CIF: Small: Mathematical Tools for Unifying and Simplifying the Analysis and Optimization of Wireless Networks

CIF：小型：用于统一和简化无线网络分析和优化的数学工具

• 批准号: 1910868
• 负责人: Annamalai Annamalai
• 金额: $ 42.09万
• 依托单位: Prairie View A & M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910868&HistoricalAwards=false
• 关键词: CIF; Small; Mathematical; Tools; Unifying

The advent of Internet-of-Things (IoT) devices that are connected through wireless networks will dramatically transform the way people and machines interact with their world, enabling many new applications ranging from environmental sensing and disaster relief to smart grids, intelligent transportation, and mobile healthcare. Given the limited wireless spectrum, any wireless communication technique should optimally utilize the limited radio resources. Network operators should be able to quantify the performance of the emerging adaptable wireless networks under realistic assumptions of propagation environments prior to deployment. However, the design space for such exploration is huge and an exhaustive exploration of this space via experimental studies and/or simulation approaches is typically impractical, time-consuming and/or expensive. This project attacks this challenge by developing novel analytical tools that are both simple in form and easy to evaluate, yet yield accurate performance predictions in relevant operational regimes. These tools will yield deep insights into the dependence of various design parameters on system performance. This knowledge, in turn, will guide wireless system engineers and network operators in their designs and efficiently perform system trade-off studies at a fraction of computer simulations run-time and costs, especially at early design stages. The educational and outreach activities will substantially improve the wireless research and education infrastructure at a historically black university and produce a skilled workforce in a rapidly growing field. Today, it is extremely challenging to accurately characterizing the wireless link layer performances of advanced transceivers that capture the non-linearity of the propagation medium, multi-path fading and co-channel interference. The principal difficulty stems from finding analytically tractable expressions (preferably in closed-form) for the density function of various arithmetic combinations (e.g., partial sums, ratios, products, powers) of random variables drawn from generalized fading distributions. Moreover, limitations of the state-of-the-art exact analytical tools impede efficient computations of some important new wireless performance measures such as the higher-order statistics of channel capacity and symbol error probabilities in generalized fading channel models. This project seeks to address these challenges by focusing on three specific research tasks: (1) develop new classes of asymptotic performance bounds/approximations for accurately predicting wireless networks perturbed by multi-path fading and interference in generalized stochastic fading environments; (2) develop closed-form exponential-type approximations for powers of the conditional error probabilities of digital modulations as well as alternative integral representations for the Nuttall-Q, Marcum-Q and incomplete Gamma functions that will facilitate the statistical averaging task of random variables in their arguments; and (3) build upon the mathematical tools developed in tasks (1) and (2) in unifying and simplifying the analysis and optimization of emerging wireless systems. This project's framework is expected to yield computationally stable and efficient solutions to numerous wireless performance analyses problems that heretofore had resisted solutions in simple forms, facilitate investigation and development of cross-layer design rules for next-generation adaptable wireless networks as well as bridge some knowledge gaps in wireless communication theory.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

通过无线网络连接的物联网(IoT)设备的出现将极大地改变人和机器与世界互动的方式，实现从环境传感和救灾到智能电网、智能交通和移动医疗的许多新应用。在无线频谱有限的情况下，任何一种无线通信技术都应该优化利用有限的无线资源。网络运营商应该能够在部署之前根据传播环境的现实假设来量化新兴的自适应无线网络的性能。然而，这种探索的设计空间是巨大的，通过实验研究和/或模拟方法对这个空间进行详尽的探索通常是不切实际的、耗时的和/或昂贵的。该项目通过开发形式简单且易于评估的新型分析工具来应对这一挑战，同时在相关业务制度中产生准确的业绩预测。这些工具将深入了解各种设计参数对系统性能的依赖。反过来，这些知识将指导无线系统工程师和网络运营商进行设计，并以计算机模拟运行时间和成本的一小部分高效地执行系统权衡研究，特别是在早期设计阶段。教育和推广活动将大大改善一所历史悠久的黑人大学的无线研究和教育基础设施，并在一个快速增长的领域培养一支熟练的劳动力队伍。今天，准确描述先进收发信机的无线链路层性能是非常具有挑战性的，这些收发信机能够捕获传播介质的非线性、多径衰落和同频道干扰。主要困难在于为从广义衰落分布中提取的随机变量的各种算术组合(例如，部分和、比率、乘积、幂)的密度函数找到分析上容易处理的表达式(最好是闭合形式)。此外，最新的精确分析工具的局限性阻碍了一些重要的新的无线性能指标的有效计算，例如在广义衰落信道模型中的信道容量和符号错误概率的高阶统计量。该项目试图通过集中于三个具体的研究任务来解决这些挑战：(1)开发新的渐近性能界/近似，用于在广义随机衰落环境中准确地预测受多径衰落和干扰干扰的无线网络；(2)开发数字调制条件误差概率的幂的闭合形式的指数型近似，以及Nutall-Q、Marcum-Q和不完全Gamma函数的替代积分表示，以便于在其参数中执行随机变量的统计平均任务；以及(3)建立在任务(1)和(2)中开发的数学工具，以统一和简化新兴无线系统的分析和优化。该项目的框架预计将为众多无线性能分析问题提供计算稳定和高效的解决方案，这些问题到目前为止一直拒绝以简单的形式解决，促进下一代自适应无线网络的跨层设计规则的研究和开发，并弥合无线通信理论中的一些知识空白。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

On Private Server Implementations and Data Visualization for LoRaWAN

LoRaWAN 的私有服务器实现和数据可视化

• DOI: 10.1109/iscaie57739.2023.10165109
• 发表时间: 2023
• 期刊: IEEE
• 作者: Ahmed, Sheikh Tareq;Annamalai, Annamalai
• 通讯作者: Annamalai, Annamalai

Efficacy of CNN-Bidirectional LSTM Hybrid Model for Network-Based Anomaly Detection

• DOI: 10.1109/iscaie57739.2023.10165088
• 发表时间: 2023-05
• 期刊: 2023 IEEE 13th Symposium on Computer Applications & Industrial Electronics (ISCAIE)
• 作者: Toya Acharya;A. Annamalai;M. Chouikha

Improving Geo-Location Performance of LoRa with Adaptive Spreading Factor

利用自适应扩频因子提高 LoRa 的地理位置性能

• DOI: 10.1109/iscaie57739.2023.10165296
• 发表时间: 2023
• 期刊: IEEE
• 作者: Ahmed, Sheikh Tareq;Annamalai, Annamalai
• 通讯作者: Annamalai, Annamalai

Efficacy of Bidirectional LSTM Model for Network-Based Anomaly Detection

用于基于网络的异常检测的双向 LSTM 模型的功效

• DOI: 10.1109/iscaie57739.2023.10165336
• 发表时间: 2023
• 期刊: IEEE
• 作者: Acharya, Toya;Annamalai, Annamalai;Chouikha, Mohamed F
• 通讯作者: Chouikha, Mohamed F