【摘要】：隨著無線通信技術的迅猛發(fā)展,可用的頻譜資源變得越來越緊張,尤其是隨著無線局域網、無線個域網和無線城域網等技術的高速發(fā)展,目前的寬帶無線應用技術已無法滿足人們的需求。目前的頻譜分配體制造成了網絡使用方式僵化、無線頻譜規(guī)劃緊張,難以滿足未來網絡通信技術智能化、泛在化、融合化的發(fā)展趨勢。作為認知無線電技術與自組織網絡結合的認知自組織網絡,采用頻譜共享的認知無線電系統,使網絡從靜態(tài)工作模式發(fā)展到動態(tài)自適應模式,在一定程度上解決了頻譜資源短缺的問題,提高了網絡對環(huán)境的適應能力。然而,在認知自組織網絡中,網絡拓撲具有時變性,容易形成網絡孤島,進而導致認知節(jié)點之間的鏈路頻繁的斷開,需要中繼節(jié)點以多跳存儲攜帶轉發(fā)、接觸關系預測的方式將數據包以動態(tài)機會路由模式轉發(fā)至目的節(jié)點。因此,本文采用接觸可預測的方法描述不同網絡孤島間SU節(jié)點間接觸關系,基于接觸可預測的認知自組織網絡的特性,有針對性地開展了以下研究工作:1、在接觸可預測的認知自組織網絡可用頻譜與網絡拓撲時變性的前提下,提出了一種動態(tài)多路徑機會路由選擇算法-SefRoute。通過利用電磁場中電場線的分布,初步確定多條不相交路徑的軌跡,結合社交網絡中相關知識,構造出節(jié)點之間相遇概率的函數,通過機會連接率將多元社交關系中的中心性、相似性與信任度三個重要因素與節(jié)點相遇概率結合在一起。結合認知自組織網絡自身的特性構造出三個重要因素的相關函數,最終在多條不相交路徑軌跡的基礎上確定多路徑機會路由。仿真結果表明所提SefRoute算法在成功傳輸率、時延等方面均有很好的性能。2、定義了一種鏈路穩(wěn)定度指標的度量方法,結合路徑穩(wěn)定度與業(yè)務類型優(yōu)先級別提出多路徑路由動態(tài)速率分配算法。考慮用戶不同類型業(yè)務的性能參數,引入流量感知因子,在保證不同類型業(yè)務對流量需求的基礎上,將路徑穩(wěn)定性因子考慮在內,利用數學工具-非合作微分博弈建立多路徑路由動態(tài)的速率分配模型。構造最優(yōu)問題并得到最優(yōu)解,仿真分析表明,該算法在不同業(yè)務對QoS(服務質量)需求方面有很好的性能。
[Abstract]:With the rapid development of wireless communication technology, the available spectrum resources become increasingly tight, especially with the rapid development of wireless local area network, wireless personal area network and wireless metropolitan area network. The current broadband wireless application technology has been unable to meet the needs of people. The current spectrum allocation system has resulted in rigid network usage and tight wireless spectrum planning, which makes it difficult to meet the development trend of intelligent, ubiquitous and integrated network communication technology in the future. As a combination of cognitive radio technology and ad hoc network, the cognitive ad hoc network uses spectrum sharing cognitive radio system to develop the network from static mode to dynamic adaptive mode. To some extent, the shortage of spectrum resources is solved, and the adaptability of network to environment is improved. However, in cognitive ad hoc networks, the network topology is time-varying, which is easy to form a network island, which leads to frequent disconnection of links between cognitive nodes, which requires relay nodes to be stored and forwarded in multiple hops. Contact relationship prediction forwards packets to the destination node in dynamic opportunity routing mode. Therefore, the contact predictability method is used to describe the contact relationship between SU nodes in different network islands. Based on the characteristics of the contact-predictable cognitive ad hoc networks, the following research works are carried out: 1. In this paper, a dynamic multipath opportunistic routing algorithm, SefRoute., is proposed on the premise of the temporal variability of the available spectrum and the topology of the cognitive ad hoc networks. By using the distribution of electric field lines in the electromagnetic field, the locus of several disjoint paths is preliminarily determined, and the function of the probability of meeting between nodes is constructed by combining the relevant knowledge in the social network, and the centrality of the multivariate social relations is determined by the chance connection rate. Three important factors of similarity and trust are combined with the encounter probability of nodes. Based on the characteristics of cognitive ad hoc networks, the correlation functions of three important factors are constructed. Finally, the opportunity routing of multiple paths is determined on the basis of multiple disjoint paths. The simulation results show that the proposed SefRoute algorithm has good performance in the aspects of successful transmission rate and delay. Combining path stability with traffic type priority, a dynamic rate allocation algorithm for multipath routing is proposed. Considering the performance parameters of different types of services and introducing a traffic awareness factor, the path stability factor is taken into account on the basis of ensuring the traffic requirements of different types of services. A dynamic rate allocation model of multipath routing is established by using non-cooperative differential game, which is a mathematical tool. The optimal problem is constructed and the optimal solution is obtained. The simulation results show that the algorithm has good performance in different traffic requirements for QoS (quality of Service).
【學位授予單位】：河北工程大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN925

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