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This paper addresses the problem of decoding in large-scale multiple-input–multiple-output (MIMO) systems. In this case, the optimal maximum-likelihood (ML) detector becomes impractical due to an exponential increase in the complexity with the signal and the constellation dimensions. This paper introduces an iterative decoding strategy with a tolerable complexity order. We consider a MIMO system with...
Selected mapping (SLM) is considered as a practical probabilistic PAPR reduction method for OFDM systems. A problem of this technique is its high computational complexity due to multiple inverse Fourier transform. We suggest a decimation in frequency IFFT scheme together with an interleaver-butterfly ensemble to generate multiple candidates. Orthogonality in the frequency domain is kept and better...
We consider the multiple candidate OFDM systems as a class of probabilistic method to reduce the peak to average power ratio (PAPR) of OFDM symbols. The candidate having the lowest PAPR is selected for transmission. For that, many IFFTs have to be processed to measure the PAPR of each candidate, which can be too complex for handheld devices. We propose the concept of phase uncertainty as an alternative...
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