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首页> 外文期刊>IEEE Transactions on Signal Processing >Krylov Subspace Algorithms and Circulant-Embedding Method for Efficient Wideband Single-Carrier Equalization
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Krylov Subspace Algorithms and Circulant-Embedding Method for Efficient Wideband Single-Carrier Equalization

机译:有效宽带单载波均衡的Krylov子空间算法和循环嵌入方法

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Wider bandwidth allows higher data rate by transmitting narrower pulses. However, doing so would also increase the discrete channel memory length. For single-carrier communication systems this results in higher computational burden at the receiver. We are concerned with single-carrier nonblock transmission schemes with receiver oversampling, as they can provide higher spectral efficiency than block transmission schemes in the presence of large delay spreads. We first propose a simple finite-impulse-response (FIR) equalizer that is based on the circulant-embedding (CE) method and analyze its performance by investigating the relationship between solutions of various finite-dimensional models and the original infinite-dimensional problem. We show that under proper conditions the CE FIR equalizer converges exponentially fast to the IIR equalizer. We then focus on the conjugate gradient (CG) algorithm as an efficient means for equalization that is specifically well suited for dealing with large-delay-spread channels. We discuss the importance of stopping the iterations for the CG algorithm at the right time in the presence of noise and present several reliable low-cost stopping criteria. It turns out that the CG algorithm equipped with appropriate stopping criteria can outperform MMSE equalizers. Since both the CE and the CG methods can be efficiently implemented via fast Fourier transforms, equalization complexity is only in the order of $Nlog(N)$ for $N$ data symbols. Several numerical experiments demonstrate the performance of the proposed methods.
机译:较宽的带宽可通过传输较窄的脉冲来实现较高的数据速率。但是,这样做也会增加离散通道存储器的长度。对于单载波通信系统,这导致接收机处的计算负担更大。我们关注具有接收器过采样的单载波非块传输方案,因为在存在较大延迟扩展的情况下,它们可以提供比块传输方案更高的频谱效率。我们首先提出一种基于循环嵌入(CE)方法的简单有限冲激响应(FIR)均衡器,并通过研究各种有限维模型的解与原始无限维问题之间的关系来分析其性能。我们表明,在适当的条件下,CE FIR均衡器快速指数收敛到IIR均衡器。然后,我们将重点放在共轭梯度(CG)算法上,将其作为一种有效的均衡方法,特别适合处理大延迟扩展信道。我们讨论了在有噪声的情况下在正确的时间停止CG算法迭代的重要性,并提出了几种可靠的低成本停止准则。事实证明,配备适当停止准则的CG算法可以胜过MMSE均衡器。由于可以通过快速傅立叶变换有效地实现CE和CG方法,因此对于$ N $数据符号,均衡复杂度仅为$ Nlog(N)$。几个数值实验证明了所提出方法的性能。

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