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2008•Indian Journal of Pure & Applied PhysicsOpen access

Gaussian minimum shift keying systems with additive white Gaussian noise

Aashish Saraf, Mayank Tiwari

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Abstract

In this paper, the basic properties of an I-Q Gaussian minimum shift keying (GMSK) with additive white Gaussian noise have been investigated. The probability of error for non-fading and fading channels of communication has been analyzed and discussed. The hardware realization is simple and straight forward like minimum shift keying (MSK) system. Some analytical results have been achieved and compared with machine computed GMSK results of others. The modular circuits are available for VLSI design. Thus, the system developed is suitable for VLSI design of GMSK.

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What this paper is about

In this paper, the basic properties of an I-Q Gaussian minimum shift keying (GMSK) with additive white Gaussian noise have been investigated. The probability of error for non-fading and fading channels of communication has been analyzed and discussed. The hardware realization is simple and straight forward like minimum shift keying (MSK) system. Some analytical results have been achieved and compared with machine computed GMSK results of others. The modular circuits are available for VLSI design. Thus, the system developed is suitable for VLSI design of GMSK.

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Available abstract

In this paper, the basic properties of an I-Q Gaussian minimum shift keying (GMSK) with additive white Gaussian noise have been investigated. The probability of error for non-fading and fading channels of communication has been analyzed and discussed. The hardware realization is simple and straight forward like minimum shift keying (MSK) system. Some analytical results have been achieved and compared with machine computed GMSK results of others. The modular circuits are available for VLSI design. Thus, the system developed is suitable for VLSI design of GMSK.

Key concepts: Minimum-shift keying, Additive white Gaussian noise, Realization (probability), Very-large-scale integration, White noise, Gaussian, Computer science, Fading

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