论文标题
有效的大型机器类型通信（MMTC）通过AMP
Efficient Massive Machine Type Communication (mMTC) via AMP
论文作者
论文摘要
我们提出了高斯多访问通道（G-MAC）的高效和低复杂性多源检测（MUD）算法，以用于大型机器类型通信中的短包传输。为此，我们首先将G-MAC泥浆问题作为稀疏信号恢复问题，并获得要恢复的稀疏矢量的确切和近似的关节分布。然后，我们采用贝叶斯近似消息传递（AMP）算法，具有最佳的可分离和不可分割的最小平方误差（MMSE）DENOISER，以软解码稀疏向量。模拟结果支持了大量设备的泥浆算法的有效性。对于8个信息位的包装，而具有软阈值deoising的最先进的放大器可在EB/N0 = 4 dB时达到上限的8/100，提议的算法达到上限的4/7和1/2。
We propose efficient and low-complexity multiuser detection (MUD) algorithms for Gaussian multiple access channel (G-MAC) for short-packet transmission in massive machine type communications. To do so, we first formulate the G-MAC MUD problem as a sparse signal recovery problem and obtain the exact and approximate joint prior distribution of the sparse vector to be recovered. Then, we employ the Bayesian approximate message passing (AMP) algorithms with the optimal separable and non-separable minimum mean squared error (MMSE) denoisers for soft decoding of the sparse vector. The effectiveness of the proposed MUD algorithms for a large number of devices is supported by simulation results. For packets of 8 information bits, while the state-of-the-art AMP with soft-threshold denoising achieves 8/100 of the upper bound at Eb/N0 = 4 dB, the proposed algorithms reach 4/7 and 1/2 of the upper bound.
