Parameter Estimation for a Capacitive Coupling Communication Channel Within a Metal Cabinet Based on a Modified Artificial Immune Algorithm

Abstract

The channel model optimization algorithm plays a critical role in novel communication method research. Wireless sensor connections using capacitive coupling communication inside a metal cabinet such as spacecraft are an emerging communication technology. However, channel modeling along with optimization methods have not been systematically investigated. In this paper, a modified artificial immune algorithm (MAIA) was developed to optimize a few tens of model parameters for the capacitive coupling communication channel within a metal cabinet. The mathematical model of the communication channel was derived from the equivalent circuit model by analyzing the capacitive coupling electric field distribution. Unknown parameters in the model were optimally estimated by adopting MAIA with the objective of minimizing the root mean square error (RMSE) between the model computed data and simulation or experimental data. The proposed scheme enhanced the convergence performance by incorporating the artificial bee colony (ABC) algorithm, modifying the strategies of immune operations and introducing a similarity detection step. Validation results showed that the frequency response of the optimized model matched well with the simulation and experimental data, verifying the feasibility and robustness of the proposed MAIA. Compared with three other state-of-the-art ABC algorithms and three enhanced intelligent algorithms, it was demonstrated that the proposed algorithm performed better with respect to convergence speed and accuracy. The study provided a multiparameter channel model estimation solution for capacitive coupling communication within a metal cabinet research.

Recursive Identification for MIMO Fractional-Order Hammerstein Model Based on AIAGS

“…Because the concentration represents the quality of population diversity, and too high concentration means that there are many very similar individuals in the population, the key point of the immune algorithm is to suppress the individuals with a high concentration to achieve global optimization. However, in both the original algorithm and various improved immune algorithms today, the coefficient b is non-negative, which leads to a minor incentive for individuals with low affinity and high concentration [34][35][36][37][38]. This improvement conforms to the core concept of the algorithm.…”

“…In the original algorithm, the a and b are constants. In various improved algorithms [34][35][36][37][38], the adaptive coefficients are only related to the number of current iterations. Because the comparison of stimulations between individuals is carried out in the population of the current iteration, these adaptive coefficients are not different from constants.…”

Channel modeling and characterization of capacitive coupling communication within a metal cabinet

“…However, in view of the ubiquitous requirements of non-line-ofsight (NLOS) transmission with strong fading caused by various metal components in narrow, compact and closed metal spaces, traditional radio frequency (RF) or optical wireless communication technology is faced with great challenges [8][9][10] . As a solution to this problem, the method of capacitive coupling communication within a metal cabinet is becoming an appealing technology 7,11,12 . Capacitive coupling communication was firstly proposed by Zimmerman 13 , and was widely used in human body communication to realize the data transmission between wearable devices or implantable devices using electric field coupling [14][15][16] .…”

Parameter Estimation in Neutral Delay Differential Equations Using Genetic Algorithm With Multi-Parent Crossover

“…Heuristic algorithms have also been shown to be effective in identifying parameters of S-System models [30]- [32]. Other recent works on the application of various heuristic optimization methods on estimating parameters of engineering systems are found in [33]- [41].…”