Efficient Power Control In D2d-oriented Cognitive Radio Networks Based On Multiparty Bilateral Bargaining

With the rapid development of wireless communication systems, the spectrum resource becomes increasingly limited. The emergence of cognitive radio technology provides a new viable solution to improve the utilization of spectrum, and solve other issues of heterogeneous wireless networks. In cognitive radio network which is based on Underlay model, cognitive users(CUs) are allowed to communicate over the licensed spectrum of primary users(PUs) in the underlay model of cognitive network, as long as they control their transmission powers to subject to the interference temperature limit imposed by PUs. Meanwhile, for each CU, a good quality of service(Qo S) for data transmission is required. In order to guarantee CU to obtain a certain Qo S which is defined as the minimum Signal-to-Interference-Noise-Ratio(SINR), CU’s transmission power must be sufficient for its own data transmission. Moreover, the uncertainty of channel gain is a troublesome problem in wireless communication, since wireless communication channels are generally influenced by multiple composite fading in actual network scenarios, including path loss, shadow fading and small-scale fading and other multiple composite fading. The statistical characteristics of these fading effects are random and superimposed on each other, that will lead channel gain became time-varying. In order to solve cognitive users transmit power control problem under uncertain channel gains, in this present paper we focuses on the distributed power control technique in underlay cognitive radio network, which enable CUs to guarantee their interference to PUs below a predefined interference temperature limit(ITL) and meet their minimal Qo S requirement of transmission rates at the same time.First, in order to offset the impact of the uncertainty brought about by the wireless channel gain, in this paper we define the constraints for each cognitive users’ transmit power in cognitive radio networks based on statistical characteristics of the wireless channel gain between authorized users and cognitive users. And then, power control problem in underlay fashion is modeled as a constrained optimization problem of overall transmission rate of cognitive user under the constraints mentioned above.Secondly, we had the knowledge of that two main disadvantages of Karush-KuhnTucker(KKT) solutions for wireless networks power control algorithm which are described as the overhead of information exchanging is too large and computational complexity is too high. In this paper, based on Rubinstein Bargaining(RB) bargaining game model, we extend the existing bilateral multiplayer game model(Multi-party Bilateral Bargaining, MBB) to a new MBB game process described in detail in chapter four, and also give solving methods and results of the game equilibrium and lays a theoretical foundation.Finally, we combine MBB Game Model with the power control problem of cognitive wireless network, and proposes an efficient power control mechanism based on the equilibrium solution of MBB. Benefit from the requires only polynomial computational complexity of MBB equilibrium solution, this mechanism requires less communication overhead between authorized users and cognitive user, and can adapt well to the impact caused by random variation of wireless channel gain. Numerical simulation also shows that the MBB-based mechanism outperforms the existing power control mechanisms based on the Nash bargaining solution(NBS) in both total transmission rate and power control fairness.