理想和非理想信道估计下的高维调制叠加NOMA系统

doi:10.19678/j.issn.1000-3428.0065235

摘要/Abstract

摘要：

随着第5代移动通信技术（5G）的投入使用，传统的正交多址接入（OMA）技术难以完全满足5G多场景对通信速度和系统容量的需求，非正交多址（NOMA）技术以其高频谱效率和大接入容量的优势逐渐成为未来通信系统中的一项重要技术，但目前NOMA技术在信道估计误差下存在码字检测错误概率过高的问题。提出两种基于高维调制叠加的功率域NOMA系统，分别用于理想信道估计和非理想信道估计，并分析这两种双用户NOMA系统中两个用户码字检测错误概率的近似界，以提高功率域NOMA系统的性能。此外，基于近似界推导在给定码字检测错误概率的情况下使传输功率最小的最优功率分配因子。仿真结果表明，两种用户NOMA系统内用户的实际码字检测错误概率间的差距在理想和非理想信道估计下分别约为1 dB、2 dB，所提功率分配方案在增加较小运算量的情况下能有效提高系统码字检测性能。

关键词: 非正交多址接入, 功率分配, 球码, 高维调制, 信道估计

Abstract:

As the fifth generation mobile communication technology(5G) has been put into use, the traditional Orthogonal Multiple Access(OMA) technology is difficult to fully satisfy the requirements for communication speed and system capacity in 5G multi-scenes.Non-Orthogonal Multiple Access(NOMA) is becoming essential in future communication systems with advantages of high spectral efficiency and large access capacity.However, in NOMA technology, the error probability of code word detection is extremely high under the error of channel estimation. Two power-domain NOMA schemes based on high-dimensional modulation superposition are proposed: one is used in ideal channel estimation, and the other is under the condition of non-ideal channel estimation. The approximate bounds of the error probability of two user code word detection in these two dual-user NOMA systems are analyzed to improve the performance of power domain NOMA systems. In addition, based on the approximation bounds, this study derives the optimal power allocation factor, which can minimize the transmit power with a given word error probability. The simulation results show that under ideal and non-ideal channel estimation, the actual error probability of user codework detection of the gap between two users in the NOMA system is approximately 1 dB and 2 dB, respectively.The proposed power allocation scheme can effectively improve the detection performance of the system with minimal computation effort.

Key words: Non-Orthogonal Multiple Access(NOMA), power allocation, spherical code, high-dimensional modulation, channel estimation

邹骏, 赵心雨, 顾鹏, 孙继元. 理想和非理想信道估计下的高维调制叠加NOMA系统[J]. 计算机工程, 2023, 49(8): 111-121.

Jun ZOU, Xinyu ZHAO, Peng GU, Jiyuan SUN. High-Dimensional Modulation Superposition NOMA System with Ideal and Non-Ideal Channel Estimation[J]. Computer Engineering, 2023, 49(8): 111-121.

https://www.ecice06.com/CN/Y2023/V49/I8/111

图/表 14

图1 双用户NOMA系统模型

Fig.1 Two-user NOMA system model

图2 球码叠加NOMA的用户码字检测错误概率1

Fig.2 Error probability 1 of user codeword detection based on spherical code superposition NOMA

图3 球码叠加NOMA的用户码字检测错误概率2

Fig.3 Error probability 2 of user codeword detection based on spherical code superposition NOMA

图4 球码叠加NOMA的用户码字检测错误概率3

Fig.4 Error probability 3 of user codeword detection based on spherical code superposition NOMA

图5 球码叠加NOMA的用户码字检测错误概率4

Fig.5 Error probability 4 of user codeword detection based on spherical code superposition NOMA

图6 球码叠加NOMA的用户码字检测错误概率5

Fig.6 Error probability 5 of user codeword detection based on spherical code superposition NOMA

图7 不同信道估计误差下球码叠加NOMA的用户码字检测错误概率

Fig.7 Error probability of user codeword detection based on spherical code superposition NOMA under different channel estimation errors

图8 球码叠加NOMA的用户码字检测错误概率6

Fig.8 Error probability 6 of user codeword detection based on spherical code superposition NOMA

图9 球码叠加NOMA的用户码字检测错误概率7

Fig.9 Error probability 7 of user codeword detection based on spherical code superposition NOMA

图10 不同功率分配因子下球码叠加NOMA的用户码字检测错误概率1（

$ {{\sigma }}_{1}=0.01，{{\sigma }}_{2}=0.03 $

）

Fig.10 Error probability 1 of user codeword detection based on spherical code superposition NOMA under different power allocation factor(

$ {{\sigma }}_{1}=0.01,{{\sigma }}_{2}=0.03 $

)

图11 不同功率分配因子下球码叠加NOMA的用户码字检测错误概率2（

$ {{\sigma }}_{1}=0.02，{{\sigma }}_{2}=0.06 $

）

Fig.11 Error probability 2 of user codeword detection based on spherical code superposition NOMA under different power allocation factor(

$ {{\sigma }}_{1}=0.02,{{\sigma }}_{2}=0.06 $

)

图12 用户2不同信道估计误差下的球码叠加NOMA的用户码字检测错误概率（

$ {{\sigma }}_{1}=0.01，{{\sigma }}_{2}=0.10 $

）

Fig.12 Error probability of user codeword detection based on spherical code superposition NOMA under different channel estimation errors for user 2(

$ {{\sigma }}_{1}=0.01,{{\sigma }}_{2}=0.10 $

)

图13 用户1不同信道估计误差下的球码叠加NOMA的用户码字检测错误概率（

$ {{\sigma }}_{2}=0.08，{g}=1.10 $

）

Fig.13 Error probability of user codeword detection based on spherical code superposition NOMA under different channel estimation errors of user 1(

$ {{\sigma }}_{2}=0.08,{g}=1.10 $

)

图14 不同信道估计误差下格码叠加NOMA的用户码字检测错误概率

Fig.14 Error probability of user codeword detection based on grid code superposition NOMA under different channel estimation errors

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