異構(gòu)蜂窩網(wǎng)絡(luò)中基于能效的非正交多址接入下行功率分配算法

張雙; 康桂霞

doi:10.11999/JEIT190492

異構(gòu)蜂窩網(wǎng)絡(luò)中基于能效的非正交多址接入下行功率分配算法

doi: 10.11999/JEIT190492 cstr: 32379.14.JEIT190492

張雙,
康桂霞^,

1.
河北師范大學(xué)職業(yè)技術(shù)學(xué)院石家莊 050024
2.
北京郵電大學(xué)信息與通信工程學(xué)院北京 100876
3.
無錫北郵感知技術(shù)產(chǎn)業(yè)研究院無錫 214000

基金項(xiàng)目: 國家重大專項(xiàng)(2017ZX03001022)

詳細(xì)信息

作者簡介:
張雙：女，1989年生，博士生，研究方向?yàn)楫悩?gòu)網(wǎng)絡(luò)、非正交多址接入技術(shù)、綠色蜂窩網(wǎng)絡(luò)

康桂霞：女，1972年生，博士生導(dǎo)師，研究方向?yàn)橐苿?dòng)物聯(lián)通信、大數(shù)據(jù)人工智能技術(shù)

通訊作者:
康桂霞　gxkang@bupt.edu.cn

中圖分類號(hào): TN929.5
計(jì)量
- 文章訪問數(shù): 1522
- HTML全文瀏覽量: 700
- PDF下載量: 70
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2019-07-02
- 修回日期: 2020-04-13
- 網(wǎng)絡(luò)出版日期: 2020-08-31
- 刊出日期: 2020-11-16

Energy Efficient Power Allocation with NOMA in Downlink Heterogeneous Networks

Shuang ZHANG,
Guixia KANG^,

1.
College of Career Technology, Hebei Normal University, Shijiazhuang 050024, China
2.
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
3.
Wuxi BUPT Sensory Technology and Industry Institute, Wuxi 214000, China

Funds: The National Science and Technology Major Project of China (2017ZX03001022)

摘要

摘要: 該文針對應(yīng)用非正交多址接入(NOMA)技術(shù)的異構(gòu)蜂窩網(wǎng)絡(luò)，在考慮層間層內(nèi)干擾的情況下，提出一種能效最大化的功率分配算法。該算法主要包括兩部分，一部分為子信道內(nèi)用戶功率分配因子的求解，主要利用差分優(yōu)化的方法，迭代求解。另一部分為子信道間的功率分配，主要利用凹凸程序法將原有的非凸問題簡化為可解的凸問題，最后利用拉格朗日求解法得出功率最優(yōu)解。仿真結(jié)果表明該算法有良好的迭代性，且新算法表明利用NOMA技術(shù)得到的系統(tǒng)能效較利用正交技術(shù)得到的系統(tǒng)能效提高了至少44%以上。
- 非正交多址接入 /
- 異構(gòu)蜂窩網(wǎng)絡(luò) /
- 能效 /
- 功率分配
Abstract: This paper proposes a power allocation scheme for energy efficiency maximization in a downlink Non-Orthogonal Multiple Access (NOMA)-based Heterogeneous Network (HetNets) with considering the out-of-cell interference and in-cell interference. The scheme contains mainly two parts. One is the power allocation between the users at the same sub-channel, where Difference of Convex (DC) functions -programming is exploited to solve the problem. Another is the power allocation between the sub-channels, in which ConCave–Convex Procedure (CCCP) method and Lagrangian multiplier method are combined to solve the problem. The simulation results show that the fast convergence property, and demonstrate that the EE obtained by the proposed algorithms based on NOMA is at least 44% higher than that obtained by the conventional orthogonal multiple access scheme.
- Non-Orthogonal Multiple Access (NOMA) /
- Heterogeneous Networks (HetNets) /
- Energy efficiency /
- Power allocation

HTML全文

圖 1 不同最大發(fā)送功率下的能效值

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圖 2 不同用戶速率要求下的能效值

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圖 3 算法收斂性能

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表 1 子信道內(nèi)用戶功率分配因子算法

DC programing功率分配因子算法
1.初始化：設(shè)置${(\alpha _f^n)^c}$的初始值；設(shè)置迭代索引$c = 0$；設(shè)置最大迭代次數(shù)${C_{\max }}$以及容忍度$\mu $的值；計(jì)算式　 $q({(\alpha _f^n)^0}) = f({(\alpha _f^n)^0}) - g({(\alpha _f^n)^0})$的值。
2. repeat
3. 計(jì)算式(8)獲取最優(yōu)功率分配因子${(\alpha _f^n)^*}$
4. $c = c + 1$，${(\alpha _f^n)^c} = {(\alpha _f^n)^*}$，計(jì)算$q({(\alpha _f^n)^c}) = f({(\alpha _f^n)^c}) - g({(\alpha _f^n)^c})$
5. until $\left\| {q({{(\alpha _f^n)}^c}) - q({{(\alpha _f^n)}^{c - 1}})} \right\| \le \mu $ or $c > {C_{\max }}$
6. ${(\alpha _f^n)^*} = {(\alpha _f^n)^c}$

下載: 導(dǎo)出CSV

表 2 子信道間功率分配算法

CCCP信道功率分配算法
1：初始化設(shè)置迭代索引$v = 0$，誤差容忍度$\xi > 0$。設(shè)置初始化${{{P}}^0}$，最大迭代次數(shù)${V_{\max }}$，計(jì)算${\left( {\lambda _f^n} \right)^0} = {1 / {\left( {{{\left( {p_f^n} \right)}^0} + {p_c}} \right)}}$, 　　 ${(\gamma _f^n)^0} = {{R_f^n\left( {{{(p_f^n)}^0}} \right)} / {\left( {{{(p_f^n)}^0} + {p_c}} \right)}}$
2: repeat
3：利用拉格朗日對偶求解${\left( {{{{P}}^}} \right)^v}$即${{{P}}^{v + 1}}$其中${\left( {{{{P}}^}} \right)^v}$滿足式(35)和式(36)。
4：根據(jù)式(12)更新${(\lambda _f^n)^{v + 1}}$和${(\gamma _f^n)^{v + 1}}$的值。
5：設(shè)置$v = v + 1$ 　6: until $\left\| {\mathop {\max }\limits_{{P} } \left\{ {\displaystyle\sum\limits_{f = 1}^F { { {(\lambda _f^n)}^v}[R_f^n({ {(p_f^n)}^v})(1 + { {\beta \left( { { {(p_f^n)}^v} + {p_c} } \right)} / B}) - { {(\gamma _f^n)}^v}({ {(p_f^n)}^v} + {p_c})]} } \right\} } \right\| \le \xi$ or $v > {V_{\max }}$

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