新型自适应非高斯接收机设计

New adaptive receiver for channels with non-Gaussian noise

为了解决低频非高斯噪声信道下的信号传输问题,提出了一种新型的自适应接收机设计。通过设计马尔科夫链蒙特卡罗(MCMC)算法,并采用训练序列估计信道衰减系数和噪声模型参数,进而对信号进行检测。非高斯噪声模型选用了应用广泛的α稳定分布和高斯分布的混合模型。仿真结果表明:本文设计的自适应接收机能够逼近已知信道参数条件下的最优接收机的性能。

In order to detect signals in low frequency channels with non-Gaussian noise, a novel adaptive receiver is developed. A Markov Chain Monte Carlo （MCMC） algorithm is proposed to estimate the fading coefficients and the noise model parameters simultaneously using the training sequence; then the signal is estimated by the optimal decision rule. A commonly used model, which mixes the symmetric a distribution and the Gaussian distribution, is used to model the noise. Simulation results show that the performance of proposed adaptive receiver can approach that of the optimal receiver with known channel model parameters.