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On the Selection of the Best MSR PAPR Reduction Technique for OFDM Based Systems

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Internet of Things—Applications and Future

Abstract

Orthogonal Frequency Division Multiplexing (OFDM) is used in the physical layer of IoT–based networks, due to its ability to mitigate frequency selectivity. However, OFDM suffers from high Peak-to-Average Power Ratio (PAPR) problem, which reduces the Power Amplifier (PA) efficiency or otherwise degrade BER and increases out-of-band (OOB) radiation. This means IoT networks will consume more power. However, IoT devices are expected to have limited power sources. Many PAPR reduction techniques were introduced in the literature. Among them, Multiple Signal Representation (MSR) techniques have high PAPR reduction gain and a small number of Side Information (SI) bits. However, they require high computational complexity to provide high PAPR reduction gain. In this paper, three MSR techniques namely Partial Transmit Sequence (PTS), Selective Mapping (SLM), and interleaving are compared in terms of PAPR reduction gain and computational complexity. Results showed that PTS is the best among others. It provides PAPR reduction performance similar to SLM and better than interleaving with less computational complexity.

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Correspondence to Mohamed Mounir .

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Mounir, M., El_Mashade, M.B., Gaba, G.S. (2020). On the Selection of the Best MSR PAPR Reduction Technique for OFDM Based Systems. In: Ghalwash, A., El Khameesy, N., Magdi, D., Joshi, A. (eds) Internet of Things—Applications and Future. Lecture Notes in Networks and Systems, vol 114. Springer, Singapore. https://doi.org/10.1007/978-981-15-3075-3_11

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