A practical MGA‐ARIMA model for forecasting real‐time dynamic rain‐induced attenuation

Abstract

[1] The novel and practical modified genetic algorithm (MGA)-autoregressive integrated moving average (ARIMA) model for forecasting real-time dynamic rain-induced attenuation has been established by combining genetic algorithm ideas with the ARIMA model. It is proved that due to the introduction of MGA into the ARIMA(1,1,7) model, the MGA-ARIMA model has the potential to be conveniently applied in every country or area by creating a parameter database used by the ARIMA (1,1,7) model. The parameter database is given in this paper based on attenuation data measured in Xi'an, China. The methods to create the parameter databases in other countries or areas are offered, too. Based on the experimental results, the MGA-ARIMA model has been proved practical for forecasting dynamic rain-induced attenuation in real time. The novel model given in this paper is significant for developing adaptive fade mitigation technologies at millimeter wave bands.

A Survey of Rain Fade Models for Earth–Space Telecommunication Links—Taxonomy, Methods, and Comparative Study

“…Empirical models SAM model [32] Singapore [33] Garcia [34] GSST [66] LU model [68] Karasawa [88] Breakpoint [29] Unified [89] YLO model [12] Statistical models M-K model [90] MARIMA [91] ITU-R P.618 [45] PEARP [92] Das Model 1 [93] Physical models Bryant [37] Crane TC [94] PM Model [95] SC EXCELL [62] Fade models Japan [96] Das model 2 [97] ITU-R P.1623 [98] Dao model [99] Learning-based AANN [100] The SAM model [32] has evolved through some previously published articles [101].…”

“…This model [91] combines GA concepts with the autoregressive integrated moving average (ARIMA) filter. The detailed steps of the MARIMA model are given in Algorithm 11.…”

“…as α is dependent on frequency (not polarization), ∩ mentioned but no mathematical form is found, ∪ rain attenuation is used, cylindrical rain cell, the rain structure is composed of heavy and light rainfall components, frequency parameter is not directly used in the calculation of the attenuation, as the applicable frequency range is limited to 10-50 GHz, ⊕ not mentioned, s-constant that depends on elevation angle and climate. The model is applicable only during the rain periods because no transition is included in the model to switch from rainy to clear sky conditions [91] Validated based on the measured rain attenuation data at Xi'an, China…”

“…MARIMA model[91] Prepare sub-databank with m-group parameters /* Using ARIMA (1,1,7) and k-NN */ 2 Initialize and define the population N /* Maximum population, N max = 2 m */ 3 Compute parameters of ARIMA /* Generate N groups of 1 × m arrays with 0/1 */ 4 Calculate the average of each "chromosome"; 5 Compute FITNESS FUNCTION, f i /* f t ← A t −ARIMA(A t−1 ,ϕ,,θ i )] 2 A t means the real value of rain-induced attenuation, and ARIMA(A t−1 , ϕ, θ i ) represents the predicted value using the parameters based on one of N. */ 6 if f i > η then7 and Mutate and then go to step 3:10 Return rain attenuation time series;…”

Prediction Algorithms: A Study

“…ARIMA integrate both the Autoregressive and Moving Average process into one. [5] ARIMA is integrated with the complex neurofuzzy system and the new computing model is able to predict a complex-valued output, of which the real and imaginary parts can be used for two different functional mappings. ARIMA is adapted to solve problems in different application fields.…”