By Mo Ghorbanzadeh, Ahmed Abdelhadi, Charles Clancy
This e-book offers a mathematical remedy of the radio source allocation of contemporary mobile communications structures in contested environments. It specializes in pleasurable the standard of provider standards of the residing purposes at the person units, which leverage the mobile process, and with realization to raising the clients’ caliber of expertise. The authors additionally handle the congestion of the spectrum by way of permitting sharing with the band incumbents whereas supplying with a quality-of-service-minded source allocation within the community. The content material is of specific curiosity to telecommunications scheduler specialists in undefined, communications functions academia, and graduate scholars whose paramount learn bargains with source allocation and caliber of service.
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Extra resources for Cellular Communications Systems in Congested Environments: Resource Allocation and End-to-End Quality of Service Solutions with MATLAB
In: IEEE international symposium on personal, indoor and mobile radio communications (PIMRC) 102. Shajaiah H, Abdelhadi A, Clancy T (2014) Spectrum sharing between public safety and commercial users in 4g-lte. In: IEEE international conference on computing, networking and communications (ICNC) 103. Lackpour A, Luddy M, Winters J (2011) Overview of interference mitigation techniques between wimax networks and ground based radar. In: Proceedings 20th annual wireless and optical communications conference 104.
IEEE/ACM Trans Netw 56. Demers A, Keshav S, Shenker S (1989) Analysis and simulation of a fair queueing algorithm. SIGCOMM Comput Commun Rev 57. Khawar A, Abdelhadi A, Clancy TC (2014) On the impact of time-varying interferencechannel on the spatial approach of spectrum sharing between S-band radar and communication system. In: Military communications conference (MILCOM) 58. Kelly F, Maulloo A, Tan D (1998) Rate control in communication networks: shadow prices, proportional fairness and stability.
Next, Sect. 2 explains some points regarding various factors that affect resource allocation formulation. 2 Resource Allocation Formulations In the mathematics literature germane to utility functions and resource allocation, a wide variety of formulations have been presented and numerous solutions have been proposed. Amidst various formulations, max-min fairness [33–40] and proportional fairness  have received attention as they can yield in optimal and/or efficient solutions [42–44]. Moreover, the authors in [45–47] define a solution to be either Pareto inefficient, Pareto optimal, or infeasible solutions.