一种面向CR-NOMA系统的动态功率分配算法

彭艺; 范泽昊; 杨青青; 彭游

doi:10.12265/j.cjors.2021246

一种面向CR-NOMA系统的动态功率分配算法

doi: 10.12265/j.cjors.2021246

昆明理工大学信息工程与自动化学院，昆明 650504

基金项目: 国家自然科学基金（617610025）

详细信息

作者简介:
彭艺 (1975—)，女，云南人，昆明理工大学副教授，博士，研究方向为无线认知网络

范泽昊 (1996—)，男，河北人，昆明理工大学硕士研究生，研究方向为认知无线电、非正交多址接入技术

杨青青 (1981—)，女，山东人，博士，硕士研究生导师，研究方向为信息处理、应急通信以及新材料等方面

通讯作者:
范泽昊 E-mail：1073138447@qq.com

中图分类号: TN929.5
计量
- 文章访问数: 222
- HTML全文浏览量: 54
- PDF下载量: 18
- 被引次数: 0
出版历程
- 收稿日期: 2021-09-06
- 录用日期: 2021-12-14
- 网络出版日期: 2021-12-14

A dynamic power allocation algorithm for CR-NOMA system

College of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China

摘要

摘要: 在密集小区的认知非正交多址（cognitive radio non-orthogonal multiple access, CR-NOMA）网络场景下，针对用户采取Underlay方式复用时信道频带利用率低问题，提出了一种基于能效的组合用户动态功率分配算法. 该算法在保证主用户服务质量前提下，基于用户之间的干扰和信干噪比，优化了组合多用户的接入方案，使信道接入用户数量最大且提高了频带利用率. 同时，根据增益排序下的功率差额配比改进了剩余功率再分配方案，使空闲功率重新利用更加合理和有效. 仿真结果表明，本文算法可以有效实现接入用户数量最大化的同时提高频谱利用率.
- 认知无线电 /
- 非正交多址 /
- 动态功率分配 /
- 动态组合 /
- 功率再分配
Abstract: In the case of CR-NOMA networks in dense cells, this paper proposes a combined user dynamic power allocation algorithm based on energy efficiency to address the problem of low channel band utilization when users adopt Underlay multiplexing. Under the premise of ensuring the quality of service of the primary user, the algorithm optimizes the combined multi-user access scheme based on the interference between users and the signal-to-interference-to-noise ratio, maximizes the number of channel access users and improves the frequency band utilization. At the same time, the remaining power redistribution scheme is improved according to the power balance ratio under the gain sorting, making the reuse of idle power more reasonable and effective. The simulation results show that the proposed algorithm can effectively maximize the number of access users while improving the spectrum utilization
- cognitive radio /
- non-orthogonal multiple access /
- dynamic power distribution /
- dynamic combination /
- power redistribution

HTML全文

图 1 CR-NOMA多用户接入模型

Fig. 1 CR-NOMA multi-user access model

下载: 全尺寸图片幻灯片

图 2 SU接入模型

Fig. 2 Secondary user access model

下载: 全尺寸图片幻灯片

图 3 允许接入的SU数随发起请求SU数变化

Fig. 3 The number of secondary users allowed to access varies with the number of secondary users who initiate requests

下载: 全尺寸图片幻灯片

图 4 SU公平指数随分配功率变化

Fig. 4 The change of secondary user fairness index with allocated power

下载: 全尺寸图片幻灯片

图 5 允许接入SU数随PU信干噪比变化

Fig. 5 Variation of allowable access secondary users with new interference noise ratio of primary users

下载: 全尺寸图片幻灯片

图 6 平均系统能效随接入SU数变化

Fig. 6 The average system energy efficiency varies with the number of access users

下载: 全尺寸图片幻灯片

图 7 频带利用率之比随接入用户数变化

Fig. 7 The ratio of band utilization varies with the number of access users

下载: 全尺寸图片幻灯片

表 1 基于能效的组合用户功率动态分配算法

Tab. 1 Combined user power dynamic allocation algorithm based on energy efficiency

(1)　初始化控制参数$ {P}_{\mathrm{s}} $，用户队列字典$ S=\{{S}_{1}:{P}_{1};{S}_{2}:{P}_{2};\cdots {;S}_{j}:{P}_{j}\} $，$ j\in \left(1,{\displaystyle\sum }_{j=1}^{N}{C}_{N}^{j}\right) $，序列字典$ {S}^{\mathrm{*}}=\{{S}_{1}:0;{S}_{2}:0;\cdots ;{S}_{k}:0\} $，$ k\in (\mathrm{1,2},\cdots ,n) $，发起请求SU字典$ \mathrm{S}\mathrm{U}=[{\mathrm{S}\mathrm{U}}_{1}:{P}_{1};{\mathrm{S}\mathrm{U}}_{2}:{P}_{2};\cdots ;{\mathrm{S}\mathrm{U}}_{i}:{P}_{i}] $
(2)　for $ {\mathrm{S}\mathrm{U}}_{j},{P}_{j} $ in range S. items(): 　# 遍历用户队列字典
(3)　　for $ j $,$ {P}_{i} $ in range(1,$ {\displaystyle\sum }_{j=1}^{N}{C}_{N}^{j} $):
(4)　permutations ($ {\mathrm{S}\mathrm{U}}_{j},j $)　* 生成随机组合
(5)　　　return $ {\mathrm{S}\mathrm{U}}_{j} $ 　# 返回编号为 $ j $的组合$ {\mathrm{S}\mathrm{U}}_{j} $
(6)　　return $ {\displaystyle\sum }_{{\mathrm{S}\mathrm{U}}_{j}}{P}_{i}{x}_{i} $ 　# 返回编号为 $ j $的组合$ {\mathrm{S}\mathrm{U}}_{j} $的SU功率和
(7)　将$ {\mathrm{S}\mathrm{U}}_{j} $的功率和赋值给序列字典$ {S}^{\mathrm{*}} $，得到更新后的序列字典$ {S}^{\mathrm{*}}=\{{S}_{1}:\displaystyle\sum {P}_{i}{x}_{\left(i,{\mathrm{S}\mathrm{U}}_{1}\right)};{S}_{2}:\displaystyle\sum {P}_{i}{x}_{\left(i,{\mathrm{S}\mathrm{U}}_{2}\right)};\cdots {;S}_{k}:\displaystyle\sum {P}_{i}{x}_{\left(i,{\mathrm{S}\mathrm{U}}_{k}\right)}\} $
(8)　for $ k{P}_{k} $in range$ {S}^{\mathrm{*}} $.items():
(9)　　if $ {P}_{k} > {P}_{\mathrm{s}} $:
(10)　　　return 0
(11)　　elif $ {P}_{k}={P}_{\mathrm{s}} $:
(12)　　　return k
(13)　　　return $ n=\displaystyle\sum {x}_{\left(i,{\mathrm{S}\mathrm{U}}_{k}\right)} $ 　# 返回最优值
(14)　　else：
(15)　　　if $ {{P}_{s}-P}_{k}\ge {P}_{\left(\mathrm{U}\mathrm{A},j\right)}: $ 　# $ {P}_{(\mathrm{U}\mathrm{A},j)} $表示未接入的用户
(16)　　　return 0
(17)　　else:
(18)　　　　return $ {P}_{k} $
(19)　　　　return $ n=\displaystyle\sum {x}_{\left(i,{\mathrm{S}\mathrm{U}}_{k}\right)} $ 　# 返回$ k $用户数
(20)　 return $ k $
(21) 返回值继续赋值给序列字典$ {S}^{\mathrm{*}} $
(22) * 将$ {S}^{\mathrm{*}} $内冗余情况清空，返回值继续存放在序列字典$ {S}^{\mathrm{*}} $，节省内存
(23) for $ {k}^{\mathrm{*}} $,$ n $ in range$ {S}^{\mathrm{*}} $.items():
(24)　$ n $.sort(reverse=True)
(25)　return $ {k}^{\mathrm{*}} $ 　# 返回按从大到小后的顺序给列表
(26)　if $ {n}_{{k}^{\mathrm{*}}} > {n}_{{k}^{\mathrm{*}}-1} > {n}_{{k}^{\mathrm{*}}-2} > \cdots $: 　# 判断用户数量最多
(27)　　return $ {k}^{\mathrm{*}} $
(28)　elif $ {n}_{{k}^{\mathrm{*}}}={n}_{{k}^{\mathrm{*}}-1}={n}_{{k}^{\mathrm{*}}-2} > \cdots $:
(29)　　cmp($ {P}_{{k}^{\mathrm{*}}},{P}_{{k}^{\mathrm{*}}-1}\cdots $)　# 返回功率最大的情况
(30)　else:
(31)　　Break

(32) end

下载: 导出CSV

表 2 基于信道增益的功率再分配算法

Tab. 2 Power redistribution algorithm based on channel gain

(1) 初始化字典$ \boldsymbol{Q}=\{{\boldsymbol{Q}}_{1}:\left|{\boldsymbol{h}}_{\left(\mathbf{S}\mathbf{U},1\right)}\right|,{\boldsymbol{Q}}_{2}:\left|{\boldsymbol{h}}_{\left(\mathbf{S}\mathbf{U},2\right)}\right|\cdots {\boldsymbol{Q}}_{\boldsymbol{k}}:\left|{\boldsymbol{h}}_{\left(\mathbf{S}\mathbf{U},\boldsymbol{k}\right)}\right|\}，{\boldsymbol{P}}_{\mathbf{A}}=0，{\boldsymbol{P}}_{\mathbf{U}\mathbf{N}}=0 $，初始化列表$ \boldsymbol{O}=\mathbf{\varnothing } $，${\boldsymbol{O}}^{\boldsymbol{*}}=\mathbf{\varnothing } $
　　　　　# $ {\boldsymbol{P}}_{\mathbf{A}}=0 $表示接入用户总功率　　 $ {\boldsymbol{P}}_{\mathbf{U}\mathbf{N}}=0 $表示剩余功率
(2)将算法1中最优解的SU功率及信道增益值赋值给字典
(3) $ \boldsymbol{Q} $.sort(reverse=True) 　　# 将$ \boldsymbol{Q} $中元素按初始功率从大到小排列
(4) 代入式(18)-(20)，计算出$ \boldsymbol{Q} $中SU排出干扰后的功率
(5) ${\boldsymbol{P} }_{\mathbf{A} }={\displaystyle\sum }_{\boldsymbol{l}=1}^{\boldsymbol{k} }{\boldsymbol{P} }_{\boldsymbol{l} }$
(6) $ {\boldsymbol{P}}_{\mathbf{U}\mathbf{N}}={{\boldsymbol{P}}_{\mathbf{s}}-{\boldsymbol{P}}_{\mathbf{A}}}_{} $
(7) $ \boldsymbol{Q} $.sort(reverse=True)　　 # 将$ \boldsymbol{Q} $中元素按增益从大到小排列
(8) 功率累减得到数列，并构造新列表$ \boldsymbol{O}=[{\boldsymbol{O}}_{1},{\boldsymbol{O}}_{2},\cdots ,{\boldsymbol{O}}_{\boldsymbol{k}-1}] $ 　　# 信道增益相近用户功率差
(9) 构造新列表${\boldsymbol{O} }^{ {*} }=\left[\left|\frac{ {\boldsymbol{O} }_{1} }{ {\displaystyle\sum }_{\boldsymbol{L}=1}^{\boldsymbol{k}-1}{\boldsymbol{O} }_{\boldsymbol{L} } }|,|\frac{ {\boldsymbol{O} }_{2} }{ {\displaystyle\sum }_{\boldsymbol{L}=1}^{\boldsymbol{k}-1}{\boldsymbol{O} }_{\boldsymbol{L} } }|\cdots |\frac{ {\boldsymbol{O} }_{\boldsymbol{l} } }{ {\displaystyle\sum }_{\boldsymbol{L}=1}^{\boldsymbol{k}-1}{\boldsymbol{O} }_{\boldsymbol{L} } }\right|\right]$
(10) ${\boldsymbol{P} }_{\boldsymbol{k}-1}={\boldsymbol{P} }_{\mathbf{U}\mathbf{N} }\left|\frac{ {\mathbf{O} }_{\boldsymbol{l} } }{ {\displaystyle\sum }_{\boldsymbol{L}=1}^{\boldsymbol{k}-1}{\boldsymbol{O} }_{\boldsymbol{L} } }\right|+{\boldsymbol{P} }_{\boldsymbol{k}-1},{\boldsymbol{P} }_{\boldsymbol{k}-2}={\boldsymbol{P} }_{\mathbf{U}\mathbf{N} }\left|\frac{ {\boldsymbol{O} }_{\boldsymbol{l}-1} }{ {\displaystyle\sum }_{\boldsymbol{L}=1}^{\boldsymbol{k}-1}{\boldsymbol{O} }_{\boldsymbol{L} } }\right|+{\boldsymbol{P} }_{\boldsymbol{k}-2},\cdots \cdots {,\boldsymbol{P} }_{1}={\boldsymbol{P} }_{\mathbf{U}\mathbf{N} }\left|\frac{ {\boldsymbol{O} }_{1} }{ {\displaystyle\sum }_{\boldsymbol{L}=1}^{\boldsymbol{k}-1}{\boldsymbol{O} }_{\boldsymbol{L} } }\right|+{\mathbf{P} }_{1}$ # 剩余功率分配给前$ \boldsymbol{k}-1 $个SU

(11) end

下载: 导出CSV

参考文献(14)

[1]	卢前溪. 认知无线电网络中的资源调度算法研究[D]. 北京邮电大学, 2011. Q X Lu. Research on resource scheduling algorithm in cognitive radio networks[D]. Beijing University of Posts and Telecommunications, 2011
[2]	MITOLA J, MAGUIRE G Q. Cognitive radio: making software radios more personal[J]. IEEE personal communications,1999,6(4):13-18. DOI: 10.1109/98.788210
[3]	ISLAM S M R, AVAZOV N, DOBRE O A, et al. Power-domain non-orthogonal multiple access (NOMA) in 5G systems: potentials and challenges[J]. IEEE communications surveys and tutorials,2017,19(2):721-742. DOI: 10.1109/COMST.2016.2621116
[4]	SAITO Y, KISHIYAMA Y, BENJEBBOUR A. Non-orthogonal multiple access(NOMA) for cellular future radio access[C]// IEEE Vehicular Technology Conference(VTC), Dresden, 2013: 1-5.
[5]	SAITO Y, BENJEBBOUR A, KISHIYAMA Y, et al. System-level performance evaluation of downlink non-orthogonal multiple access(NOMA)[C]// IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications(PIMRC), London, 2013: 611-615.
[6]	BENJEBBOUR A, SAITO Y, KISHIYAMA Y, et al. Concept and practical considerations of Non-orthogonal multiple access(noma)for future radio access[C]// International Symposium on Intelligent Signal Processing and Communication Systems, Naha, 2013: 770-774.
[7]	LIU Y, DING Z, ELKASHLAN M, et al. Nonorthogonal multiple access in large-scale underlay cognitive radio networks[J]. IEEE transaction on vehicular technology,2016,65(12):10152-10157. DOI: 10.1109/TVT.2016.2524694
[8]	ALHAMAD R, BOUJEMA H. Optimal power allocation for CRN-NOMA systems with adaptive transmit power[J]. Signal image and video processing, 2020, 14(8). DOI: 10.1007/s11760-020-01674-8
[9]	罗章凯, 裴忠民, 熊伟, 等. 一种基于正交向量的极化相关衰减效应消除方法[J]. 电波科学学报, 2021. DOI: 10.12265/j.cjors.2021036 ZABETIAN N, BAGHANI M, MOHAMMADI A. Rate optimization in NOMA cognitive radio networks[C]// International Symposium on Telecommunications(IST), Tehran, 2016: 62-65. LUO Z K, PEI Z M, XIONG W, et al. Orthogonal vector based transmission method for polarization dependent loss effect elimination[J]. Chinese journal of radio science, 2021. (in Chines). DOI: 10.12265/j.cjors.2021036
[10]	李冠雄, 李桂林. 基于强化学习的合作频谱分配算法[J]. 电波科学学报, 2021. DOI: 10.12265/j.cjors.2020016 LI G X, LI G L. Cooperative spectrum allocation algorithm based on reinforcement learning[J]. Chinese journal of radio science, 2021. (in Chinese). DOI: 10.12265/j.cjors.2020016
[11]	OTAO N, KISHIYAMA Y, HIGUCHI K. Performance of non-orthogonal multiple access with sic in cellular downlink using proportional fair-based resource allocation[J]. IEICE transactions on communications,2015,98(2):344-351.
[12]	GAMAL S, RIHAN M, ZAGHLOUL A, et al. Two-tier power allocation for non-orthogonal multiple access based cognitive radio networks[C]// IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA). IEEE, 2018.
[13]	时安谊, 杨震. 针对NOMA和CR网络的功率分配方法[J]. 信号处理,2019,35(7):1224-1234. SHI A Y, YANG Z. Power allocation method for non-orthogonal multiple access and cognitive radio network[J]. Journal of signal processing,2019,35(7):1224-1234. (in Chinese)
[14]	YAN C, HARADA A, BENJEBBOUR A, et a1. Receiver design for downlink non-orthogonal multiple access(NOMA)[C]// IEEE Vehicular Technology Conference(VTC), Glasgow, 2015: 1-6.