移动异构物联网接入网中冲突与恶意干扰感知的速率自适应问题研究

Rate adaptation, which selects the best physical bit rate according to the wireless link quality, is the most efficient method to improve the performance of throughput of access network in Internet of Things. However, the highly dynamic and heterogeneous network scenarios, huge amounts of data, broadcast and shared wireless channel bring new challenges to such problem. The most difficult point lies in the timely changes and unpredictability of link quality, and collisions and malicious interference which will affect rate adaptation decisions. At present, the most existing work focuses on the homogeneous wirless local area networks, which have problems of low throughput and vulnerability to malicious interference attacks. . In our project, we will investigate the rate adaptation problem in mobile and heterogeneous access networks in Internet of Things. First, we will analyze the communication characteristics of links, collision patterns and behavior characteristics of malicious interference through extensive experiments. Then, a new method to evaluate and estimate link quality is presented, and also a method to indentify the collisions and malicious interference. Our methods are at the premise of minimizing the overhead of sensing link quality, and keeping the identification method of collisions and malicious interference accurate and simplified. Finally, based on the link quality estimation results and identification outcomes, we design a scheme that is aware of collisions and malicious interference to select rate adaptively. The goal of our method is to guarantee a certain throughput performance for access networks and some ability to anti-malicious-interference for access equipment. Our proposed methods will be systematically evaluated by simulation analysis and real network scenario experiments.

速率自适应，即节点根据无线链路的通信质量选择最优的物理层比特速率，是提升物联网接入网吞吐量性能的最有效方法。然而，接入网的高动态性与强异构性、数据的海量性和无线信道的广播共享性给该问题的研究带来挑战，最大的难点在于链路通信质量的实时变化和不可预测性，及冲突与恶意干扰对速率选择的影响。目前，该领域的研究主要集中在同构无线局域网，存在吞吐量低和易受恶意干扰攻击等问题。. 本项目针对“移动异构物联网接入网中的速率自适应问题”，分析“链路的通信特征、冲突模式及恶意干扰行为特征”，以此为基础，以“最小化链路感知开销”和“冲突与恶意干扰识别方法准确、简单可行”为前提，以“保证接入网一定的吞吐量性能和接入设备一定的抗恶意干扰能力”为目标，提出一种新的链路质量评估与预测方法和冲突与恶意干扰识别方法，及与之匹配的冲突与恶意干扰感知的速率自适应机制，通过仿真分析与实际网络测试对其进行系统的验证。

本课题以最大化无线带宽资源的利用率，提升物联网接入网的累计吞吐量性能，增强接入设备抗恶意干扰的能力，满足物联网前端感知网中海量数据对接入互联网的服务质量需求为目标。本课题对物联网接入网中链路冲突模式、恶意干扰行为特征和速率自适应问题进行了研究，建立了一套移动异构物联网接入网中冲突与恶意干扰感知的速率自适应选择协议。.主要研究成果包括（1）提出了一套针对低占空比、多信道和移动异构物联网邻居发现协议，实现了多信道同步异步邻居发现Quorum系统，在发现延时和能耗直接取得很好的权衡；（2）设计并实现了一种基于RSSI和CSI的链路质量估计与分组丢失与错误原因识别方法，实现了基于时间、空间和频率三维特征属性的链路质量预测方法，以低的开销提供实时、准确的链路质量信息和分组丢失与错误原因识别结果；（3）提出了一种基于RSSI和CSI的两级速率自适应算法，能够有效解决速率搜索空间大和速率选择收敛慢的问题；（4）提出了一种基于Quorum的信道自适应算法，能够有效降低冲突和恶意干扰对数据传输的影响；（5）实现了一种冲突与恶意干扰感知的信道和速率联合自适应协议，该协议能够有效提高物联网接入网的累积吞吐量性能。.相关研究成果发表在本领域知名国际期刊上（Wireless Personal Communications、Transactions on Emerging Telecommunications Technologies， IEEE Communication Letters等）和国际会议上。共计7篇论文，其中SCI检索6篇，EI检索1篇。