面向5G的SCMA系统设计

面向5G的SCMA系统设计(任务书,开题报告,外文翻译,论文说明书22000字)
摘要
多址接入是无线通信物理层最核心的技术之一，现有系统采用正交的多址接入方式。正交多址技术由于其接入用户数与正交资源成正比，因此不能满足5G大容量、海量连接、低延时接入等需求，非正交多址接入就成为当下5G多址接入的研究重点。SCMA，稀疏码多址接入，就是应5G需求设计产生的一种非正交多址技术。在发送端通过多维调制和稀疏扩频将编码比特映射成SCMA码字，接收端通过多用户检测完成译码。相比4G的OFDMA技术，它可以实现在同等资源数量条件下，同时服务更多用户，从而有效提升系统整体容量。
在接收端，SCMA通过MPA（Message Passing Algorithm），消息传递算法进行多用户检测。由于需要进行迭代运算，检测器的时延较大。除此之外，传统MPA算法中存在大量非线性计算，不利于硬件实现。为了弥补上述缺点，本文首先设计了针对SCMA技术的快速收敛MPA算法和简化Log-MPA算法，研究了针对SCMA-Turbo的联合大迭代接收机。为了便于硬件实现，本文还提出了一套完整的量化处理方案。重点通过FPGA实现SCMA上行多接入系统，完成了SCMA编码和低复杂度译码模块的开发和验证。
研究结果表明：相对于传统MPA算法，在保证相同性能的前提下，本文提出的快速收敛MPA算法可以明显降低迭代次数，从而大幅降低MPA算法复杂度。简化Log-MPA算法随着迭代次数的增加可以保证其算法稳定收敛，并且明显降低了硬件资源开销。在硬件实现方面，不加噪时可以保证译码正确。加入AWGN信道测试BER v.s Eb/N0的性能瀑布曲线，与仿真结果比对，差别小于1dB。

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本文的特色：研究内容新颖，系创新性突出，研究全面。对于正在发展的5G事业有重要实践意义。
关键词：SCMA；MPA算法；5G；FPGA
 
Abstract
Multiple access is one of the most important technologies in the physical layer of wireless communication, and the existing system adopts orthogonal multiple access method. Orthogonal multiple access technology due to the proportional to the number of access users and orthogonal resource, and therefore can’t satisfy the 5g large capacity, massive connection, low latency access requirements, non orthogonal multiple access has become research focus of current 5g multiple access. SCMA, sparse code multiple access, which is a non orthogonal multiple access technology that should be generated by 5G demand design. The coding bits are mapped into SCMA code word by multi dimension modulation and sparse spread spectrum at the transmitter end. Compared to the OFDMA 4G technology, it can be achieved in the same amount of resources under the conditions, while serving more users, so as to effectively enhance the overall capacity of the system. [来源：http://Doc163.com]
At the receiving end, SCMA through Message (Passing Algorithm MPA), message passing algorithm for multi-user detection. Due to the need of iterative computation, the delay of the detector is larger. In addition, the traditional MPA algorithm has a large number of nonlinear computation, which is not conducive to the realization of the hardware. In order to make up for these shortcomings, this paper firstly designs a fast convergent MPA algorithm and a simplified Log-MPA algorithm for SCMA technology, and studies the combination of SCMA-Turbo and the large iterative receiver. In order to facilitate hardware implementation, this paper also proposes a complete set of quantitative processing. Focusing on the implementation of SCMA uplink multiple access system, the development and verification of SCMA coding and low complexity decoding module is completed by FPGA.
The research results show that: compared with the traditional MPA algorithm, the fast convergent MPA algorithm can significantly reduce the number of iterations, which significantly reduces the complexity of the MPA algorithm compared to the traditional algorithm. With the increase of the number of iterations, the simplified Log-MPA algorithm can ensure the stability and convergence of the algorithm, and obviously reduce the overhead of hardware resources. In terms of hardware implementation, without noise, can ensure the correct decoding. Join AWGN channel test v.s Eb/N0 BER performance of the waterfall curve, and the simulation results, the difference is less than 1dB.

[资料来源：http://www.doc163.com]

The characteristics of this paper: the research content is novel, innovative and comprehensive. It is of great practical significance for the development of 5G industry.
Key Words：SCMA；MPA algorithm；5G；FPGA
 
目录
第1章绪论    1
1.15G技术场景    1
1.25G技术发展现状    2
1.3SCMA概述及发展现状    3
1.4SCMA非正交多址接入技术    4
1.4.1SCMA复用    5
1.4.2SCMA接收机    6
1.5 本课题研究内容及预期目标    7
1.6 本章小结    8
第2章 SCMA多用户检测算法设计    9
2.1Log-MPA检测算法    9
2.1.1 转移概率计算    9
2.1.2 校验节点更新    9
2.1.3 变量节点更新    13
2.1.4SCMA输出比特似然比（LLR）计算    13
2.2Max-Log-MPA检测算法    14
2.3 简化的Log-MPA（S-Log-MPA）算法    14

[来源：http://Doc163.com]

2.4 快速收敛MPA（FC-Log-MPA）算法    16
2.4.1 检验节点更新    17
2.4.2 变量节点更新    18
2.5SCMA-Turbo大迭代联合检测    19
2.6 量化方案    22
2.6.1 对数转移概率的分布    22
2.6.2 对数似然概率的分布    24
2.6.3 量化区间的确定    25
2.6.4SCMA输出比特对数似然比量化区间的确定    27
2.7 本章小结    27
第3章仿真与结果分析    29
3.1仿真参数配置    29
3.2SCMA基本算法性能分析    29
3.2.1Log-MPA算法LUT方法性能分析    29
3.2.2Log-MPA算法与Max-Log-MPA算法性能对比    31
3.3SCMA简化算法性能分析    32
3.3.1快速收敛Log-MPA算法性能分析    32
3.3.2简化Log-MPA算法性能分析    33
3.4SCMA各检测算法性能综合对比分析    33
3.5SCMA-Turbo大迭代性能分析    34
3.6SCMA定点仿真性能分析    36
3.7本章小结    37
第4章硬件仿真与实现    38
4.1系统参数配置和实现环境    38
4.2硬件系统整体框架    39
4.3硬件系统模块    40
4.3.1PLL时钟    40
4.3.2随机信号的产生    40
4.3.3SCMA编码模块    41
4.3.4高斯白噪声的产生    42
4.3.5SCMA译码模块    43
4.4PCI express接口与上位机设计    45
4.4.1FPGA端PCIE设计    45
4.4.2PC端PCIE及上位机设计    46
4.5Modelsim仿真    47
4.5.1仿真环境配置    47
4.5.2伪随机信号的产生    48
4.5.3SCMA编码模块仿真    48
4.5.4AWGN产生模块仿真    49
4.5.5SCMA译码模块仿真    50
4.5.6SCMA系统仿真    51
4.6实测与结果分析    52
4.7本章小结    54
第5章总结与展望    55
5.1总结    55
5.2展望    55
参考文献    56
附录A    58
附A1    58
附A2    59
附A3    59
致谢    60 [资料来源：https://www.doc163.com]