Partial transmit sequence (PTS) scheme has been well applied to reduce the high peak-toaverage power ratio (PAPR) of the orthogonal frequency division multiplexing (OFDM) signal. However, due to the signal structure differences between the filter bank multicarrier and offset quadrature amplitude modulation (FBMC/OQAM) signal and the OFDM signal, the conventional PTS scheme is not applicable to the FBMC/OQAM signal. Considering the PAPR reduction issue for the FBMC/OQAM signal, this paper proposes a genetic algorithm (GA) based bilayer partial transmit sequence (GA-BPTS) scheme. In order to reduce the computational complexity, the proposed scheme continues to partition each subblock, transforming the single layer structure of the conventional PTS into a bilayer phase factor search structure, and introduces a penalty threshold. Then the suboptimal phase factor vector is obtained by using the GA. Meanwhile, before PAPR reduction processing, aided by the proposed prototype filter which has the better performance of out-of-band attenuation than the PHYDAYS filter, the GA-BPTS scheme can effectively reduce the PAPR of the FBMC/OQAM signal. The simulations have confirmed that the proposed scheme not only provides an excellent PAPR performance but also decreases the computational complexity compared with the conventional PTS scheme. INDEX TERMS Bilayer partial transmit sequence (PTS), filter bank multicarrier and offset quadrature amplitude modulation (FBMC/OQAM), genetic algorithm (GA), peak-to-average power ratio (PAPR) reduction.
The prototype filter design problem is investigated for the filter bank multicarrier (FBMC) system of the fifth generation (5G) physical-layer wireless communications. In order to further suppress the side lobe energy within a certain frequency range, different constraint factors need to be introduced to meet the various side lobe energy suppression demands. In this paper, we formulate a dual-objective optimization problem which minimizes the stopband energy with constrained factors and subjects to the ISI/ICI constraints. Considering the uncertain constrained factors, a suboptimization problem is proposed by constraining the total stopband energy and the side lobe energy of the first segment to minimize the side lobe energy of the second or the third segments. Then, the nested sequential quadratic program-genetic algorithm (NSGA), one of the artificial intelligence (AI) aided algorithms, is introduced to obtain the optimal solution of the dual-objective problem, in which the genetic algorithm (GA) is applied to acquire the optimal constrained factors and the sequential quadratic program (SQP) is applied to acquire the optimal filter coefficients. Numerical results validate that the proposed method can achieve orientated side lobe energy suppression at specified segments for satisfying different side lobe energy suppression requirements with the confirmed algorithm convergence. INDEX TERMS Artificial intelligence (AI), filter bank multicarrier (FBMC), genetic algorithm (GA), oriented side lobe energy suppression, prototype filter design.
Digital metering system, the electronic energy meter analog-to-digital conversion sampling function moved to the electronic instrument transformer, and electronic instrument transformer sampling frequency compared with the electronic energy meter is low, the sampling frequency will be insufficient in the analog-to-digital conversion process Introduce quantization error. In this paper, the measurement error model of electronic instrument transformer based on analog-to-digital conversion sampling principle is established, and the influence of sampling frequency on energy measurement error is quantitatively analyzed. The analysis shows that the accuracy of electronic instrument transformer measurement is related to oversampling rate.
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