Interference-Aware Routing And Power Control Algorithm In Hybrid Wireless Networks

The wireless technology is becoming indispensable and ubiquitous. However, in the meantime the spectrum is becoming more crowded than ever before. As a result, improving the spectral efficiency is still a key problem in wireless research. In recent years, the hybrid wireless network is emerging. It comprises a cellular network and an ad-hoc (device-to-device, D2D) network. By inheriting the advantages of both networks, the hybrid wireless network is supposed to be better than either single network. The difference between the hybrid wireless network and wireless mesh networks is that the hybrid can support the mobility as traditional cellular network. The hybrid network is also different from classical heterogeneous ones, because the two basic networks share the same spectrum. Since the spectrum they use is the same, the interference between two networks is inevitable. The solution to the interference is also the key to improving the performance gain. Thus, the hybrid hierarchy itself is challenging. Nevertheless, Cognitive Radio (CR) provides a solution to this key problem.Since the beginning of the CR research, it has been aimed to dynamically and intelligently utilize the idle resources in authorized spectrum. The core of CR technology is to enable the equipments to cognize and learn from the radio environment, so that equipments or devices can make judgment and adjust their radio parameters. In the hybrid wireless networks, CR will enable user equipments (UE) to optimize the network intelligently, and to avoid the interference effectively. Moreover, thanks to the CR-equipped UE, only minor adjustment is necessary to update the traditional cellular network to a hybrid wireless network.This paper is based on CR technology and assumption that the CR-equipped UE are able to learn and to make decisions. We designed an interference-aware cost model, which considered interference as network costs. Then an algorithm is proposed to optimize the mode switching, routing and power control. Finally, two simulation scenarios are designed to testify the performance gain that provided by the new model and algorithm. It is proved that the new model and algorithm is an effective way to solve the mode switching, routing and power control problem in hybrid wireless networks, and simultaneously provides promising performance gain.