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arXiv 1005.0167cs.ITmath.IT
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高斯中继和干扰网络的数字接口:离散叠加模型的提升码

A digital interface for Gaussian relay and interference networks: Lifting codes from the discrete superposition model

M. Anand, P. R. Kumar

摘要:

对于每个高斯网络,都存在一个对应的确定性网络,称为离散叠加网络。我们表明,这种离散叠加网络提供了一个接近最佳的数字接口,用于操作一个由许多高斯网络组成的类,在这个意义上,任何代码的离散叠加网络可以自然地提升到相应的代码的高斯网络,同时实现的速率是不超过一个恒定的比特数小于它实现的离散叠加网络的速率。该常数仅取决于网络中的节点数量,而不取决于信道增益或SNR。此外,这两个网络的容量在彼此的常数内,再次独立于信道增益和SNR。我们表明,这类接口属性的高斯网络,包括中继网络与一个单一的源-目的地对,干扰网络,组播网络,以及这些网络的多个发射和接收天线的同行。高斯中继网络的代码可以从任何离散叠加网络的代码中简单地通过修剪它来获得。这种提升方案建立了叠加模型确实可以潜在地作为高斯中继网络设计代码的强代理。我们提出了类似的结果为K × K高斯干扰网络,MIMO高斯干扰网络,MIMO高斯中继网络,和多播网络,与恒定的间隙取决于天线的数量在MIMO网络的情况下。

英文摘要:

For every Gaussian network, there exists a corresponding deterministic network called the discrete superposition network. We show that this discrete superposition network provides a near-optimal digital interface for operating a class consisting of many Gaussian networks in the sense that any code for the discrete superposition network can be naturally lifted to a corresponding code for the Gaussian network, while achieving a rate that is no more than a constant number of bits lesser than the rate it achieves for the discrete superposition network. This constant depends only on the number of nodes in the network and not on the channel gains or SNR. Moreover the capacities of the two networks are within a constant of each other, again independent of channel gains and SNR. We show that the class of Gaussian networks for which this interface property holds includes relay networks with a single source-destination pair, interference networks, multicast networks, and the counterparts of these networks with multiple transmit and receive antennas. The code for the Gaussian relay network can be obtained from any code for the discrete superposition network simply by pruning it. This lifting scheme establishes that the superposition model can indeed potentially serve as a strong surrogate for designing codes for Gaussian relay networks. We present similar results for the K x K Gaussian interference network, MIMO Gaussian interference networks, MIMO Gaussian relay networks, and multicast networks, with the constant gap depending additionally on the number of antennas in case of MIMO networks.

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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