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arXiv 1111.0727cs.ITmath.IT
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基于结构化信令的全双工多跳网络自干扰消除

Self-Interference Cancellation in Multi-hop Full-Duplex Networks via Structured Signaling

Evan Everett, Debashis Dash, Chris Dick, Ashutosh Sabharawal

摘要:

本文讨论了在多跳无线网络中,节点采用全双工通信方式时,处理自干扰问题的传输策略。对最简单的这种多跳网络:两跳源-中继-目的地网络的信息理论研究导致了一种称为结构化自干扰消除(或简称“结构化消除”)的新传输策略。在结构化消除策略中,源抑制在某些信号电平上进行发送,并且中继器结构化其发送信号,使得其可以通过观察其自己的发送信号的出现在源留下的空信号电平处的部分来学习残余自干扰信道,并且消除自干扰。结果表明,在某些非平凡的制度,结构化的消除策略优于不仅半双工,但也全双工计划中,时间正交训练用于估计残留的自干扰信道。

英文摘要:

This paper discusses transmission strategies for dealing with the problem of self-interference in multi-hop wireless networks in which the nodes communicate in a full- duplex mode. An information theoretic study of the simplest such multi-hop network: the two-hop source-relay-destination network, leads to a novel transmission strategy called structured self-interference cancellation (or just "structured cancellation" for short). In the structured cancellation strategy the source restrains from transmitting on certain signal levels, and the relay structures its transmit signal such that it can learn the residual self-interference channel, and undo the self-interference, by observing the portion of its own transmit signal that appears at the signal levels left empty by the source. It is shown that in certain nontrivial regimes, the structured cancellation strategy outperforms not only half-duplex but also full-duplex schemes in which time-orthogonal training is used for estimating the residual self-interference channel.

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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