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基于稀疏感知有序干扰消除的大规模机器类通信系统多用户检测

申滨 吴和彪 赵书锋 崔太平

申滨, 吴和彪, 赵书锋, 崔太平. 基于稀疏感知有序干扰消除的大规模机器类通信系统多用户检测[J]. 电子与信息学报, 2020, 42(12): 2960-2968. doi: 10.11999/JEIT190994
引用本文: 申滨, 吴和彪, 赵书锋, 崔太平. 基于稀疏感知有序干扰消除的大规模机器类通信系统多用户检测[J]. 电子与信息学报, 2020, 42(12): 2960-2968. doi: 10.11999/JEIT190994
Bin SHEN, Hebiao WU, Shufeng ZHAO, Taiping CUI. Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2960-2968. doi: 10.11999/JEIT190994
Citation: Bin SHEN, Hebiao WU, Shufeng ZHAO, Taiping CUI. Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC[J]. Journal of Electronics & Information Technology, 2020, 42(12): 2960-2968. doi: 10.11999/JEIT190994

基于稀疏感知有序干扰消除的大规模机器类通信系统多用户检测

doi: 10.11999/JEIT190994
基金项目: 国家重大研发计划(2017YFE0118900),欧盟H2020项目(734798)
详细信息
    作者简介:

    申滨:男,1978年生,教授,研究方向为认知无线电、大规模MIMO等

    吴和彪:男,1994年生,硕士生,研究方向为大规模机器类系统多用户检测

    赵书锋:男,1991年生,硕士生,研究方向为大规模MIMO系统信号检测

    崔太平:男,1981年生,讲师,研究方向为认知无线电、车联网

    通讯作者:

    申滨 shenbin@cqupt.edu.cn

  • 中图分类号: TN929.5

Sparsity-aware Ordered Successive Interference Cancellation Based Multi-user Detection for Uplink mMTC

Funds: The National Key R&D Program of China (2017YFE0118900), The EU H2020 Project (734798)
  • 摘要:

    在大规模机器类通信(mMTC)系统中,以用户活跃性为先验信息,接收机可以基于稀疏感知最大后验概率(S-MAP)准则来检测多用户信号。为了降低S-MAP检测的计算复杂度,基于干扰消除的思想,该文提出一种改进的活跃性感知有序正交三角分解(IA-SQRD)算法,以适用于mMTC系统上行链路多用户信号检测。IA-SQRD算法将传统的活跃性感知有序正交三角分解(A-SQRD)算法的最终解作为初始解,并额外增加迭代干扰消除操作,以进一步提高检测性能。此外,利用与改进A-SQRD算法相似的思路,该文对稀疏感知串行干扰消除(SA-SIC)、有序正交三角分解(SQRD)及数据相关的排序和正则化(DDS)算法亦进行了改进设计,分别获得了相应的改进型算法,即ISA-SIC、I-SQRD及I-DDS算法。仿真结果表明:相对于A-SQRD算法,在未显著增加计算复杂度的情况下,在系统误比特率(BER)为

    \begin{document}$2.5 \times {10^{ - 2}}$\end{document}

    时,该文所提IA-SQRD算法可取得3 dB性能增益;并且,对于不同的活跃概率或扩频序列长度等参数配置下的mMTC系统,IA-SQRD算法相对于其它算法均表现出更优良的多用户检测性能。

  • 图  1  在[0.1 0.3]区间中随机均匀分布的用户活跃概率

    图  2  BER性能对比,$64 \times 128$配置

    图  3  BER性能对比,$128 \times 256$配置

    图  4  不同用户活跃概率对应的BER性能

    图  5  不同扩频序列长度对应的BER性能

    表  1  改进型活跃性感知有序正交三角分解(IA-SQRD)检测算法

     输入:${y}$, ${H}$, ${{A}_0}$, ${\rm{\sigma }}_w^2$,$\left\{ {{p_n}} \right\}_{n = 1}^N$
     输出:${{\bar s}^{{T_{{\rm{iter}}}}}}$(${T_{{\rm{iter}}}}$为迭代次数)
     (1) ${{\rm{\lambda }}_n} = \ln [(1 - {p_n})/({p_n}/\left| {A} \right|)]$
     (2) ${{y}_0} = [{y};{\bf{0}_N}]$, ${Q} = [{H};{{\rm{\sigma }}_w}{\rm{diag}}\left( {\sqrt {{\lambda }} } \right)]$, ${R} = {{{\textit{0}}}_{N \times N}}$, ${P} = {{I}_N}$
     (3) for $n = 1,2, \cdots ,N$ do
     (4) ${n_{\min } } = \arg {\min _{j = n,n + 1, ··· ,N} }{\left\| { {{q}_j} } \right\|^2}$
     (5) 交换${Q}$, ${R}$和${P}$中的$n$和${n_{\min }}$列
     (6) ${R_{nn}} = \left\| {{{q}_n}} \right\|$,${{q}_n} = {{q}_n}/{R_{nn}}$
     (7) for $j = n + 1, ···,N - 1,N$ do
     (8) ${R_{nj}} = {q}_n^{\rm{H}}{{q}_j}$, ${{q}_j} = {{q}_j} - {R_{nj}}{{q}_n}$
     (9) end for
     (10) end for
     (11) ${{\tilde y}_0} = {{Q}^{\rm{H}}}{{y}_0}$
     (12) for $n = N,N - 1, ··· ,1$ do
     (13) $x_n' = \left({\tilde y_{0,n} } - \displaystyle\sum\limits_{l = n + 1}^N { {R_{nl} } } {\hat x_l}\right)/{R_{nn} }$
     (14) ${\hat x_n} = {Q_{{{A}_0}}}({x_{n'}})$
     (15) end for
     (16) $\hat{ x} = \hat{ x}{{P}^{\rm{H}}}$
     (17) ${s} = \hat{ x}$
     (18) ${G} = {{H}^{\rm{H}}}{H}$, ${b} = {{H}^{\rm{H}}}{y}$
     (19) for $t = 1:{T_{{\rm{iter}}}}$
     (20) for $n = 1:N$
     (21) $\hat s_n^{(t)} = \hat s_n^{(t - 1)} + \dfrac{ { {b_n} - \displaystyle\sum\limits_{j = 1}^N { {G_{nj} }\hat s_j^{(t - 1)} } } }{ { {G_{nn} } } }$
     (22) $\bar s_n^{(t)} = {Q_{{{A}_0}}}(\hat s_n^{(t)})$
     (23) end for
     (24) end for
    下载: 导出CSV

    表  2  计算复杂度比较(复数浮点运算次数)

    $M$$N$SQRDA-SQRDI-SQRDIA-SQRD
    $16$$32$$3.4 \times {10^4}$$1.0 \times {10^5}$$5.5 \times {10^4}$$1.2 \times {10^5}$
    $32$$64$$2.7 \times {10^5}$$7.9 \times {10^5}$$4.2 \times {10^5}$$9.4 \times {10^5}$
    $64$$128$$2.1 \times {10^6}$$6.3 \times {10^6}$$3.2 \times {10^6}$$7.4 \times {10^6}$
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-12-13
  • 修回日期:  2020-06-23
  • 网络出版日期:  2020-07-18
  • 刊出日期:  2020-12-08

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