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

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

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2.5×10^-2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。

In massive Machine-Type Communication(mMTC)systems,when the user activity is exploited as a priori information for the receiver,the Sparsity-aware Maximum A Posteriori probability(S-MAP)criterion can be used to recover the sparse multi-user vectors over the uplink mMTC systems.In order to reduce the computational complexity of S-MAP detection,based on interference cancellation mechanism,an Improved Activity-aware Sorted QR Decomposition(IA-SQRD)algorithm is proposed in this paper.The IA-SQRD algorithm utilizes the final solution of the A-SQRD algorithm as the initial solution and the iterative interference cancellation operation is performed to improve further the detection performance.Following the same philosophy in improving the A-SQRD algorithm,the conventional Sparsity-Aware Successive Interference Cancellation(SA-SIC),Sorted QR Decomposition(SQRD),and Data-Dependent Sorting and regularization(DDS)algorithms are modified to enhance the performance,respectively.Simulation results verify that compared with the A-SQRD algorithm,a 3 dB gain is achieved by the proposed IA-SQRD algorithm when the Bit Error Rate(BER)is 2.5×10^-2,without significantly increasing the computational complexity.In addition,given different system configurations in terms of active probability and the length of spread spectrum sequence,the proposed IA-SQRD also exhibits better performance than that of the other algorithms mentioned in this paper.