高斯信源下多中继网络的分布式压缩转发系统与优化设计

Compression Forward and Optimization of Multi-relay Networks for Gaussian Sources

提出了一种模拟高斯信源通过多中继网络进行压缩转发的系统模型,该系统模型可以描述实际中传感器受限于环境或成本,只能进行简单的模拟信号发送,而中继器能够进行复杂的分布式信源编码和信道编码的传感中继网络。本文提出了该系统的理论分析框架,对传感器网络的分布式信源编码问题,采用CEO理论建立多中继网络的率失真函数,结合Shannon信道容量理论,将传感器网络与数字通信网络建立联系。本文提出了系统的优化设计理论方法,在总功率受限条件下,在传感器网络和通信网络之间进行功率分配,使信噪比性能达到最大。理论分析和仿真结果表明,本文提出的方法比模拟中继转发系统在低信噪比区域抗干扰性能更好。在高信噪比区域,随着总信噪比约束的增大,可提高至10dB以上。

A new relay quantization scheme based on Gaussian sources is proposed,This model is applicable for the following system,the sensor can only simply send analog signals,and relays can provide distributed source encoding and channel encoding,the microwave radars and acoustic radars,etc.A theoretical analysis framework of the system is presented.The rate distortion function of the sensor network is established using chief executive officer（CEO）theory,and then we use the Shannon channel capacity theory to establish the connection between the sensor network and the digital communication network.The optimization design method of the system is proposed.Power allocation between the sensor network and the communication network is achieved to make the SNR performance reach the maximum under the condition of total power constraint.Theoretical analysis and simulation results show that the performance of the proposed method is much better than that of the analog amplify and forward.