## 1 Introduction
Therefore, there is an urgent need for a fast, objective and favorite-supporting network effectiveness evaluation method [14; 15; 16; 17]. Figure 1: Structure of mobile communication network of a brigade. The general definition of effectiveness is that the system or equipment can achieve the expected use target ability under the specific use conditions and within the specified time [18; 19]. However, the mobile communication system faces many tasks, which presents some characteristics such as diversity, complexity and science. Many scholars have performed relevant research and proposed evaluation methods and ideas for communication systems under different tasks and application scenarios. Some effective and typical evaluation methods and models can be summarized as follows: generalized index method; principal component analysis method [20; 21]; analytic hierarchy process (AHP) method [22; 23]; fuzzy comprehensive evaluation method [24; 25; 26]; grey correlation analysis evaluation method [27]; neural network [28; 29; 30]; and ADC method [31]. These methods have certain effects on effectiveness evaluation and are usually used with different synthetic strategies to solve different types of problems. For example, the reference [32] evaluated the security of the LTE-R communication system with AHP and the fuzzy comprehensive evaluation method and achieved the security status objectively and reasonably. Aiming at the multicriteria decision making (MCDM) problems, reference [33] used the fuzzy grey Choquet integral (FGCI) method to evaluate MCDM problems with many interactive and qualitative indexes; this method can reduce the influence of experts' subjective preference. The reference [34] combines AHP, grey correlation technique and TOPSIS to solve the problem of green decoration materials selection, this method can obtain the weight vector of hierarchical index structure reasonably. However, the evaluation index system is difficult to construct in complicated problems. The reference [35] uses the data envelopment analysis (DEA) model to describe undesirable indicators and to obtain more reasonable results with Shannon's entropy in order to assess the operational efficiency of public bus transportation. Furthermore, when considering the communication system effectiveness evaluation, the large number of influencing factors and their complex relationship renders this type of work difficult. The reference [36] used an analytic network process (ANP) to aggregate and calculate complex indicators in order to solve the problem that the dependency of elements within the hierarchy and the feedback influence of lower elements on upper elements should be considered in a complex system. The reference [37] proposed a robust mobility management scheme for (TCN) and developed a physical test-bed environment. It used service availability, network throughput and first recover packet arrival time in order to evaluate the effectiveness of the management scheme. The reference [38] proposed a fast algorithm for performance analysis for optimizing tactical communications networks in a timely fashion. For each class of traffic, this paper discussed three measures and analytical algorithms for performance ability evaluation, such as average call-arrival rate,  
Figure 2: Network planning assistant optimization system. average call-holding time and service priority. The reference [39] proposed a unified T&E framework for the test and evaluation of the tactical communication networks. It studied a visual and modular radio software programming tool that supports easy and fast test and evaluation ranges from simulations to the use of over-the-air wireless testbeds and hardware-in-the-loop network emulation tests. Therefore, it can be observed that there is currently no unified and fixed mode for the evaluation of tactical mobile communication networks, and the selection of evaluation methods and indicators is largely related to the tasks undertaken; however, simple and rapid evaluation methods are focuses of research.