CAREER: Addressing Fundamental Challenges for Wireless Coverage Service in the TV White Space

这个项目解决了白色覆盖网络中的基本问题，该网络在人口稠密的地区提供电视白空间频谱的数据覆盖服务。它的动机是，一个白色覆盖小区可能会承载数百个用户，同时支持高度动态的数据流量，这一场景超出了现有网络协议的能力。此外，由于人口稠密地区缺乏免费电视频道，白色封面设备可能不得不与不同类型的设备共存于同一频道。这些挑战通过新的物理层技术和先进的机器学习技术相结合来解决，并通过进一步的优化来增强解决方案。本项目研究：1)高效的节点状态检测物理层方案，可以非常高效地调度小区内的传输；2)利用强化学习技术来适应异偶干扰条件的高级协议；3)针对功率消耗和综合部分分组恢复的优化协议；以及4)全网性能分析和规划。本项目设计的白盖网络为电视白空间的现有技术提供了一种更好的选择。用户可以以比蜂窝电话网络低得多的成本享受数据覆盖，并且可以实现新的业务。该项目的预期结果包括针对白色覆盖的独特功能优化的协议和算法，并通过实验进行了测试。结果将在会议和期刊上传播；源代码将在网上免费提供。

This project addresses fundamental issues in the White-Cover network which provides data coverage services in the densely populated areas with the TV White Space spectrum. It is motivated by the fact that a White-Cover cell will likely host hundreds of users while supporting highly dynamic data traffic, a scenario beyond the capabilities of existing network protocols. In addition, the White-Cover devices will likely have to coexist in the same channel with heterogeneous devices due to the lack of free TV channels in the densely populated areas. These challenges are addressed by a combination of novel physical layer techniques and advanced machine learning techniques, and the solutions are enhanced by further optimizations. This project studies: 1) efficient physical layer schemes for node state detection with which the transmissions in the cell can be scheduled very efficiently, 2) advanced protocols that adapt to the heterogamous interferences conditions with the reinforcement learning technique, 3) optimized protocol for power consumption and integrated partial packet recovery, and 4) network-wide performance analysis and planning. The White-Cover network designed in this project provides a better alternative to the current technologies for the TV White Space. Users may enjoy data coverage at much less cost than from the cellular phone networks and new business may be enabled. The expected results of this project include the protocols and algorithms optimized for the unique features of White-Cover and tested with experiments. The results will be disseminated in conferences and journals; the source code will be freely available online.