A multi-objective topology control method based on incentive cooperation in heterogeneous wireless access networks
A wireless access network and topology control technology, applied in wireless communication, network planning, network traffic/resource management, etc., can solve problems such as network topology performance impact
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Embodiment 1
[0104] 300 nodes are randomly distributed in a square area of 1000m×1000m, and a base station is located in the center of the area. In ILDIA, w p 、w t and w f Take 0.3, 0.3 and 0.4 respectively. The simulation results of the four methods are shown in Figure 1 to Figure 4 .
[0105] figure 1 It is shown that as the k-neighborhood range expands, the performance parameter p of ILDIA, LDIA and LMIA av All were improved to varying degrees, especially LDIA and LMIA. This shows that knowing more about the network information is more beneficial to the improvement of the performance parameter, but it needs to pay more message exchange cost. When reaching the neighborhood range of 8 hops and above, the performance parameter p of LDIA av It is better than LMIA, because at this time the effects of LDIA and LMIA are close to (or reach) the effects of DIA and MIA, respectively. Literature [2] pointed out that the performance parameter p of DIA av It is better than MIA, but both...
Embodiment 2
[0109] In this embodiment, network nodes are randomly distributed in a square area of 1000m×1000m, and a base station is located in the center of the area, but the number of nodes is variable, that is, from 300 to 600 in increments of 25 each time. Each node can obtain the network information of its 2-hop neighborhood at most. The simulation results of the four methods are shown in Figure 5 to Figure 8 .
[0110] The purpose of this example is to simulate the node density vs. p av , t av 、h av and Δb av Impact. Figure 5 shows that the effect of node density on the p of LDIA, LMIA and CTCA av The impact is greater, and the greater the node density, the better it is to improve p av (i.e. reducing p av ); ILDIA needs to juggle multiple goals and will not focus on p av This performance parameter, therefore, increases in density in favor of optimizing p av opportunities cannot be fully exploited.
[0111] Figure 6 and 7 shows that the four methods of t av and h ...
Embodiment 3
[0113] 300 nodes are randomly distributed in a square area of 1000m×1000m, and a base station is located in the center of the area. This example is in ILDIA's w p 、w t and w f When taking four groups of typical values respectively, compare p av , t av 、h av and Δb av The changing trend presented with the change of k-neighborhood scope. Simulation results see Figure 9 to Figure 12 . A basic trend can be seen from it. When increasing the weight of the transmit power performance target to 0.8, the performance of the target can be significantly improved, but significantly increasing the weight of the mean square error of link delay and link life cannot guarantee improvement. The performance of the two targets, this may be because the factors affecting the two performance indicators are not single, therefore, the changes of each influencing factor may be mutually restrained. Other trends are similar to Example 1.
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