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满速率满分集优化的单频网发射信号
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作者 沈莹 唐友喜 《电子科技大学学报》 EI CAS CSCD 北大核心 2010年第5期676-679,705,共5页
针对分布式发射天线单频网,设计了3种发射信号及针对第一种发射信号的优化方案。首先通过误对概率分析,推导出满速率单频网能获得的分集度,设计了一种能达到该分集度的发射信号和具有满分集度的2种发射信号。然后针对第一种发射信号,提... 针对分布式发射天线单频网,设计了3种发射信号及针对第一种发射信号的优化方案。首先通过误对概率分析,推导出满速率单频网能获得的分集度,设计了一种能达到该分集度的发射信号和具有满分集度的2种发射信号。然后针对第一种发射信号,提出了基于异步时延的子载波交织分组的信号优化方法,在接收机位置与性能之间建立了一种折中关系。仿真结果表明,设计的满分集发射信号能获得8dB左右增益,优化后的发射信号能获得5~9dB增益。 展开更多
关键词 异步时延 分集度 误对概率 单频网
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JOINT LLR-CRC ERROR MITIGATION FOR TWO-WAY ADAPTIVE DENOISE-AND-FORWARD NETWORK CODING
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作者 Cheng Yulun Yang Longxiang 《Journal of Electronics(China)》 2013年第4期352-361,共10页
Network Coding (NC) brings correlation between the coded signals from different sources, which makes the system more vulnerable to the decode error at relay. Conventional Cyclic Redundancy Code (CRC) has been implemen... Network Coding (NC) brings correlation between the coded signals from different sources, which makes the system more vulnerable to the decode error at relay. Conventional Cyclic Redundancy Code (CRC) has been implemented for error bit detection. However, its error correction is simply ignored. To fully exploit this feature, this paper proposes a novel joint Log-Likelihood Ratio (LLR) CRC error mitigation for NC two way relay channel. Specific thresholds are designed to estimate the error number of data block and identify those which can be recovered if the number is within the error correction scope of CRC. We examine two modes of the thresholds, one based on the average Bit Error Rate (BER) of source-relay link, while the other based on that of instantaneous one. We provide the full analysis for the Pair-wise Error Probability (PEP) performance of the scheme. A variety of numerical results are presented to reveal the superiority of the proposed scheme to conventional CRC NC under independent Rayleigh fading channels. Moreover, the efficiencies of the proposed thresholds are also validated. 展开更多
关键词 Network Coding (NC) Log-Likelihood Ratio (LLR) Cyclic Redundancy Code (CRC) Denoise-and-forward Pair-wise Error Probability (PEP)
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