上海交通大学学报(英文版) ›› 2015, Vol. 20 ›› Issue (5): 540-547.doi: 10.1007/s12204-015-1661-4

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A Novel Interference Modeling Scheme in Cognitive Networks

LI Jian1,2* (李 剑), LI Sheng-hong1 (李生红)   

  1. (1. Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai 200240, China; 2. The Third Research Institute of Ministry of Public Security of P.R.C, Shanghai 200031, China)
  • 发布日期:2015-10-29
  • 通讯作者: LI Jian (李 剑) E-mail:lijian@163.com

A Novel Interference Modeling Scheme in Cognitive Networks

LI Jian1,2* (李 剑), LI Sheng-hong1 (李生红)   

  1. (1. Department of Electronic Engineering, Shanghai Jiaotong University, Shanghai 200240, China; 2. The Third Research Institute of Ministry of Public Security of P.R.C, Shanghai 200031, China)
  • Published:2015-10-29
  • Contact: LI Jian (李 剑) E-mail:lijian@163.com

摘要: In this paper, we propose a mathematical model of aggregate co-channel interference over Rayleigh fading in cognitive networks. Unlike the statistical models in the literature that aim at finding the bound or approximation of the interference, the proposed model gives an accurate expression of probability density function (PDF), cumulative distribution function (CDF) and mean and variance of the interference, which takes into account a number of factors, such as spectrum sensing scheme, and spatial distribution of the secondary users (SUs). In particular, we focus on a more general spatial structure where there are two roles of primary users (PUs) and the interfering SUs distributed in the two-dimensional space. The framework developed in this paper is easy to be applied in power control, error evaluation and other applications.

关键词: interference, modeling, cognitive networks

Abstract: In this paper, we propose a mathematical model of aggregate co-channel interference over Rayleigh fading in cognitive networks. Unlike the statistical models in the literature that aim at finding the bound or approximation of the interference, the proposed model gives an accurate expression of probability density function (PDF), cumulative distribution function (CDF) and mean and variance of the interference, which takes into account a number of factors, such as spectrum sensing scheme, and spatial distribution of the secondary users (SUs). In particular, we focus on a more general spatial structure where there are two roles of primary users (PUs) and the interfering SUs distributed in the two-dimensional space. The framework developed in this paper is easy to be applied in power control, error evaluation and other applications.

Key words: interference, modeling, cognitive networks

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