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A methodology for information and capacity analysis of broadband wireless access systems

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  • Igor Lazov

    (Ss. Cyril and Methodius University)

Abstract

Using a part of a general methodology for population analysis, developed recently in Lazov and Lazov [1], and relying on the fundamental concepts of system information i and system entropy $$S=E\left( i \right) $$ S = E i , this paper promotes a methodology for information and capacity analysis of broadband wireless access (BWA) systems. A BWA system consists of a base station (BS) and a group of M users in its coverage area, with N simultaneously active users, $$0\le N\le M$$ 0 ≤ N ≤ M , working in point-to-multipoint mode. As in [1], we model this system as family of birth-death processes (BDPs), with size $$M+1$$ M + 1 , in equilibrium, indexed by the system utilization parameter $$\rho $$ ρ , ratio of its primary birth and death rates, $$\rho =\lambda /\mu $$ ρ = λ / μ . We evaluate the BWA system information and entropy, and full system capacity, and then, assuming the same Gaussian distribution for the arrival traffic at BS from any user, system capacity (as a function of the system information) and its mean value, and mean normalized square deviation of the system capacity from its linear part. We compare the information of empty $$\left( {N=0} \right) $$ N = 0 and full $$\left( {N=M} \right) $$ N = M system with system entropy, and further, system mean capacity with full system capacity, as functions of parameter $$\rho $$ ρ . The developed methodology is illustrated on families of BDPs with truncated geometrical, truncated Poisson and Binomial distributions as their equilibrium ones, which model the information linear, Erlang loss and Binomial BWA systems, respectively.

Suggested Citation

  • Igor Lazov, 2016. "A methodology for information and capacity analysis of broadband wireless access systems," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 63(2), pages 127-139, October.
  • Handle: RePEc:spr:telsys:v:63:y:2016:i:2:d:10.1007_s11235-015-0104-8
    DOI: 10.1007/s11235-015-0104-8
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    References listed on IDEAS

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    1. Touchette, Hugo & Lloyd, Seth, 2004. "Information-theoretic approach to the study of control systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(1), pages 140-172.
    2. Kaniadakis, G., 2001. "Non-linear kinetics underlying generalized statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 296(3), pages 405-425.
    3. B. Sharma & I. Taneja, 1975. "Entropy of type (α, β) and other generalized measures in information theory," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(1), pages 205-215, December.
    4. Lazov, Petar & Lazov, Igor, 2014. "A general methodology for population analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 557-594.
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    Cited by:

    1. Igor Lazov, 2019. "A Methodology for Revenue Analysis of Parking Lots," Networks and Spatial Economics, Springer, vol. 19(1), pages 177-198, March.
    2. Lazov, Igor, 2017. "Profit management of car rental companies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 307-314.
    3. Yipei Zhang & Jiale Liu & Xiaoyan Xie & Chenshuo Wang & Libiao Bai, 2023. "Modeling of Project Portfolio Risk Evolution and Response under the Influence of Interactions," Mathematics, MDPI, vol. 11(19), pages 1-20, September.

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