Multiuser Detection Based on MAP Estimation With Sum-of-Absolute-Values Relaxation
Multiuser Detection Based on MAP Estimation With Sum-of-Absolute-Values Relaxation
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DOI：
10.1109/tsp.2017.2740164
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发表时间：
2017-11
影响因子：
5.4
通讯作者：
Hampei Sasahara;K. Hayashi;M. Nagahara
中科院分区：
文献类型：
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作者：
Hampei Sasahara;K. Hayashi;M. Nagahara
在本文中，我们考虑多用户检测，应付多址干扰造成的低速率无线通信系统中有大量的节点，如机器对机器通信。我们考虑到传输信号的离散性（例如，取$\pm 1$的值的二进制信号），我们将其用作检测中的先验信息。我们首先制定的检测问题作为一个最大后验估计问题。由于这个问题是高度非凸的和不连续的，我们提出了凸松弛的绝对值（SOAV）的最优化的基础上，可以有效地解决了邻近分裂。我们还推导出一个上限的松弛误差的SOAV优化噪声情况下的限制等距属性的基础上。数值仿真结果表明了该方法的有效性。
In this paper, we consider multiuser detection that copes with multiple access interference caused in low-rate wireless communication systems with a large number of nodes, such as machine-to-machine communications. We take account of discreteness of transmitted signals (e.g., binary signals taking values of $\pm 1$), which we utilize as prior information in detection. We first formulate the detection problem as a maximum a posteriori estimation problem. Since this problem is highly nonconvex and discontinuous, we propose convex relaxation based on the sum-of-absolute-values (SOAV) optimization, which can be efficiently solved by proximal splitting. We also derive an upper bound of the relaxation error by the SOAV optimization in noisy cases based on the restricted isometry property. Numerical simulations are shown to illustrate the effectiveness of the proposed approach.