Error probability analysis of Joint Signal Detection with Base Station sleeping and cooperation

Amplitude detection (AD) is a low-complexity nonlinear scheme for information retrieval, as it only considers the envelop of the received signal. This makes it ideal in applications with low-cost low-power devices such as the Internet of Things. We consider a basic point-to-point (P2P) setup and develop a unified analytical framework for the asymptotic symbol error rate (SER) performance of the maximum likelihood (ML) decoder with M -ary amplitude shift keying. The developed framework is general and can be applied for a large class of fading channels. The SER can be characterized by two parameters: the diversity order and the coding gain at sufficiently high signal-to-noise regime. We derive closed form expressions for the exact diversity order along with a lower and upper bound on the coding gain. We show that, the diversity order is equal to m for Nakagami-m fading, whereas for the other considered models, it is equal to one. We also prove that among all possible binary modulations with equal power, the modulation with one symbol equal to zero (i.e., on-off keying) achieves the minimum asymptotic SER. The mathematical framework developed for the P2P setup is extended for cooperative relay networks. Specifically, we consider a basic amplify-and-forward (AF) three-node relay topology that employs AD at both the relay and the destination. We analytically derive the ML decoder and study asymptotic bounds on the SER by showing that the proposed AF-AD relay setup can be transformed into an equivalent P2P-AD with respect to the ML decoder.

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Communication Systems With Amplitude Detection: An Asymptotic Approach

Agarwal

Psomas

Krikidis

2022

IEEE Internet Things J.

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Error probability analysis of Joint Signal Detection with Base Station sleeping and cooperation

Cited by 1 publication

References 22 publications

Communication Systems With Amplitude Detection: An Asymptotic Approach

Communication Systems With Amplitude Detection: An Asymptotic Approach

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