Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

Abstract

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion

“…As is well known, maintaining the balance between the exploration of new possibilities and the exploitation of old certainties [ 12 , 13 ] has been considered a priority in designing an optimization scheme. As one of latest evolutionary approaches, particle swarm optimization (PSO) uses randomly placed particles on the search-space to explore new possibilities toward a global best position as a new solution to solve real-world problems [ 14 , 15 , 16 ]. PSO can be utilized in training a neural network by a population based stochastic back-propagation technique [ 17 ].…”

Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture

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Study on Dynamic Monitoring of Wire Rope Tension Based on the Particle Damping Sensor

“…Deng et al [8] proposed a new stress measuring sensor including a static magnetization unit made of permanent magnets and a magnetic field measurement unit to evaluate the axial stress in steel wires. Xu et al [9] designed a wireless sensor network technology adapted to underground channel conditions, which has important theoretical and practical value for safety monitoring in underground coal mines. Chen et al [10] designed and fabricated a miniaturized Co-based amorphous wire GMI (Giant magneto-impedance) magnetic sensor with a high sensitivity.…”