEEE, 2015, pp. 499-504. [12] S. AlQahtani, and M. AlHassany. “Performancemodeling and evaluation of novel scheduling algorithm for LTE networks.” Network computingand applications (NCA), 2013 12th IEEE international symposium on. IEEE, 2013, pp. 101-105. [13] P. Tang, et al. “QoE-based resource allocationalgorithm for multi-applications in downlink LTE systems.” 2014 International Conference onComputer, Communications and Information Technology (CCIT 2014). Atlantis Press, 2014, pp.1011-1016. [14] M. Li, C.Zhenzhong, and T. Yap-Peng. “AMAXMIN resource allocation approach for scalable video delivery over multiuser MIMO-OFDMsystems,” Circuits and Systems (ISCAS), 2011 IEEE International Symposium on. IEEE, May 2011, pp.2645 - 2648. [15] R.K. Jain, D.M.W. Chiu, W.R Hawe. “A quantitative measure of fairness and discrimination for resource allocation,” in shared computer systems. Public, TR-301, Digital Equipment Corp., 26, September 1984. [16] M.J. Fischer, et al. “Distributed FIFO allocation of identical resources using small shared space.” ACM Transactions on Programming Languages and Systems (TOPLAS), vol. 11, no. 1, pp. 90-114, 1989. [17] M. Shreedhar, and G.Varghese. “Efficient fair queuing using deficit round-robin.” Networking, IEEE/ACM Trans., vol. 4, no. 3, pp. 375-385, Jun. 1996. [18] A. Pokhariyal, et al. “HARQ aware frequency domain packet scheduler with different degrees of fairness for the UTRAN long term evolution.” Vehicular Technology Conference, 2007. VTC2007-Spring. IEEE 65th. IEEE, Apr. 2007, pp. 2761-2765. [19] A. Demers, K. Srinivasan, and Sh. Scott. “Analysis and simulation of a fair queueing algorithm.” ACM SIGCOMM Computer Communication Review. vol. 19. no. 4. ACM, 1989. [20] S. Boyd, and V. Lieven. “Convex optimization.” Cambridge university press, 2004. [21] M.A. Freitag, A. Spence. “A Newton-based method for the calculation of the distance to instability”. Linear Algebra and its Applications. vol. 435, no. 12, pp. 3189-3205, 2011. [22] F. Capozzi, G. Piro, L.A. Grieco, G. Boggia and P. Camarda, Downlink Packet Scheduling in LTE Cellular Networks: Key Design Issue and a Survey, IEEE Communications Surveys & Tutorials, Vol. 15, No.2, 2013, pp. 678-700. [23] P. Kela, J. Puttonen, N. Kolehmainen, T. Ristaniemi, T. Henttonen, and M. Moisio, "Dynamic packet scheduling performance in UTRA Long Term Evolution downlink," in Proc. Of International Symposium on Wireless Pervasive Comput, Santorini, Greece, May 2008, pp. 308-313. [24] A. S. Tanenbaum, Modern Operating Systems, 3rd ed. Upper Saddle River, NJ, USA: Prentice Hall Press, 2007. [25] 3GPP, “TS 23.203 v11.7.0: Policy and charging control architecture,” 2012. | ||
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