【摘要】：機(jī)器對(duì)機(jī)器(Machine to Machine,M2M)通信是一種不需要人為干預(yù)的機(jī)器設(shè)備之間的通信。作為物聯(lián)網(wǎng)(Internet of Things)的關(guān)鍵技術(shù)之一,M2M通信被廣泛應(yīng)用于交通、金融、智能家居、環(huán)境監(jiān)測(cè)和智能電網(wǎng)等多個(gè)領(lǐng)域。移動(dòng)蜂窩網(wǎng)絡(luò)具有高速率傳輸、大范圍覆蓋、高可靠性、易于部署等特點(diǎn),是物聯(lián)網(wǎng)業(yè)務(wù)的理想載體。但是現(xiàn)有蜂窩網(wǎng)絡(luò)主要針對(duì)人對(duì)人(Human to Human,H2H)通信進(jìn)行優(yōu)化和設(shè)計(jì),而M2M通信獨(dú)特的業(yè)務(wù)特點(diǎn)會(huì)對(duì)蜂窩網(wǎng)絡(luò)造成挑戰(zhàn)。比如低功耗廣覆蓋(Low Power Wide Area,LPWA)類業(yè)務(wù),物聯(lián)網(wǎng)網(wǎng)絡(luò)中存在海量機(jī)器類通信(Machine Type Communication,MTC)連接需求,這些連接設(shè)備速率要求低、時(shí)延不敏感,但是對(duì)功耗和覆蓋非常敏感,而蜂窩網(wǎng)容量有限不能滿足大規(guī)模MTC設(shè)備頻繁接入的需求。因此在第五代移動(dòng)通信系統(tǒng)(the 5th Generation mobile communication technology,5G)中,解決大規(guī)模設(shè)備接入問(wèn)題成為5G的關(guān)鍵場(chǎng)景之一。本文針對(duì)5G蜂窩網(wǎng)絡(luò)中LPWA類物聯(lián)網(wǎng)業(yè)務(wù)接入問(wèn)題,提出了基于非授權(quán)頻譜的覆蓋性增強(qiáng)的窄帶M2M系統(tǒng)設(shè)計(jì)方案。針對(duì)蜂窩網(wǎng)中M2M通信資源調(diào)度問(wèn)題,提出了基于強(qiáng)化學(xué)習(xí)的分布式M2M調(diào)度算法。本文主要研究?jī)?nèi)容和創(chuàng)新點(diǎn)如下:1.針對(duì)LPWA類業(yè)務(wù)特性和授權(quán)頻譜資源緊張問(wèn)題,提出一種部署在非授權(quán)頻譜的覆蓋性增強(qiáng)的窄帶M2M系統(tǒng)。本文詳細(xì)介紹了系統(tǒng)的物理層設(shè)計(jì)方案,同時(shí)針對(duì)M2M通信覆蓋增強(qiáng)的研究,提出了在發(fā)送端采用重傳機(jī)制和低階調(diào)制編碼,接收端采用多種相應(yīng)接收機(jī)制的方案達(dá)到低功耗、廣覆蓋目的。仿真結(jié)果證明了提出窄帶的M2M系統(tǒng)相比LTE系統(tǒng)可以獲得10～21dB的覆蓋增強(qiáng)。2.針對(duì)蜂窩網(wǎng)中M2M通信資源調(diào)度問(wèn)題,本文面向5G網(wǎng)絡(luò),根據(jù)M2M通信業(yè)務(wù)流量、時(shí)延等將M2M業(yè)務(wù)進(jìn)行分類。根據(jù)M2M業(yè)務(wù)類型將類型相同的終端設(shè)備分成一個(gè)簇,基于位置信息將簇內(nèi)設(shè)備分成多個(gè)接入組,然后選出組長(zhǎng)設(shè)備代表全體組內(nèi)成員申請(qǐng)調(diào)度資源。在分組的基礎(chǔ)上,提出一種基于強(qiáng)化學(xué)習(xí)的分布式M2M調(diào)度算法,將調(diào)度問(wèn)題建模為多智能體學(xué)習(xí)機(jī),具有強(qiáng)化學(xué)習(xí)能力的組長(zhǎng)設(shè)備們通過(guò)基于收集到的環(huán)境信息,通過(guò)試錯(cuò)的方式尋找最優(yōu)的無(wú)線調(diào)度資源完成數(shù)據(jù)傳輸。通過(guò)與其他先存方法對(duì)比,仿真結(jié)果證明了該算法的可行性、公平性和優(yōu)勢(shì)。
[Abstract]:Machine to machine (Machine to machine M 2m communication is a kind of communication between machine and equipment without human intervention. As one of the key technologies of Internet of things (Internet of Things), M2M communication is widely used in many fields, such as transportation, finance, smart home, environment monitoring and smart grid. Mobile cellular network is an ideal carrier for Internet of things services because of its high speed transmission, wide coverage, high reliability and easy deployment. However, the existing cellular networks are mainly focused on the optimization and design of human (Human to human H2H) communications, and the unique service characteristics of M2M communications will challenge the cellular networks. For example, low power and wide coverage of (Low Power Wide area (Low Power Wide) class services, there are a large number of machine communication (Machine Type communication (Low Power Wide connection requirements in the Internet of things network, these connection devices require low speed, delay is not sensitive, but very sensitive to power consumption and coverage. However, the limited capacity of cellular network can not meet the needs of frequent access to large scale MTC devices. Therefore, in the fifth generation mobile communication system (the 5th Generation mobile communication technology 5G), solving the problem of large scale equipment access becomes one of the key scenarios of 5G. In this paper, we propose a design scheme of narrow-band M2m system based on unauthorized spectrum coverage enhancement for LPWA class Internet of things (IoT) service access in 5G cellular networks. A distributed M2m scheduling algorithm based on reinforcement learning is proposed for M2m communication resource scheduling in cellular networks. The main contents and innovations of this paper are as follows: 1. In order to solve the problem of LPWA traffic characteristics and resource shortage of authorized spectrum, a narrowband M2m system with enhanced coverage in unauthorized spectrum is proposed. In this paper, the physical layer design scheme of the system is introduced in detail. At the same time, aiming at the research of M2m communication coverage enhancement, a scheme of using retransmission mechanism and low order modulation coding in the transmitter is proposed, and the receiver adopts a variety of corresponding receiving mechanisms to achieve low power consumption. Wide coverage purpose. The simulation results show that the proposed narrowband M2m system can obtain the coverage enhancement of 10~21dB compared with LTE system. Aiming at the scheduling problem of M2m communication resources in cellular networks, this paper classifies M2m services according to M2m traffic and delay. According to the M2m service type, the terminal devices of the same type are divided into a cluster, the devices in the cluster are divided into multiple access groups based on the location information, and then the leader equipment is selected to apply for scheduling resources on behalf of all the members of the group. On the basis of grouping, a distributed M2m scheduling algorithm based on reinforcement learning is proposed. The scheduling problem is modeled as a multi-agent learning machine. To find the optimal wireless scheduling resource to complete data transmission by trial and error. The simulation results show that the algorithm is feasible, fair and superior.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5

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本文編號(hào)：2160174