Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering
Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering
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DOI：
10.1109/isit.2000.866569
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发表时间：
2000-09
期刊：
影响因子：
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通讯作者：
Rong Chen;Xiaodong Wang;Jun S. Liu
中科院分区：
文献类型：
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作者：
Rong Chen;Xiaodong Wang;Jun S. Liu
基于序贯蒙特卡罗方法，提出了一种新的用于平坦衰落信道中信号检测的自适应贝叶斯接收机。其基本思想是将传输的信号视为缺失数据，并根据观察到的信号依次估算它们的多个副本。估算的信号序列，连同它们的重要性权重，提供了一种方法来近似的贝叶斯估计的发送信号和信道状态。仿真结果表明，该接收机在衰落信道中不需要任何训练/导频符号或判决反馈就能获得接近极限的性能。此外，建议的接收器结构具有巨大的并行性，非常适合于高速并行实现使用的VLSI脉动阵列技术。
A novel adaptive Bayesian receiver for signal detection in flat-fading channels is developed based on the sequential Monte Carlo methodology. The basic idea is to treat the transmitted signals as missing data and to sequentially impute multiple copies of them based on the observed signals. The imputed signal sequences, together with their importance weights, provide a way to approximate the Bayesian estimate of the transmitted signals and the channel states. It is shown through simulations that the proposed sequential Monte Carlo receivers achieve near-bound performance in fading channels without the aid of any training/pilot symbols or decision feedback. Moreover, the proposed receiver structure exhibits massive parallelism and is ideally suited for high-speed parallel implementation using the VLSI systolic array technology.