ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2020
DOI: 10.1109/icassp40776.2020.9053923
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Near Capacity RCQD Constellations for PAPR Reduction of OFDM Systems

Abstract: We investigate an optimized blind SeLected Mapping (SLM) algorithm to reduce the Peak-to-Average Power Ratio (PAPR) for Orthogonal Frequency Division Multiplexing (OFDM) systems with Signal Space Diversity (SSD). Several phase sequences based on two Rotated and Cyclically Q-Delayed (RCQD) constellations are used at the transmitter to considerably reduce the PAPR. The pair of RCQD constellations is selected so as to achieve the highest average mutual information for both the Coded Modulation (CM) and the Bit-In… Show more

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Cited by 9 publications
(7 citation statements)
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“…At the transmitter side, note that no multiplication by any phase sequence is required for our proposal; this reduces the complexity burden by 4N (D − 1) RMs and 2N (D − 1) RSs compared to the SLM algorithm in [5], [6]. Furthermore, at the receiver side, the total computational complexity of the proposed MMSE-based blind detector (see equations ( 15)-( 17)) is 38N D RMs, 15DN RSs, (2log 2 M − 2)DN RCs, and DN RIs.…”
Section: Complexity Analysismentioning
confidence: 99%
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“…At the transmitter side, note that no multiplication by any phase sequence is required for our proposal; this reduces the complexity burden by 4N (D − 1) RMs and 2N (D − 1) RSs compared to the SLM algorithm in [5], [6]. Furthermore, at the receiver side, the total computational complexity of the proposed MMSE-based blind detector (see equations ( 15)-( 17)) is 38N D RMs, 15DN RSs, (2log 2 M − 2)DN RCs, and DN RIs.…”
Section: Complexity Analysismentioning
confidence: 99%
“…Besides, when we jointly use the TR and the proposed algorithms with D = 8, we obtain similar PAPR reduction performance to the optimal PTS with much lower computational complexity and higher spectral efficiency. Finally, when compared to the blind SLM method [5], [6], both methods have approximately the same PAPR reduction performance; however, our proposal for UP-RCQD constellations reduces considerably the computational complexity both at the transmitter and the receiver sides; in particular, in addition to the computational complexity reduction obtained for the LLR computation thanks to the use of the UP-RCQD constellation [9], the computational complexity is reduced, with the chosen system parameters, by 97% (see Table I and Fig. 6).…”
Section: Rs Rc M1mentioning
confidence: 99%
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“…The measured EVM rms measurements using either the average constellation power or the peak constellation power method as Calculated using the following equations [16,17].…”
Section: Error Vector Magnitude (Evm)mentioning
confidence: 99%