CIF: Small: Signal Processing for Multi-user Communications under Finite Alphabet Constraints

CIF：小：有限字母表约束下的多用户通信信号处理

• 批准号: 0915846
• 负责人: Chengshan Xiao
• 金额: $ 23.83万
• 依托单位: Missouri University of Science and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915846&HistoricalAwards=false
• 关键词: CIF; Small; Signal; Processing; Multi

Abstract for NSF Proposal #0915846Abstract: Channel capacity and mutual information have been studied extensively for various types of wire-line and wireless multi-user communication channels. Among the vast information theoretic literature, most of the results are based on the assumption that the channel inputs are Gaussian distributed. However, Gaussian inputs can never be realized in practical systems. The inputs are usually taken from finite alphabets, which can significantly depart from Gaussian distribution. A large nonlinear gap exists between the theoretical capacity and practical achievable rate. This nonlinear gap indicates that Gaussian-input assumption may not provide a realistic design guideline to practical systems. Maximizing mutual information over channels with finite alphabet inputs will benefit not only bandwidth efficiency but also bit error rate performance. However, much less work has been done for this important topic. This is mainly due to lack of closed-form solution and high computational complexity.The project investigates the direct maximization of mutual information and throughput over multi-user channels with finite alphabet inputs. The computational complexity problem is tackled by developing mathematically tractable and practically accurate algorithms via employing graph-based message-passing techniques. Shaping matrices are introduced to the maximization of mutual information. Parameterized approaches are developed to solve optimal shaping matrices which lead to the global maxima of the mutual information. Research efforts focus on multiple access channels, broadcast channels and interference channels, which are the fundamental channel scenarios of multi-user communications. The channel state information and/or channel covariance information are made available to the transmitter and receiver for the maximization of mutual information. Both frequency-flat fading and frequency-selective fading channels are explored.

摘要：对各种类型的有线和无线多用户通信信道的信道容量和互信息进行了广泛的研究。在大量的信息论文献中，大多数结果都是基于信道输入是高斯分布的假设。然而，在实际系统中，高斯输入永远无法实现。输入通常取自有限的字母，这可能明显偏离高斯分布。理论容量与实际可达速率之间存在较大的非线性差距。这种非线性间隙表明高斯输入假设可能不能为实际系统提供现实的设计指导。在有限字母输入的信道上最大化互信息不仅有利于带宽效率，而且有利于误码率性能。然而，关于这一重要主题的工作却少得多。这主要是由于缺乏封闭解和计算复杂度高。该项目研究了在有限字母输入的多用户信道上相互信息和吞吐量的直接最大化。通过采用基于图的消息传递技术，开发数学上易于处理且实际准确的算法来解决计算复杂性问题。将整形矩阵引入到互信息的最大化中。采用参数化方法求解最优成形矩阵，使互信息达到全局最大值。多址信道、广播信道和干扰信道是多用户通信的基本信道场景。信道状态信息和/或信道协方差信息可供发射机和接收机使用，以使互信息最大化。研究了频率平坦衰落和频率选择性衰落信道。