Jitter and error performance analysis of QPR-TCM and neural network equivalent systems over mobile satellite channels

O. Ucan
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Abstract

In this paper, to improve bandwidth efficiency and error performance, partial response signaling (PRS) and trellis coded modulation (TCM) are combined together and named as QPR-TCM. The emphasis in this paper is on the jitter and error performance of QPR-TCM and neural network equivalent models in the fading environment with ideal channel state information (CSI) and no side information exist on the phase noise process. Analytical upper bounds are derived using Chernoff bounding technique, combined with the modified generating functional approach. One interesting result is that the bit error probability upper bounds of the proposed scheme is better than 4QAM-TCM for SNR values greater than a threshold, which have the best error performance till now. Neural network models of QPR-TCM schemes are introduced for the first time in the literature for fading channels and the bit error event curves are derived using the back propagation algorithm. It is shown that neuro-computing results confirm the analytical approach.
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移动卫星信道上QPR-TCM和神经网络等效系统的抖动和误差性能分析
为了提高带宽效率和误差性能,本文将部分响应信令(PRS)和网格编码调制(TCM)结合在一起,命名为QPR-TCM。本文重点研究了QPR-TCM和神经网络等效模型在具有理想信道状态信息(CSI)和相位噪声过程中不存在侧信息的衰落环境下的抖动和误差性能。利用Chernoff边界技术,结合改进的生成泛函方法,导出了解析上界。一个有趣的结果是,在信噪比大于阈值的情况下,该方案的误码概率上界优于4QAM-TCM,是目前为止误码性能最好的方案。在文献中首次引入了衰落信道QPR-TCM方案的神经网络模型,并利用反向传播算法推导了误码事件曲线。神经计算结果证实了分析方法的正确性。
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