An important feature of the wireless network scenario is that there are multi- radio access technologies in the same area, and the signal coverage of these networks overlaps each other, forming the heterogeneous wireless network area. Network selection algorithm is the key technology of heterogeneous wireless network. The common network selection algorithms are based on accurate network attribute values. However, due to the mobility of users, the interference of wireless signals and the fluctuation of network state, the network attributes obtained by the algorithms are often uncertain. To solve this problem, this paper designs a multi-attribute access selection approach based on the fuzzy network attributes. This approach calculates the network attribute values by interval hesitant fuzzy theory at first. Then, it calculates the subjective weights of network attribute values by the analytic hierarchy process and the objective weights of network attribute values by the entropy method. The integrated weights of subjective weights and objective weights are obtained by the method based on the longest geometric distance to the negative ideal solution. In the end, we calculate the scores of candidate networks by grey relational analysis based on the intuitionistic fuzzy decision matrix. The simulation shows that the algorithm proposed by this paper can select the most suitable network and reduce the number of handoffs under the environment of uncertain network attribute values.

A heterogeneous wireless network (HWN) contains many kinds of wireless networks with overlapping areas of signal coverage. One of the research topics on HWNs is how to make users choose the most suitable network. This paper designs a user-oriented intelligent access selection algorithm in HWNs with five modules (input, user preference calculation, candidate network score calculation, output, and learning). Essentially, the input module uses a utility function to calculate the utility value of the judgment parameter; the user preference calculation module calculates the weight of the judgment parameter using the fuzzy analysis hierarchy process (FAHP) approach; the candidate network score calculation module calculates the network score through a fuzzy neural network; the output module calculates the error between the actual output value and the expected output value; and the learning module corrects the parameter of the membership function in the fuzzy neural network structure according to the error. Simulation results show that the algorithm proposed in this paper can enable users to select the most suitable network according to service characteristics and can enable users to obtain higher gains.

In heterogeneous wireless networks (HWNs), various wireless networks have signal ranges that overlap and cover each other. Enabling mobile users to access the most suitable network is one of the research topics on HWNs. This paper designs a multiattribute access selection algorithm supporting service characteristics and user preferences in HWNs, which includes five calculation modules: network attribute utility value, network attribute weight, network attribute score, user preference value, and candidate network comprehensive score. In addition, the algorithm proposed in this paper integrates the utility theory, fuzzy analysis hierarchy process (FAHP), fuzzy logic, and multiattribute decision-making (MADM) methods for a complete access selection scheme that considers different network performances, service characteristics, and user preferences. The simulation results show that the algorithm proposed in this paper can allow users to select the most suitable network while obtaining higher gains and reducing user handover between different networks.

A heterogeneous wireless network (HWN) environment contains many kinds of wireless networks, such as UMTS, LTE, and WLAN, where users move around within their coverage area. How to ensure mobile users select the most suitable network is a hot research topic for HWNs. Owing to the mobility of users, the interference of wireless signals, and the fluctuation of network status, the network attribute values obtained by mobile users are often uncertain. However, the traditional access-selection algorithms assume that mobile users can obtain accurate network attribute values, which makes users unable to access the most appropriate network. To solve this problem, this paper designs an access-selection algorithm for HWNs in the context of inaccurate network attribute values. First, the algorithm calculates the network attribute values based on the hesitant fuzzy theory, then calculates the weights of network attributes using the fuzzy analytic hierarchy process (FAHP), and finally sorts the candidate networks using the hesitant fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. The simulation results show that the proposed algorithm enables users to select the most suitable network to access under the inaccurate network attribute environment and obtain higher gains.

Wireless networks form heterogeneous wireless networks (HWNs) with overlapping signal coverage, and access selection is one of the key technologies of HWNs. Today, most access selection algorithms select appropriate networks mainly from the perspective of users while failing to consider resource allocation and optimize the overall transmission performance of HWNs. This paper proposes an access selection algorithm for HWNs based on optimal resource allocation by analyzing the wireless link transmission rate model, focusing on maximizing the HWN transmission rate, using the dynamic programming theory to derive the optimal value of bandwidth allocated to users. Experimental results show that the algorithm proposed in this paper can effectively improve network throughput and resource utilization and can connect users to the appropriate network according to QoS rate requirements.

A heterogeneous wireless network (HWN) environment contains many kinds of wireless networks, such as UMTS, LTE, and WLAN, where users move around within their coverage area. How to ensure mobile users select the most suitable network is a hot research topic for HWNs. While traditional access selection algorithms assume that mobile users can obtain accurate network attribute values, the network attribute values obtained by mobile users are often uncertain due to the mobility of users, the interference of wireless signals, and the fluctuation of the network state. To solve this problem, this paper designs an access selection algorithm for HWNs in the context of inaccurate network attribute values. First, the algorithm calculates the network attribute values based on the hesitant fuzzy theory, then calculates the weights of network attributes using the fuzzy analytic hierarchy process (FAHP), and finally sorts the candidate networks using the hesitant fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. The simulation results show the proposed algorithm enables users to select the most suitable network to access under the inaccurate network attribute environment and obtain higher gains.