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arXiv 1203.0695cs.ITmath.IT
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协同计算转发

Cooperative Compute-and-Forward

Matthew Nokleby, Behnaam Aazhang

摘要:

我们研究了在计算和转发下用户合作的好处。与网络编码非常相似,计算转发网络中的接收器恢复发射器消息的有限域线性组合。恢复是通过线性码实现的:发射机将消息映射到线性码本,接收机尝试将输入的信号叠加解码为码字的整数组合。然而,如果信道增益不对应于合适的线性组合,则可实现的计算速率低。为了应对这一挑战,我们提出了一个合作的方法来计算和转发。我们设计了一个格编码的方法来块马尔可夫编码,我们构建了一个解码和转发风格的计算策略。发送器广播格形码字,解码彼此的消息,然后协作地发送分辨率信息以帮助接收器解码整数组合。使用我们的策略,我们表明,合作提供了一个显着的改善,在可实现的计算速率和多样性复用的权衡。

英文摘要:

We examine the benefits of user cooperation under compute-and-forward. Much like in network coding, receivers in a compute-and-forward network recover finite-field linear combinations of transmitters' messages. Recovery is enabled by linear codes: transmitters map messages to a linear codebook, and receivers attempt to decode the incoming superposition of signals to an integer combination of codewords. However, the achievable computation rates are low if channel gains do not correspond to a suitable linear combination. In response to this challenge, we propose a cooperative approach to compute-and-forward. We devise a lattice-coding approach to block Markov encoding with which we construct a decode-and-forward style computation strategy. Transmitters broadcast lattice codewords, decode each other's messages, and then cooperatively transmit resolution information to aid receivers in decoding the integer combinations. Using our strategy, we show that cooperation offers a significant improvement both in the achievable computation rate and in the diversity-multiplexing tradeoff.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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