基于能量收集的無線傳感網絡關鍵技術研究與實現

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基于能量收集的無線傳感網絡關鍵技術研究與實現(任務書,開題報告,外文翻譯,論文17000字,答辯PPT)
摘要
通信領域的飛速發展所帶來的能源消耗和環境污染問題已經引起了國內外研究組織的廣泛關注,并提出了降低未來無線通信系統能耗和綠色通信的目標。能量收集技術的出現,離實現這個目標更進了一步。能量收集技術不僅可以通過可再生能源,解決網絡節點的電池更換不方便的問題,還可以解決碳排放量過高的問題,因此也受到國內外學者越來越多的關注。
與此同時,用戶需求量的指數型增長導致網絡高度密集化,還有無線通信網絡將面臨信道衰落和噪聲干擾問題。這些都會成為影響未來無線通信技術發展的因素。因此,基于能量收集技術和無線傳感網絡技術在將來的第五代(5G)無線通信系統起著關鍵性的作用。本論文借助馬爾科夫鏈以及概率論等基礎理論工具,基于能量收集的無線傳感網絡關鍵技術展開研究。論文的主要包括以下三個部分:
首先,通過廣泛的調研,本文概述了能量收集技術。通過詳細介紹其技術特點和與可再生能源相結合,以此來解決網絡節點的電池更換不方便以及碳排放量過高的問題。無線傳感網絡技術的特點和應用領域,用其大規模性和自適應性來解決用戶需求量逐漸增長的問題。還有總結了國內外相關研究組織對這兩種關鍵技術的研究成果。
其次,在基于能量收集無線傳感網絡的場景下,本文提出了一種基站與用戶數據與能量交互的模型,并且考慮了用戶需求和能量傳輸兩個方面。通過采用隨機過程數學工具,設計了多能量級的能量收集馬爾科夫模型,對基于能量收集節點的傳輸機會進行度量。結果表明,隨著能量從上一個能量級到達下一個能量級的概率增加,傳輸機會也會增加。而用戶需求數據交流的概率和能量到達可以傳輸給用戶的能量級增加,傳輸機會會隨之降低。
最后,在基于發射機與接收機經過瑞利信道衰落和噪聲干擾的場景下,本文提出了一種降低中斷概率的方法,將多能量級能量收集模型中的能量級增加,可以明顯降低中斷概率。通過采用概率論相關數學工具,對于無線傳感網絡來說,我們分析了多能量級能量收集的中斷概率,將其與仿真結果相比較,最終證明中斷概率的理論推導和實際結果相符合,并且提出降低中斷概率的方法是可行的。
   
關鍵詞:能量收集;可再生能源;無線傳感網絡;馬爾科夫鏈;

Abstract
The energy consumption and environmental pollution caused by the rapid development of communication field have attracted the attention of research organizations at home and abroad, and put forward the goal of reducing energy consumption and green communication in future wireless communication systems. The advent of energy harvesting technology is a step closer to achieving this goal. Energy collection technology can not only solve the problem of inconvenient battery replacement by renewable energy, but also solve the problem of high carbon emissions, so it is also paid more and more attention by scholars at home and abroad.
At the same time, the exponential growth of user demand leads to high network density, and wireless communication network will be faced with the problem of channel fading and noise interference. These will become the factors that affect the future development of wireless communication technology. Therefore, energy harvesting technology and wireless sensor network technology will play a key role in the future fifth generation (5G) wireless communication system. With the help of the basic theory tools such as Markoff chain and probability theory, this paper studies the key technologies of wireless sensor networks based on energy harvesting. The paper mainly includes the following three parts:
First of all, through extensive research, this paper outlines the energy harvesting technology. In order to solve the problem of inconvenient battery replacement and high carbon emission, the technical features of the network and the combination of renewable energy are introduced in detail. The characteristics and application fields of wireless sensor network technology solve the problem of increasing user demand with its large scale and adaptability. It also summarizes the research results of the two key technologies by relevant research organizations at home and abroad.
Secondly, in the scene based on the energy collection wireless sensor network, this paper presents a model of the interaction between the base station and the user's data and energy, and takes into account the two aspects of user demand and energy transmission. By using the stochastic process mathematical tools, a multi energy level energy collection Markov model is designed to measure the transmission opportunities based on the energy collection nodes. The results show that as the probability of energy reaching the next energy level from the last energy level increases, the transmission opportunity also increases. The probability and energy of user demand data exchange can reach the energy level that can be transmitted to the user, and the transmission opportunity will decrease.
Finally, in the scene based on the Rayleigh fading and noise interference of the transmitter and receiver, a method to reduce the interruption probability is proposed, which increases the energy level in the multi energy level energy collection model, and can obviously reduce the interruption probability. By using the mathematical tools of probability theory, for the wireless sensor network, we analyze the interruption probability of the multi energy level energy collection, and compare it with the simulation results. Finally, it proves that the theoretical deduction of the interruption probability is consistent with the actual results, and it is feasible to reduce the interruption probability.

Keywords:Energy harvesting; Renewable energy;Wireless sensor network; Markoff chain
 

基于能量收集的無線傳感網絡關鍵技術研究與實現
基于能量收集的無線傳感網絡關鍵技術研究與實現
基于能量收集的無線傳感網絡關鍵技術研究與實現
基于能量收集的無線傳感網絡關鍵技術研究與實現


目錄
摘要(中文)    Ⅰ
(英文)    Ⅱ
第一章緒論    1
1.1 研究的背景及意義    1
1.1.1 研究的背景    1
1.1.2研究的意義    1
1.2 面臨的挑戰及內容安排    2
1.2.1 面臨的挑戰    2
1.2.2 研究內容    2
1.2.3本文的內容安排    2
第二章基于能量收集的無線傳感網絡技術    3
2.1 能量收集技術    3
2.1.1 技術特點及可再生能源    3
2.1.1.1 技術特點    3
2.1.1.2 可再生能源    3
2.2無線傳感網絡技術    4
2.2.1 技術特點及應用領域    5
2.2.1.1 技術特點    5
2.2.1.2 應用領域    5
2.3國內外研究成果    6
第三章基于能量收集的無線傳感網絡模型    8
3.1 引言    8
3.2 系統模型    8
3.3 基于馬爾科夫鏈的多能量級能量收集模型    9
3.4 傳輸機會    10
3.5發射機傳輸模型    11
3.6信道與噪聲    11
3.6.1 瑞利信道    11
3.6.2 萊斯信道    12
3.6.3高斯白噪聲    13
3.7中斷概率    14
3.8仿真與數值分析    14
3.9本章小結    16
第四章總結與展望    17
4.1 全文總結    17
4.2 遇到的困難、解決方法及心得體會    17
4.3未來研究展望    17
結束語    19
參考文獻    20

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