摘要: |
面对宽带移动卫星通信中信道占用呈现的稀疏状态和时而存在的稀疏干扰,以低速率
采样和运算是简化设备的必要途径。针对宽带频谱范围内稀疏信道信号和干扰信号的检测,
提出了一种用于直接估计频谱空穴的压缩采样算法,以低速率对信号进行采样,通过相
关向量机进行迭代优化,给出检测估计值。该算法基于最大似然贝叶斯估计,具有良好的抗
噪性能,同时能够降低设备复杂度。仿真结果表明,其抗噪性能明显好于CVX方法而略逊于理
想情况,而前端随机序列的相关性是影响检测性能的重要因素。 |
关键词: 卫星通信 认知无线电 频谱空穴 压缩采样 贝叶斯检测 相
关向量机 |
DOI: |
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基金项目: |
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A new scheme for detecting spectrum holes of sparse satellite channel |
CHEN Peng,XU Feng,QIU Le-de,WANG Yu |
() |
Abstract: |
Broadband satellite systems encounter occasionally sparse channel occu
pations and sparse interferences,so lowrate sampling and oper
a
tion is required. For detection of sparse signals and interferences among a wide
spectrum range,a compressive sampling(CS) scheme is proposed that can detect sp
ectr
um holes directly. Iterative optimization by a Relevance Vector Machine(RVM) is
appli
ed on subNyquist rate samples to produce the estimate. This scheme is based on
Maximum Likelihood(ML) Bayesian estimation, and features good antinoise perfor
mance and effective
d
evice complexity reduction. Simulation results show a better antinoise perform
a
nce over CVX method. And the relevance of the frontend pseudorandom sequences
is shown to have a large impact on the detection performance. |
Key words: satellite communication cognitive radio spectrum hole compressive sampling Ba
ye
sian detection relevance vector machine |