In this paper, we consider reduction of PAPR in OFDM systems with BPSK subcarriers by combining SLM and binary cyclic codes. This combining strategy can be used for both error correction and PAPR reduction. We decompose a binary cyclic code into direct sum of two cyclic subcodes: the correction subcode used for error correction and the scrambling subcode for PAPR reduction. The transmitted OFDM signal is selected that achieves minimum PAPR, from the set of binary cyclic codewords. The received signal can be easily decoded without the need of any side information. Simulations show that the proposed scheme with simplex code as scrambling subcode achieves good PAPR reduction.

This letter proposes a modified PTS technique using binary Reed-Muller (RM) codes for error correction and PAPR control in BPSK OFDM systems. A RM code is divided into the direct sum of a correcting subcode for encoding information bits and a scrambling subcode for encoding PAPR bits. The transmitted signal of the resulting OFDM sequence is selected with minimum PAPR from a number of candidates which are codewords of a coset of the scrambling subcode. We consider the RM codes in natural and cyclic orderings. Numerical results show that RM codes in cyclic ordering achieve better performance in PAPR reduction than RM codes in natural ordering.

In this paper, we propose a peak-to-average power ratio (PAPR) reduction method for an orthogonal frequency division multiplexing (OFDM) system by combining the improved genetic algorithm used the partheno-crossover operator (PCGA) with partial transmit sequence (PTS) scheme, called PCGA-PTS. Recently, the genetic algorithm based PTS scheme (GA-PTS) is a novel PAPR reduction method, which has lower computational load than the PTS technique and is a suboptimal PAPR reduction method. However, how to further improve the PAPR performance of GA-PTS in OFDM systems is still an active research. Therefore, this paper proposes a new PAPR reduction method to improve the PAPR performance of GA-PTS, based on the same computational complexity. Our proposed method uses a two-step crossover operator and a mutation operator to generate the offspring, and then selects the proper candidates from the offspring to be the individuals of new population, where the two-step crossover operator is composed of a crossover operator and a partheno-crossover operator. In simulation results, our proposed method has better PAPR performance than the GA-PTS technique in OFDM systems.

This paper aimed to investigate how to construct a phase-generation mechanism with a systematic structure and without diminishing the peak-to-average power ratio (PAPR) reduction performance of a conventional selective mapping (SLM) technique. The SLM is a prevalent technique for reducing the PAPR and is often applied in orthogonal frequency division multiplexing (OFDM) systems. Despite effectively reducing the PAPR, the SLM generates phase sequences randomly, creating a lack of systematic structure and increased system complexity. Therefore, this paper sets an adaptive threshold value to evaluate the characteristics of input signals. On the basis of the evaluated characteristics, this paper selected the optimal phase-generation mechanism to produce phase sequences. In the proposed method, the phase-generation mechanism was established according to the structure of Reed-Muller codes, thereby achieving a systematic structure that the random generation technique lacks. Compared with the conventional SLM techniques, the proposed method required an additional bit of side information for each transmitted signal but could approximate the PAPR reduction performance of the conventional SLM technique according to the simulation results.

The symptom of tongue deviation is observed in a stroke or transient ischemic attack. Nevertheless, there is much room for the interpretation of the tongue deviation test. The crucial factor is the lack of an effective quantification method of tongue deviation. If we can quantify the features of the tongue deviation and scientifically verify the relationship between the deviation angle and a stroke, the information provided by the tongue will be helpful in recognizing a warning of a stroke. In this study, a quantification method of the tongue deviation angle was proposed for the first time to characterize stroke patients. We captured the tongue images of stroke patients (15 males and 10 females, ranging between 55 and 82 years of age); transient ischemic attack (TIA) patients (16 males and 9 females, ranging between 53 and 79 years of age); and normal subjects (14 males and 11 females, ranging between 52 and 80 years of age) to analyze whether the method is effective. In addition, we used the receiver operating characteristic curve (ROC) for the sensitivity analysis, and determined the threshold value of the tongue deviation angle for the warning sign of a stroke. The means and standard deviations of the tongue deviation angles of the stroke, TIA, and normal groups were: 6.9 ± 3.1, 4.9 ± 2.1 and 1.4 ± 0.8 degrees, respectively. Analyzed by the unpaired Student’s t-test, the p- value between the stroke group and the TIA group was 0.015 (>0.01), indicating no significant difference in the tongue deviation angle. The p- values between the stroke group and the normal group, as well as between the TIA group and the normal group were both less than 0.01. These results show the significant differences in the tongue deviation angle between the patient groups (stroke and TIA patients) and the normal group. These results also imply that the tongue deviation angle can effectively identify the patient group (stroke and TIA patients) and the normal group. With respect to the visual examination, 40% and 32% of stroke patients, 24% and 16% of TIA patients, and 4% and 0% of normal subjects were found to have tongue deviations when physicians “A” and “B” examined them. The variation showed the essentiality of the quantification method in a clinical setting. In the receiver operating characteristic curve (ROC), the Area Under Curve (AUC, = 0.96) indicates good discrimination. The tongue deviation angle more than the optimum threshold value (= 3.2°) predicts a risk of stroke. In summary, we developed an effective quantification method to characterize the tongue deviation angle, and we confirmed the feasibility of recognizing the tongue deviation angle as an early warning sign of an impending stroke.