Generating correlated Nakagami fading signals with arbitrary correlation and fading parameters
Zhefeng Song, Keli Zhang, Yong Liang Guan
Abstract
Zhefeng Song, Keli Zhang, Yong Liang Guan
Abstract
Nakagami's (1960) fading model is widely adopted for analyzing wireless communication systems and diversity combining techniques, hence the ability to generate Nakagami fading signals with arbitrary parameters is important for system design and simulations. In the literature, there are only algorithms for generating correlated Nakagami branches with the same fading parameter. We adopt a novel approach to generate Nakagami fading signals with arbitrary fading parameters and any correlation structure. The correlated Nakagami fading variables are generated from the corresponding uncorrelated gamma random variables (RVs). To achieve this, we propose a new decomposition method, and introduce Sim's (1992)method as a complementary approach, to generate correlated gamma RVs. The former is an approximate approach but can deal with any general correlation structures efficiently, while the latter is exact but has some constraints.
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Nakagami's (1960) fading model is widely adopted for analyzing wireless communication systems and diversity combining techniques, hence the ability to generate Nakagami fading signals with arbitrary parameters is important for system design and simulations. In the literature, there are only algorithms for generating correlated Nakagami branches with the same fading parameter. We adopt a novel approach to generate Nakagami fading signals with arbitrary fading parameters and any correlation structure. The correlated Nakagami fading variables are generated from the corresponding uncorrelated gamma random variables (RVs). To achieve this, we propose a new decomposition method, and introduce Sim's (1992)method as a complementary approach, to generate correlated gamma RVs. The former is an approximate approach but can deal with any general correlation structures efficiently, while the latter is exact but has some constraints.
Key concepts: Fading, Nakagami distribution, Fading distribution, Algorithm, Diversity scheme, Mathematics, Computer science, Random variable