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Uplink Oblivious Cloud Radio Access Networks: An Information Theoretic Overview

机译:上行漏窃云无线电接入网络:信息理论概述

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In this work, we consider transmission over a Cloud Radio Access Network (CRAN) in which the relay nodes (radio units) are constrained to operate without knowledge of the users' codebooks, i.e., are oblivious (nomadic), and only know time- or frequency-sharing protocols. The model is shown in Figure 1. Focusing on a class of discrete memoryless channels in which the relay outputs are independent conditionally on the users' inputs, we establish a single-letter characterization of the capacity region of this class of channels. We show that both relaying à-la Cover-El Gamal [1], i.e., compress-and-forward with joint decompression and decoding, as suggested in [2], are optimal. This is equivalent to noisy notwork coding [3]. For the proof of the converse part, we utilize useful connections with the Chief Executive Officer (CEO) source coding problem under logarithmic loss distortion measure [4]. For memoryless Gaussian channels, we provide a full characterization of the capacity region under Gaussian signaling, i.e., when the users' channel inputs are restricted to be Gaussian. In doing so, we also discuss the suboptimality of separate decompression-decoding and the role of time-sharing. Furthermore, we elaborate on meaningful connections with the problem of distributed information bottleneck problem [5]-[7]. Finally, we evaluate and compare the performance of some oblivious, including the recent scheme [8], and non-oblivious schemes, such as [9] and [10], and cut-set bounds.
机译:在这项工作中,我们考虑通过云无线电接入网络(CRAN)的传输,其中继电器节点(无线电单位)被约束以在不了解用户的码本的情况下进行操作,即,是令人沮丧的(游牧的),并且只知道时间 - 或频率共享协议。该模型如图1所示。专注于中继输出在用户输入上有条件独立的离散记忆信道,我们建立了这类通道的容量区域的单字母表征。我们表明,如[2]所示,中继à-la封面-eL gamal [1],即压缩和向前的压缩和转发,是最佳的。这相当于嘈杂的不当编码[3]。对于匡威的证明,我们利用与行政总裁(CEO)源编码问题的有用联系在对数损耗失真测量下[4]。对于记忆高斯通道,我们在高斯信令下的容量区域提供了完全表征,即,当用户的通道输入仅限于高斯时,即可。在这样做时,我们还讨论了单独的减压解码和时间共享的角色的子项优。此外,我们详细说明了与分布式信息瓶颈问题的问题有意义的联系[5] - [7]。最后,我们评估并比较一些令人沮丧的性能,包括最近的方案[8]和非倾向的方案,例如[9]和[10]和切割界限。

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