Resource allocation in cellular systems for applications with random parameters

In this paper, we conduct a study to optimize resource allocation for adaptive real-time and delay-tolerant applications in cellular systems. To represent the user applications via several devices and equipment, sigmoidal-like and logarithmic utility functions are used. A fairness proportional utility functions policy approach is used to allocate the resources among the user equipment (UE)s in a utility percentage form in order to ensure a minimum level of customer satisfaction for all the subscribers. Meanwhile, the priority of resources allocation is given to the real-time applications. We measure the effect of the stochastic variations of the adaptive real-time applications on the optimal rate allocation process and compare the results of the deterministic and stochastic systems. Our work is distinct from the other resource allocation optimization works in that we use the bisection method besides convex optimization techniques to optimally allocate rates, and we present the adaptive real-time applications in a stochastic form. We use Microsoft Visual Basic for Applications with Arena Simulation Software interface to simulate the optimization problem. Finally, we present our optimization algorithm results.

[1]  Ahmed Abdel-Hadi,et al.  A utility proportional fairness approach for resource allocation in 4G-LTE , 2014, 2014 International Conference on Computing, Networking and Communications (ICNC).

[2]  Ahmed Abdel-Hadi,et al.  An optimal resource allocation with joint carrier aggregation in 4G-LTE , 2015, 2015 International Conference on Computing, Networking and Communications (ICNC).

[3]  Ahmed Abdel-Hadi,et al.  Multi-application resource allocation with users discrimination in cellular networks , 2014, 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC).

[4]  Ahmed Abdel-Hadi,et al.  Context-Aware Resource Allocation in Cellular Networks , 2014, ArXiv.

[5]  Rebecca Lynne Kurrle,et al.  Resource Allocation for Smart Phones in 4G LTE-Advanced Carrier Aggregation , 2012 .

[6]  S. Shenker.  Fundamental Design Issues for the Future Internet , 1995 .

[7]  Ness B. Shroff,et al.  Downlink power allocation for multi-class wireless systems , 2005, IEEE/ACM Transactions on Networking.

[8]  Ahmed Abdel-Hadi,et al.  A utility proportional fairness radio resource block allocation in cellular networks , 2015, 2015 International Conference on Computing, Networking and Communications (ICNC).

[9]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[10]  Steven H. Low,et al.  Optimization flow control—I: basic algorithm and convergence , 1999, TNET.

[11]  Tobias Harks,et al.  Utility Proportional Fair Bandwidth Allocation: An Optimization Oriented Approach , 2005, QoS-IP.

[12]  A. Robinson,et al.  The influence of scene content on bit-rate variations in ATM video , 1992 .

[13]  Kin K. Leung,et al.  Utility-proportional fairness in wireless networks , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[14]  Kin K. Leung,et al.  A new distributed optimization framework for hybrid ad-hoc networks , 2011, 2011 IEEE GLOBECOM Workshops (GC Wkshps).

[15]  Mohammed Ghanbari,et al.  Components of bit-rate variation in videoconference signals , 1989 .

[16]  Gustavo de Veciana,et al.  Rate Adaptation and Admission Control for Video Transmission With Subjective Quality Constraints , 2013, IEEE Journal of Selected Topics in Signal Processing.