Computationally Efficient Joint Demodulation For Sensor Arrays

传感器阵列的计算高效联合解调

• 批准号: 0003284
• 负责人: William Gardner
• 金额: $ 10万
• 依托单位: Statistical Signal Processing Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2002-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0003284&HistoricalAwards=false
• 关键词: Computationally; Efficient; Joint; Demodulation; Sensor

Computationally Efficient Joint Demodulation for Sensor ArraysAbstractThe objective of the proposed research is to realize order-of-magnitude improvements in the interference mitigation capability of an antenna array with its associated multi-channel digital signal processing algorithms, compared with performance presently attainable using conventional linear processing. The motivating commercial applications include high-capacity cellular telephony, personal communications systems, and wireless local area networks. Such huge increases in interference mitigation capability translate to similar magnitude increases in system capacity. With no end in sight to the accelerating demands on communications capacity, the commercial value of a breakthrough of this type would be tremendous. The signal processing method being investigated is joint demodulation of multiple signals using a multichannel Viterbi algorithm modified to trade signal quality for computational cost. The goals are to 1) characterize the number of interfering signals that can be separated and 2) characterize the degree of reduction in complexity of the Virterbi algorithm that can be realized while maintaining acceptable bit-error-rate, both as functions of the number of antenna elements in the array, and parameterized by signal-to-noise ratio. The interference environments simulated model cellular telephone channels with GSM and/or IS-136 signaling.

计算高效的传感器阵列联合解调提出的研究的目的是实现天线阵列及其相关的多通道数字信号处理算法的干扰抑制能力的数量级改进，与目前使用传统的线性处理所获得的性能相比。推动商业应用的领域包括大容量蜂窝电话、个人通信系统和无线局域网。干扰抑制能力的如此巨大的增加转化为系统容量的类似幅度的增加。在对通信容量不断增长的需求看不到尽头的情况下，这种突破的商业价值将是巨大的。正在研究的信号处理方法是使用改进的多通道维特比算法对多个信号进行联合解调，以牺牲信号质量来换取计算成本。目标是1)表征可分离的干扰信号的数量，以及2)表征Virterbi算法的复杂度的降低程度，该程度可以在保持可接受的误码率的同时实现，这既是阵列中天线单元数量的函数，也是通过信噪比来参数化的。模拟的干扰环境模拟具有GSM和/或IS-136信令的蜂窝电话信道。