High Dynamic Doppler Acquisition And Wireless Networks Resource Allocation

In the past decades, on one hand, the wireless mobile communication applications have evolves from the earth to the space and underwater environments; on the other hand, the wireless communication arises various new technologies, such as cognitive radio, cooperative relay and multiple input multiple output. At the physical layer, the wireless communication link usually undergoes multipath, shading, and Doppler frequency-shift, thus imposing challenges to the reliability of the link transmission. There has been extensive and effective research on the multipath and shading, the emphasis of this paper is focused on the dynamic Doppler. At the network layer, with the development of new technologies, the wireless network has developed from the simple cellular network to more and more new pattern networks, such as cognitive network and relay network. In the wireless networks, how to effectively allocation the limited spectrum resource is the key issue for the network performance. The high dynamic Doppler acquisition and the resource allocation of the cooperative relay and cognitive radio networks can guarantee the reliable link transmission and the effective network resource allocation. Hence, they have attracted increasing attention from both academic and industrial communities, and have been two of the most widely explored topics in wireless communications. The high dynamic Doppler acquisition is aimed to the deal with the relative movement between the transmitter and the receiver, thus increasing the reliability of the communication transmission links. Through the reasonable spectrum allocation strategy, the cooperative relay and cognitive radio networks can improve the performance of the entire networks, thus increasing the efficiency of the network resources. The thesis investigates the dynamic Doppler acquisition and network resource allocation for the wireless communications.The main content of this dissertation is summarized as follows.For the transmission links in the high dynamic scenarios, firstly, the influence of low signal-to-noise ratio(SNR) and the high dynamic movement on the Doppler acquisition performance is analyzed. Then, based on the limitation of the movement acceleration on the Doppler drift, one novel search-range-correction(SRC) based Doppler acquisition algorithm is proposed. In the proposed algorithm, the multiple acquisition results obtained in the previous combination periods determine the search range for the next combination period and then confines the acquisition into a more accurate frequency range, thus increasing the Doppler acquisition probability. Based on maximum likelihood criteria, the net increment of acquisition probability is also derived in a closed-form expression, with the optimal solution of the combination period selection scheme.Based on the SRC algorithm, two improved Doppler acquisition algorithms are proposed, respectively, which are named as the overlapping SRC and iterative SRC. Compared with the SRC algorithm, the overlapping SRC algorithm is realized by partially overlapping the combination period in time. After briefly introducing the core idea, the selection scheme for the overlapping factor is presented. The proposed algorithm not only increases the feasibility of overlapping factor selection, but also saves much acquisition time. Then, based on the overlapping SRC algorithm, the iterative SRC algorithm is proposed, which uses the acquisition results obtained in the previous combination periods to determine the search range for the later combination periods and forms the iterative search-range-correction process. Through the discussions of the core idea and the algorithm implementation, the upper-bound value for the Doppler acquisition probability is derived theoretically. The simulation results show that the proposed algorithms can effectively increase the Doppler acquisition probability and decrease the acquisition bias.The relay resource allocation problem in the wireless cooperative relay communication networks is studied. First, the transmission rate payoff allocation scheme among all the source users and relay users is defined. Then, the basic concept and definition of the evolutionary game theorem is given and introduced into the cooperative relay networks, thus forming the relay source allocation problem. For this problem, the corresponding evolutionary equilibrium solution is derived under the idle relay users. After that, under the busy relay users, a novel variable-population evolutionary game based relay allocation method is proposed, in which the population of the evolutionary game is monotonically non-increasing with the evolution time. Moreover, compared with the centralized water-filling allocation in network total payoff, the proposed allocation scheme is one distributed and suboptimal allocation scheme, but it is equivalent to the optimal scheme under certain cases.The application of variable-population evolutionary game based resource allocation method into the cooperative cognitive relay networks is investigated. After introducing the spectrum properties of the primary users and the secondary users in this network, the network resource allocation scheme is present based on the variable-population game. The primary user occupies the spectrum resource and acts as the source user, while the secondary user has no spectrum resource and acts as the relay users in exchange of some resource with the primary for its own transmissions. All the secondary users own the right to select the primary users for cooperation, thus forming the population of the evolutionary game. In the cooperative relay process, the secondary users consumes the power, so it needs to consider whether the payoff obtained from the cooperation can compensate its consumed power cost, thus forming the precondition for the variable-population game. Through the computer simulations results, the proposed scheme can deal with the primary user selection problem for the secondary users, and has the unique evolutionary equilibrium solution.