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Orthogonal time frequency selective (OTFS) is a two-dimensional modulation technique that encodes data in the delay-Doppler domain, offering robust communication in dynamic environments. However, the high peak-to-average power ratio (PAPR) in OTFS waveforms can degrade the performance of power amplifiers (PA) in the system. To address this, the proposed work introduces a partial transmission sequence (PTS) method to effectively reduce PAPR while preserving system throughput. The study evaluates the PTS technique’s performance in terms of key metrics, including bit error rate (BER) and power spectral density (PSD), using MATLAB 2016 for simulation. Results demonstrate that the proposed PTS method significantly outperforms traditional approaches, achieving a PAPR reduction of 1–3.8 dB and reducing power consumption by up to 30 %. These improvements highlight the potential of the PTS method for enhancing the efficiency and reliability of OTFS systems, making it a promising solution for high-performance wireless and optical communication networks. The findings underline the effectiveness of integrating PTS in OTFS to address PAPR challenges while ensuring minimal impact on system performance, paving the way for its application in next-generation communication technologies.

Additive manufacturing (AM) offers customization of the microstructures and mechanical properties of fabricated components according to the material selected and process parameters applied. Selective laser melting (SLM) is a commonly-used technique for processing high strength aluminum alloys. The selection of SLM process parameters could control the microstructure of parts and their mechanical properties. However, the process parameters limit and defects obtained inside the as-built parts present obstacles to customized part production. This study investigates the influence of SLM process parameters on the quality of as-built Al6061 and AlSi10Mg parts according to the mutual connection between the microstructure characteristics and mechanical properties. The microstructure of both materials was characterized for different parts processed over a wide range of SLM process parameters. The optimized SLM parameters were investigated to eliminate internal microstructure defects. The behavior of the mechanical properties of parts was presented through regression models generated from the design of experiment (DOE) analysis for the results of hardness, ultimate tensile strength, and yield strength. A comparison between the results obtained and those reported in the literature is presented to illustrate the influence of process parameters, build environment, and powder characteristics on the quality of parts produced. The results obtained from this study could help to customize the part’s quality by satisfying their design requirements in addition to reducing as-built defects which, in turn, would reduce the amount of the post-processing needed.

Additive manufacturing (AM) of high-strength Al alloys promises to enhance the performance of critical components related to various aerospace and automotive applications. The key advantage of AM is its ability to generate lightweight, robust, and complex shapes. However, the characteristics of the as-built parts may represent an obstacle to the satisfaction of the parts’ quality requirements. The current study investigates the influence of selective laser melting (SLM) process parameters on the quality of parts fabricated from different Al alloys. A design of experiment (DOE) was used to analyze relative density, porosity, surface roughness, and dimensional accuracy according to the interaction effect between the SLM process parameters. The results show a range of energy densities and SLM process parameters for AlSi10Mg and Al6061 alloys needed to achieve “optimum” values for each performance characteristic. A process map was developed for each material by combining the optimized range of SLM process parameters for each characteristic to ensure good quality of the as-built parts. This study is also aimed at reducing the amount of post-processing needed according to the optimal processing window detected.

Orthogonal Frequency Division Multiplexing (OFDM) is considered as a strong candidate for future wireless communication because it is marked by its higher frequency multiplicity and greater immunity to multipath fading. However, the main drawback of OFDM is its high amplitude fluctuations measured by peak-to-average power ratio (PAPR), which leads to power inefficiency and requires expensive high power amplifier (HPA) with very good linearity. In this paper, we propose selected mapping (SLM) with predistortion technique to decrease the nonlinear distortion and to improve the power efficiency of the nonlinear HPA. In the proposed method SLM reduces the PAPR and improves the power efficiency, the predistorter improves the bit error rate (BER) performance of the system. The PAPR reduction is possible with SLM when compared with original OFDM. After reducing the PAPR with SLM the data goes into the HPA with and without predistorter. The BER performance curves of SLM method with or without predistorter shows that, predistorter operates more effectively in SLM method than original OFDM system. At 4 dB IBO (input backoff) the conventional method with predistorter achieves 1.8 dB SNR gain than conventional method without a predistorter and at 6 dB IBO the BER performance is towards the ideal linear amplifier. The proposed system will be evaluated for OFDM system in the presence of a nonlinear power amplifier.

The integration of Optical Orthogonal Frequency Division Multiplexing (OFDM) with the 5G radio waveforms has lately been attracting special attention toward its possible Visible Light Communication (VLC) systems. On the other hand, however, a key challenge in the Optical OFDM is the presence of very high PAPR, degrading the overall system performance by introducing nonlinear distortions in the optical transmitter. In the present paper, different kinds of PAPR reduction algorithms specifically developed for Optical OFDM in VLC systems are developed and investigated. Analyze techniques like clipping, selective mapping (SLM), partial transmit sequence (PTS), and companding for their PAPR reduction efficiency along with the preservation of spectral efficiency and signal integrity. Based on the above aspects, various performance metrics, such as BER, computational complexity, and SNR, have been considered in order to understand each technique’s trade-off. It can be clearly seen that the hybrid and adaptive approaches achieve greater PAPR reduction without much loss of performance and are thus appropriate for future generation optical communication systems. This analysis underlines the use of optimized PAPR reduction algorithms to achieve robust and efficient systems for 5G VLC applications.

Internet of things (IoT) and machine-to-machine (M2M) communication are characterized by short periods and bursts. Traditional orthogonal frequency division multiplexing (OFDM) has not meet the demand for such traffic, while IoT and M2M communication will play an important role in the next fifth generation (5G) communication, so it is particularly urgent to study the small packet and low-latency wireless transmission technologies that satisfy IoT and M2M communication. Universal filter multi-carrier (UFMC) is a new kind of filtered wireless transmission mechanism that meets this requirement, but it faces a higher peak-to-average power ratio (PAPR) than OFDM, which affects the energy efficiency of UFMC. Based on the PAPR performance evaluation of several multi-carrier transmission technologies, a universal filtered multi-carrier based on selective mapping (SLM-UFMC) system is proposed, and the relationship between the number of candidate sub-bands and the performance or between the number of carriers and the performance is carried out. The simulation results show that SLM-UFMC can effectively reduce the PAPR of UFMC system, and the PAPR performance is improved by 1.8 dB comparing with the traditional UFMC. It also further indicates that SLM-UFMC is more suitable for IoT and M2M communication in 5G communication. 物联网(internet of things, IoT)和机器对机器(machine-to-machine, M2M)通信的特点是周期短且突发，传统的正交频分复用技术(orthogonal frequency division multiplexing, OFDM)已经不能适应这种流量的需求，而IoT和M2M通信在未来第五代(fifth generation, 5G)通信中又将占据重要的地位，因此研究满足IoT和M2M通信的小包低时延无线传输技术显得尤为迫切。通用滤波多载波技术(universal filtered multi-carrier, UFMC)正是满足这种需求的一种新型滤波无线传输机制，但是它面临着比OFDM更高峰均功率比(peak-to-average power ratio, PAPR)的问题，这影响了UFMC的能效效率。在对几种多载波传输技术PAPR性能评估的基础上，提出了一种基于选择映射的通用滤波多载波系统(universal filtered multi-carrier based on selective mapping, SLM-UFMC)，并对候选子带个数和载波数与性能之间的关系进行了探究。仿真结果表明：SLM-UFMC能够有效地降低UFMC系统的PAPR，相对于传统UFMC，PAPR性能提高多达1.8 dB。这也进一步表明SLM-UFMC更加适合于5G通信中的IoT和M2M通信。

The aim of this review is to analyze and to summarize the state of the art of the processing of aluminum alloys, and in particular of the AlSi10Mg alloy, obtained by means of the Additive Manufacturing (AM) technique known as Selective Laser Melting (SLM). This process is gaining interest worldwide, thanks to the possibility of obtaining a freeform fabrication coupled with high mechanical properties related to a very fine microstructure. However, SLM is very complex, from a physical point of view, due to the interaction between a concentrated laser source and metallic powders, and to the extremely rapid melting and the subsequent fast solidification. The effects of the main process variables on the properties of the final parts are analyzed in this review: from the starting powder properties, such as shape and powder size distribution, to the main process parameters, such as laser power and speed, layer thickness, and scanning strategy. Furthermore, a detailed overview on the microstructure of the AlSi10Mg material, with the related tensile and fatigue properties of the final SLM parts, in some cases after different heat treatments, is presented.

Refractory high-entropy alloys (HEAs) have excellent mechanical properties, which could make them the substitutes of some superalloys. However, the high melting point of refractory HEAs leads to processing problems when using traditional processing techniques. In this study, a single BCC solid solution of NbMoTaW alloy was formed by selective laser melting (SLM) with a linear energy density of up to 2.83 J/mm. The composition distribution was analyzed, and the element with a lower melting point and lower density showed a negative deviation (no more than 5%) of the molar ratio in the formed alloy. The HEA shows an excellent microstructure, microhardness, and corrosion resistance performance compared with traditional superalloys, making it a new substitute metal with great application prospects in aerospace and energy fields.

As a technology of additive manufacturing (AM), selective laser melting (SLM) is widely used in metal printing, such as super-alloys, stainless steel. Also, the SLM is considered the most potential metal additive manufacturing technology. It is difficult to build a process-performance relationship using traditional physical model, since SLM process is multi parameter and multi-scale. Also, the experimental method takes a long time and is expensive, which requires proposal of a new accurate analytical model and simulation method. The uniqueness of this review includes discussions on the model and simulation model based on physical theory and data driven. The analytical model based on physical model in SLM is discussed. In order to solve the nonlinear equation in the physical model, the numerical method that used FEM software is summarized. With the development of machine learning method, the machine learning based on data driven is used in SLM process optimization. The discussion and future trends of three methods are proposed in order to solve the gap between laboratory and industry.