Intelligent signal processing for ubiquitous high-capacity, heterogeneous, scalable wireless networks

新兴的无线通信网络正在实现从关键基础设施保护和安全到环境监测、医疗保健和生活质量的各种应用。各种类型的当前和新兴的无线网络架构包括蜂窝网络、无线局域网、无线自组织网络、无线个域网和全球微波接入互操作性（WiMAX）系统。此外，预计未来的第四代无线电接入将提供高达100 Mb/s的广域覆盖数据速率和高达1 Gb/s的局域覆盖数据速率，这可以通过使用复杂和计算能力强的收发器来实现。经典的通信理论是基于一个竞争的框架，其中不同的用户和应用程序竞争资源，如带宽和功率。然而，最近的研究表明，合作策略可以显着提高无线网络的整体容量。这些策略利用了直观的概念，即中间节点可以帮助源节点和目的节点之间的数据传输，并促进低成本的虚拟多输入多输出（MIMO）系统的实现。协作网络需要开发适当的信道和频率估计方法、实用的编码和解码技术、波束成形和MIMO正交频分复用技术。因此，我们的主要重点是智能信号处理技术的合作网络的发展。我们将利用鲁棒波束形成，现代编码理论，空时信号处理和合作策略的最新进展，显着提高吞吐量，可扩展性，可靠性和性能的合作无线网络。因此，成功的项目成果将实现具有端到端宽带能力的高容量、无处不在的无线网络基础设施。此外，这些成果还将提高这些无线网络的可靠性、效率和可扩展性。

Emerging wireless communication networks are enabling a variety of applications ranging from critical infrastructure protection and security, to environment monitoring, health care and quality of life. Various types of current and emerging wireless network architectures include cellular networks, wireless local area networks, wireless ad hoc networks, wireless personal area networks, and Worldwide Interoperability for Microwave Access (WiMAX) systems. Moreover, future fourth-generation radio access is anticipated to provide data rates up to 100 Mb/s with wide-area coverage and up to 1 Gb/s with local-area coverage that can be achieved by using sophisticated and computationally powerful transceivers. Classical communication theory is based on a competitive framework in which different users and applications compete for resources such as bandwidth and power. However, recent research has demonstrated that cooperative strategies can significantly improve the overall capacity of wireless networks. These strategies exploit the intuitive notion that intermediate nodes can assist data transmission between the source and the destination nodes and facilitate the realization of low-cost virtual multiple-input multiple-output (MIMO) systems. Cooperative networks require the development of appropriate channel and frequency estimation methods, practical coding and decoding techniques, beamforming, and MIMO orthogonal frequency division multiplexing techniques. Our main focus is therefore on the development of intelligent signal processing techniques for cooperative networks. We will utilize recent advances in robust beamforming, modern coding theory, space-time signal processing, and cooperative strategies to significantly improve the throughput, scalability, reliability and performance of cooperative wireless networks. The successful project outcomes will thus enable high capacity, ubiquitous wireless network infrastructures with end-to-end broadband capability. Moreover, these outcomes will also improve the reliability, efficiency, and scalability of these wireless networks.