Virtual mapping method based on simulated annealing algorithm under super-intensive environment
A simulated annealing algorithm and virtual mapping technology, applied in electrical components, wireless communication and other directions, can solve the problems of the same-frequency cells becoming closer, the interference between cells is serious, and the network throughput is affected, so as to reduce the interference between cells and improve the The effect of throughput
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Embodiment 1
[0048] This embodiment provides a virtual mapping method based on a simulated annealing algorithm in an ultra-dense environment, which includes the following steps: establishing a service arrival model through the service arrival process and service duration distribution, and then determining the channel allocation matrix, and establishing an interference model ;Virtualize the wireless frequency resources, and then allocate the spectrum resources through the wireless network mapping method; so that the user's receiving signal-to-interference ratio is guaranteed, and the interference is reduced, so that the throughput of the entire system is improved.
[0049] It can be seen that this embodiment mainly includes three contents: one is the construction of ultra-dense network model and service arrival model; the other is the modeling of interference model, and the expression of signal-to-interference ratio is given; method, according to the optimization method, the spectrum resourc...
Embodiment 2
[0102] This embodiment provides a wireless virtual mapping method considering inter-cell interference in an ultra-dense environment, such as figure 2 and image 3 As shown, the method includes the following steps:
[0103] Step 1. Solution space and initial solution of the problem
[0104] The solution space S of the problem in this embodiment refers to the channel allocation matrix D that each micro base station satisfies the constraints n , through the channel allocation matrix of each micro base station, the interference and throughput of the entire network can be obtained. The solution space S can be expressed as:
[0105]
[0106] That is, the sum of each row element of each matrix is 1, and the sum of each column element is less than or equal to 1. Since the optimal solution of the simulated annealing algorithm has no strong dependence on the initial state, the initial solution is a random matrix generated by a random function.
[0107] Step 2. Objective funct...
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