The cost of uncorrelation and non-cooperation in MIMO channels

T. Philosof, R. Zamir
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引用次数: 7

Abstract

We investigate the sum-capacity loss for using uncorrelated Gaussian inputs over multiple-input multiple-output (MIMO) power-constrained linear additive-noise channels in multi-user configurations. We show that the sum-capacity loss is bounded by a universal constant which depends only on the total number of input and output dimensions of the channel, but is independent of the channel matrix, the noise distribution and the number of users. Specifically, for a multiple-access channel with a total number of nt transmit antennas and base-station with nr receive antennas, the sum-capacity loss is at most C* = min{1/2, nr/2nt log2(1 + nt/nr)} bit per input dimension (or 1 bit per transmit antenna per second per Hertz). If we restrict attention to Gaussian noises, then the capacity loss is upper bounded by CG* = min{0.265, 0.265nr/nt log2(nt/nr)}, and this bound is tight for certain channel matrices and noise spectra. We show also that the same bounds hold for the sum-capacity loss of uncorrelated Gaussian input over linear MIMO broadcast channels, input distribution being interpreted either in terms of the equivalent point-to-point channel with Sato condition, or as the output distribution of a "dirty-paper" transmitter. One implication of these results is the limited value of coherence and water-filling in spatial transmission. Another implication is the limited capacity loss in multi-user configurations relative to the fully cooperative (point-to-point) channel
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MIMO信道中不相关和不合作的代价
我们研究了在多用户配置的多输入多输出(MIMO)功率约束线性加性噪声信道上使用不相关高斯输入的和容量损失。我们证明了总容量损失由一个通用常数限定,该常数仅取决于信道的输入和输出维数的总数,但与信道矩阵、噪声分布和用户数量无关。具体来说,对于一个发射天线总数为nt、接收天线总数为nr的多址信道,每个输入维的总容量损失不超过C* = min{1/2, nr/2nt log2(1 + nt/nr)}比特(或每秒每赫兹每个发射天线1比特)。如果我们将注意力限制在高斯噪声上,则容量损失的上界为CG* = min{0.265, 0.265nr/nt log2(nt/nr)},并且该上界对于某些信道矩阵和噪声谱是紧的。我们还表明,对于线性MIMO广播信道上不相关高斯输入的和容量损失,输入分布可以用等效的点对点信道和Sato条件来解释,或者作为“脏纸”发射机的输出分布。这些结果的一个含义是相干性和充水在空间传输中的有限价值。另一个含义是,相对于完全协作(点对点)信道,多用户配置中的容量损失有限
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