本文選題：超密集無線網(wǎng)絡(luò) + 非協(xié)作博弈�。� 參考：《南京郵電大學(xué)》2017年碩士論文

【摘要】：隨著移動互聯(lián)網(wǎng)興起和大數(shù)據(jù)時代的來臨,移動數(shù)據(jù)傳輸?shù)男枨笤跇O速增加。另一方面,綠色通信、低碳生活已經(jīng)成為可持續(xù)發(fā)展的必然要求,這給無線通信網(wǎng)絡(luò)運(yùn)營和管理帶來了越來越大的挑戰(zhàn)。為了滿足終端用戶對高質(zhì)量、高速率的需求,超密集無線網(wǎng)絡(luò)是應(yīng)對此挑戰(zhàn)的重要解決方案。在超密集無線網(wǎng)絡(luò)環(huán)境下,傳統(tǒng)的資源分配算法已經(jīng)無法適用于未來網(wǎng)絡(luò)的發(fā)展。如何解決超密集無線網(wǎng)絡(luò)環(huán)境下的資源分配問題,成為未來網(wǎng)絡(luò)發(fā)展的嚴(yán)峻考驗(yàn)。本文在介紹已有的資源分配技術(shù)的基礎(chǔ)上,主要研究了三個方面的工作:(1)提出一種基于非協(xié)作博弈的資源分配算法。該算法將非協(xié)作博弈理論應(yīng)用到超密集無線網(wǎng)絡(luò),通過在效用收益中引入非線性懲罰函數(shù)來緩解干擾與提高用戶公平性,然后證明所提算法的納什均衡存在與唯一性,并給出了具體詳細(xì)的非協(xié)作博弈分布式算法。仿真結(jié)果表明所提算法在提高系統(tǒng)吞吐量、降低發(fā)射功率、提高算法收斂概率等方面具有卓越的性能。(2)提出了一種基于干擾協(xié)調(diào)的能效資源分配算法。該算法研究分簇后的超密集無線網(wǎng)絡(luò),借助圖論著色原理對簇間與簇內(nèi)干擾協(xié)調(diào),減少網(wǎng)絡(luò)信令交流。簇內(nèi)資源由簇頭進(jìn)行分配,在干擾協(xié)調(diào)的基礎(chǔ)上,分別采用最大最小算法和引入阻尼震動與適應(yīng)度變異改進(jìn)的粒子群算法對子信道和功率資源進(jìn)行分配。仿真結(jié)果表明該算法可以有效減少能量消耗、提高能量效率及降低網(wǎng)絡(luò)干擾。(3)設(shè)計并實(shí)現(xiàn)了超密集無線網(wǎng)絡(luò)資源管理驗(yàn)證平臺,搭建了一個超密集無線網(wǎng)絡(luò)驗(yàn)證系統(tǒng)。系統(tǒng)由客戶端(終端用戶)、eNodeB(Evolved Node B)小基站和資源管理平臺服務(wù)器、數(shù)據(jù)庫組成。該平臺針對超密集無線網(wǎng)絡(luò)中干擾協(xié)調(diào)、無線資源分配和能量消耗問題,平臺實(shí)現(xiàn)了全局資源實(shí)時監(jiān)控、eNodeB小基站部署圖的展示以及基于干擾協(xié)調(diào)的動態(tài)頻譜分配策略和綠色節(jié)能休眠策略研發(fā)。測試結(jié)果表明,資源管理平臺能夠降低網(wǎng)絡(luò)干擾、減少系統(tǒng)能耗、有效的進(jìn)行頻譜分配。最后,對本文研究進(jìn)行了歸納總結(jié),并對未來工作的深入方向和思路進(jìn)行了展望。
[Abstract]:With the rise of mobile Internet and the advent of big data era, the demand for mobile data transmission is increasing rapidly. On the other hand, green communication, low-carbon life has become the inevitable requirement of sustainable development, which brings more and more challenges to the operation and management of wireless communication network. In order to meet the demand of end users for high quality and high speed, ultra dense wireless network is an important solution to meet this challenge. In the super dense wireless network environment, the traditional resource allocation algorithm can not be applied to the future development of the network. How to solve the problem of resource allocation in ultra-dense wireless network environment will be a severe test of network development in the future. Based on the introduction of existing resource allocation techniques, this paper mainly studies three aspects of work: 1) and proposes a resource allocation algorithm based on non-cooperative game. In this algorithm, the non-cooperative game theory is applied to the super-dense wireless networks, and the nonlinear penalty function is introduced to mitigate the interference and improve the fairness of the users. Then, the existence and uniqueness of the Nash equilibrium of the proposed algorithm are proved. A detailed distributed non-cooperative game algorithm is presented. Simulation results show that the proposed algorithm has excellent performance in improving system throughput, reducing transmission power and improving convergence probability of the algorithm. (2) an energy efficiency resource allocation algorithm based on interference coordination is proposed. Based on the graph theory coloring principle, the algorithm is used to coordinate the inter-cluster interference and intra-cluster interference, so as to reduce the network signaling exchange. The resources in the cluster are allocated by cluster heads. On the basis of interference coordination, the maximum and minimum algorithm and particle swarm optimization algorithm with improved damping vibration and fitness mutation are used to allocate subchannels and power resources, respectively. Simulation results show that the algorithm can effectively reduce energy consumption, improve energy efficiency and reduce network interference. The system consists of client (end user) small base station and resource management platform server, database. The platform aims at interference coordination, wireless resource allocation and energy consumption in ultra-dense wireless networks. The platform realizes the display of the deployment diagram of global resource real-time monitoring and monitoring of small base station, the dynamic spectrum allocation strategy based on interference coordination and the research and development of green energy saving dormancy strategy. The test results show that the resource management platform can reduce the network interference, reduce the energy consumption of the system, and effectively allocate the spectrum. Finally, the research is summarized, and the future work is prospected.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN929.5

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本文編號：1985708