Wavelet Based Cognitive UWB Sensors for Smart Tunnels

用于智能隧道的基于小波的认知 UWB 传感器

• 批准号: 490434-2015
• 负责人: Raahemifar, Kaamran
• 金额: $ 8.74万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=601424
• 关键词: Wavelet; Based; Cognitive; UWB; Sensors

The goal of the proposed research project is to enhance the safety of the subway tunnels as well as underground mining environment and to maintain an uninterrupted data transmission between train driver or miners and the controllers using Ultra Wide-Band (UWB) sensor network. Since UWB's wide range of frequency band causes mutual interference with other wireless services such as IEEE 802.11 a, cognitive capabilities will be developed to mitigate the interference within the UWB bandwidth and enhance the monitoring performance. Cognitive radio equipped with spectrum sensing can deal with spectrum scarcity and utilize the spectrum holes without causing harmful interference to the licensed users. Cognitive features enable the proposed UWB sensor network to detect the sources of interfering signals and avoid them in the wavelet based transmitter. Such feature enables the system to eliminate interference with various wireless services of clients in a tunnel environment; e.g. users of mobile devices, PCs and Wi-Fi can enjoy uninterrupted services while commuting in subway. Likewise, wireless communication in underground mines suffer from serious environmental noise and channel impairments. The large mining and electromechanical equipment, with high power and frequent starts, produce additive Gaussian white noise and pulse jamming leading to interference with UWB network. The proposed UWB network can sense the tunnel environment, decides and mitigates the impacts of interfering users on the data transmission. This project incorporates wavelet radio as an integrated part of the UWB sensor network. In terms of multicarrier modulation (MCM), wavelet based MCM can offer more spectrum efficiency and enhance the robustness against noise and inherent interference of conventional OFDM system. Wavelet based UWB channel modeling of tunnels can reduce the number of required coefficients of channel representation with high degree of time-frequency localization compared to the Fourier based method. Due to the complex nature of underground tunnels, cooperative spectrum sensing is proposed to alleviate the effects of shadowing and multipath fading on the UWB sensor network.

该研究项目的目标是利用超宽带（UWB）传感器网络，提高地铁隧道和地下采矿环境的安全性，并保持列车驾驶员或矿工与控制器之间的不间断数据传输。由于UWB的宽频带范围会与其他无线业务（如IEEE 802.11 a）产生相互干扰，因此将开发认知能力以减轻UWB带宽内的干扰并提高监控性能。具有频谱感知功能的认知无线电可以在不给许可用户造成有害干扰的情况下，解决频谱稀缺问题，利用频谱漏洞。认知特性使所提出的超宽带传感器网络能够在小波发射机中检测到干扰信号源并避免干扰。该特征使系统能够在隧道环境中消除对客户端各种无线业务的干扰；例如，使用移动设备、个人电脑和Wi-Fi的用户可以在乘坐地铁时享受不间断的服务。同样，地下矿井的无线通信也受到严重的环境噪声和信道损伤的影响。大型矿山、机电设备功率大、启动频繁，会产生加性高斯白噪声和脉冲干扰，导致对超宽带网络的干扰。提出的超宽带网络可以感知隧道环境，判断和减轻干扰用户对数据传输的影响。该项目将小波无线电作为超宽带传感器网络的一个组成部分。在多载波调制（MCM）方面，基于小波变换的MCM可以提高频谱效率，增强传统OFDM系统对噪声和固有干扰的鲁棒性。与基于傅立叶的方法相比，基于小波的隧道超宽带信道建模可以减少信道表示所需系数的数量，并且具有高度的时频局域性。由于地下隧道的复杂性，为了减轻UWB传感器网络中阴影和多径衰落的影响，提出了协同频谱感知技术。