Collaborative Research: Practical Signal Design for Interference Management in Wireless Communication Networks

干扰管理是满足爆炸性无线数据通信需求的瓶颈。增加蜂窝或Wi-Fi网络容量的主要方法是增加基站/接入点密度，这会由于较短距离处的散射体较少而导致来自不需要的发射机的更多干扰。提出的研究通过用户之间的联合传输信号设计来解决干扰问题，从而在最大化数据链路自身速率和减少对其他链路的干扰之间取得最佳平衡。目标是实现最大数据速率。为了使研究与现实世界的系统更相关，该团队采取了联合算法和硬件设计的跨学科方法，并考虑了实际限制。因此，研究成果有望显著提高下一代无线通信系统的容量。该项目还为信号处理和嵌入式系统领域的研究生和本科生提供了一个独特的培养机会。本研究试图通过理论研究、分布式优化算法和高效的硬件设计来解决干扰信道加权和速率最大化的优化问题。这项研究的变革性在于，它采用了联合算法和硬件设计的跨学科方法，利用了最近的最优信号结构结果，并考虑了许多实际约束。PI的团队最近发现，最佳信号具有礼貌的充水结构，这类似于著名的无限信噪比干扰对齐，每个用户都可以享受一半的资源。礼貌注水算法适用于所有信噪比范围，并在充分了解信道知识和集中优化的理想假设下，设计了最有效的算法。在实际应用的限制下，设计和分析变得更具挑战性。PI将采取理论、设计、仿真和实验的整体方法，并实际考虑分布式优化、分布式信道估计、部分信道知识、量化噪声、硬件处理延迟和功耗。该项目的成果包括实用的算法、性能分析和高效的硬件架构，可作为未来无线通信系统中干扰管理的蓝图。

Interference management is the bottleneck of meeting the explosive wireless data communication demand. The primary method of increasing cellular or Wi-Fi network capacity is to increase base station/access-point density, which leads to more interference from undesired transmitters due to less scatterers at shorter distance. The proposed research attacks the interference problem through joint transmit signal design among users such that it strikes an optimal balance between maximizing a data link's own rate and reducing interference to other links. The objective is to achieve maximal data rates. To make the research more relevant to real-world systems, the team takes an interdisciplinary approach of joint algorithm and hardware design with the consideration of practical constraints. Consequently, the research results are expected to significantly improve the capacity of next generation wireless communication systems. The project also provides a unique opportunity to train both graduate and undergraduate students at the intersection of signal processing and embedded system fields.The proposed research attempts to solve the optimization problem of maximizing weighted sum-rate for interference channels by research on theory, distributed optimization algorithms, and efficient hardware design. The transformative nature of this research lies in that it adopts an interdisciplinary approach of joint algorithm and hardware design, takes advantage of recent optimal signal structure result, as well as considers many practical constraints. The PI's group recently discovered that the optimal signals have a polite water-filling structure, which is analogous to the celebrated interference alignment for infinite SNR where every user can enjoy half of the resource. The polite water-filling works for all SNR range and by exploiting it, the most efficient algorithms have been designed under the ideal assumptions of full channel knowledge and centralized optimization. Under practical constraints, the design and analysis become much more challenging. The PIs will take a holistic approach of theory, design, simulation, and experiments with practical consideration of distributed optimization, distributed channel estimation, partial channel knowledge, quantization noise, hardware processing latency, and power consumption. The outcome of the project includes practical algorithms, performance analysis, and efficient hardware architectures that can serve as a blueprint for interference management in future wireless communication systems.