Energy consumption is one of the critical challenges in designing wireless sensor network (WSN) since it is typically composed of resource-constrained devices. Many studies have been proposed clustering to deal with energy conservation in WSN. Due to its predominance in coordinating the behaviors of many players, game theory has been considered for improving energy efficiency in WSN. In this paper, we evaluate the performance of cooperative game theoretic clustering (CGC) algorithm which employs cooperative game theory in a form of 3-agent cost sharing game for energy-efficient clustering in WSN. Furthermore, we compared its performance to a well-known traditional clustering method, low-energy adaptive clustering hierarchy (LEACH), in terms of network lifetime and stability, and total residual energy. The simulation results show that CGC has better performance compared to LEACH due to the cooperation among cluster heads in coalition. CGC has higher alive nodes with stability improvement of first node dies (FND) by 65%, and the improvement by 52.4% for half node dies (HND). However, with the increasing of the number of nodes, the performance of LEACH is getting better compared to CGC.
AbstrakOrthogonal Frequency Division Multiplexing (OFDM) merupakan teknik modulasi multicarrier yang banyak diadopsi oleh berbagai teknologi komunikasi nirkabel untuk memenuhi kebutuhan akses broadband yang kian meningkat karena menyediakan transmisi dengan data rate tinggi. Selain itu, OFDM juga tahan terhadap efek multipath fading. Salah satu permasalahan utama pada sistem ini adalah tingginya nilai PAPR yang menyebabkan penggunaan power amplifier menjadi tidak efisien. Sebagai solusi permasalahan ini, teknik Selected Mapping (SLM) dan Partial Transmit Sequence (PTS) digunakan untuk mereduksi nilai PAPR. Kedua teknik ini dipilih karena efisien dalam mereduksi nilai PAPR. Dari hasil simulasi yang dilakukan terhadap 1000 simbol OFDM, kedua teknik ini memberikan reduksi PAPR yang semakin besar untuk jumlah subblok yang semakin banyak. Selanjutnya, kinerja kedua teknik ini dibandingkan. Dengan jumlah subblok yang sama, SLM memiliki performansi yang lebih baik dalam mereduksi PAPR dibandingkan dengan PTS.
Kata kunci: OFDM, teknik reduksi PAPR, selected mapping (SLM), partial transmit sequence (PTS), complementary cumulative distribution function (CCDF).
Abstract
Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique that is widely adopted by a variety of wireless communication technologies to meet the needs of highly demand on broadband wireless access. It is because OFDM provides high data rate transmission and robust against multipath fading effect. One of the major drawbacks in this system is the high PAPR value which leads to inefficiency in the use
Collision is the main issue in safe transportation, including in the railway system. Sensor systems have been developed to detect obstacles to prevent a collision, such as using cameras. One disadvantage of the camera systems is that performance detection decreases in a not clean environment, like the target position behind the fogs. This paper discusses the development of frequency modulated continuous wave (FMCW) radar signal processing for high-speed railway collision avoidance. The development of radar signal processing combines a two-dimensional constant false alarm rate (2D-CFAR) and robust principal component analysis (RPCA) to detect moving targets under clutter. Cell average (CA) and Greatest of CA (GOCA) CFAR are evaluated under a cluttered wall environment along the railway track. From the experiment, the development of FMCW radar can detect stationary or moving obstacles around 675 meters in front of the locomotive. Combining 2D-CFAR and RPCA algorithm outperforms average background subtraction in extracting moving targets from strong clutter signals along the railway track.
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