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Energy Efficiency of Uplink and Downlink Non-Orthogonal Multiple-Access Channels Under Gaussian-Mixture Interference

机译:高斯混合干扰下的上行链路和下行链路非正交多通道信道的能量效率

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摘要

In this paper, we analyze the energy efficiency (EE) of uplink and downlink non-orthogonal multiple access (NOMA) channels with successive interference cancellation under Gaussian-mixture aggregate interference. The adopted non-Gaussian model is a realistic noise plus interference model to capture the asynchronism in a heterogeneous cellular network. The considered EE is measured via the minimum energy per bit $rac {E_{b}}{N_{0}}_{min }$ for reliable communication and the wideband slope of the spectral efficiency as a function of energy per bit $rac {E_{b}}{N_{0}}$ . For completeness, both Gaussian signaling schemes and practical finite alphabet inputs are examined. To this end, our approach is to calculate $rac {E_{b}}{N_{0}}_{min }$ and the wideband slope region via the Kullback-Leibler divergence. Due to the presence of mixture of multiple Gaussian distributions, the Kullback-Leibler divergence cannot be expressed in closed-form. As an alternative, we exploit upper bounds on the divergence, and we show that the bounds are achievable at the limit points, i.e., when the signal-to-noise-ratio (SNR) approaches zero. As a result, $rac {E_{b}}{N_{0}}_{min }$ of each user can be established in closed-form. Next, we apply Taylor series expressions and exploit the achievability in the previous step to evaluate the second derivative of the rates when SNR goes to zero. It is then shown that the wideband slope region can be found effectively. The proposed method can serve as an important tool for making more accurate throughput and EE evaluation of important wireless/cellular networks.
机译:在本文中,我们在高斯 - 混合聚合干扰下分析上行链路和下行链路非正交多址(NOMA)信道的能量效率(EE)。采用的非高斯模型是一种现实噪声加干扰模型,用于捕获异步蜂窝网络中的异步。考虑的ee通过每位的最小能量测量<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ frac {e_ {b}} {n_ {0}} _ { min} $ 对于可靠的通信和光谱效率的宽带斜率作为每位能量的函数<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ FRAC {e__ {b}} $ 。为了完整性,检查高斯信令方案和实际有限字母输入。为此,我们的方法是计算<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ frac {e_ {b}} {n_ {0}} _ { min} $ 通过Kullback-Leibler发散的宽带倾斜区域。由于存在多个高斯分布的混合物,不能以闭合形式表达Kullback-Leibler发散。作为替代方案,我们利用了发散的上限,并且我们表明,当信噪比(SNR)接近零时,界限可在极限点处实现。因此,<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ frac {e_ {b}} {n_ {0}} _ { min} $ 每个用户都可以以封闭形式建立。接下来,我们应用Taylor系列表达并利用上一步中的可实现性,以评估SNR零时的速率的第二导数。然后示出了可以有效地发现宽带倾斜区域。该方法可以作为制定更准确的吞吐量和重要无线/蜂窝网络评估的重要工具。

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