Interacting Multiple Model Based Detector to Compensate Power Amplifier Distortions in Cognitive Radio
Interacting Multiple Model Based Detector to Compensate Power Amplifier Distortions in Cognitive Radio
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DOI：
10.1109/tcomm.2015.2417552
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发表时间：
2015-03
影响因子：
8.3
通讯作者：
Mouna Ben Mabrouk;G. Ferré;É. Grivel;N. Deltimple
中科院分区：
文献类型：
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作者：
Mouna Ben Mabrouk;G. Ferré;É. Grivel;N. Deltimple
对于电池驱动的终端，必须优化功率放大器（PA）效率。因此，在传输链中的PA输出端可能出现非线性。为了补偿这些失真，一种解决方案包括使用基于PA和信道两者的沃尔泰拉模型的数字检测器和基于卡尔曼滤波器（KF）的算法来联合估计沃尔泰拉内核和所发送的符号。在这里，我们建议在处理认知无线电（CR）时解决这个问题。在这种情况下，必须考虑其他约束。由于CR端子可以从一个子带切换到另一个子带，因此PA非线性可以随时间变化。因此，我们建议设计一个数字检测器的基础上相互作用的多个模型结合各种基于KF的估计，使用不同的模型参数动态。这使得有可能跟踪沃尔泰拉内核的时间变化，同时保持准确的估计时，这些参数是静态的。此外，单载波和多载波的情况下，解决和仿真结果验证。我们的解决方案对应于计算成本和误码率性能之间的妥协。
For a battery driven terminal, the power amplifier (PA) efficiency must be optimized. Consequently, non-linearities may appear at the PA output in the transmission chain. To compensate these distortions, one solution consists of using a digital detector based on a Volterra model of both the PA and the channel and a Kalman filter (KF) based algorithm to jointly estimate the Volterra kernels and the transmitted symbols. Here, we suggest addressing this issue when dealing with cognitive radio (CR). In this case, additional constraints must be taken into account. Since the CR terminal may switch from one sub-band to another, the PA non-linearities may vary over time. Therefore, we propose to design a digital detector based on an interacting multiple model combining various KF based estimators using different model parameter dynamics. This makes it possible to track the time variations of the Volterra kernels while keeping accurate estimates when those parameters are static. Furthermore, the single and multicarrier cases are addressed and validated by simulation results. Our solution corresponds to a compromise between computational cost and bit-error-rate performance.