In the massive machine-type communication (mMTC) scenario, a large number of devices with sporadic traffic need to access the network on limited radio resources. While grant-free random access has emerged as a promising mechanism for massive access, its potential has not been fully unleashed. In particular, the common sparsity pattern in the received pilot and data signal has been ignored in most existing studies, and auxiliary information of channel decoding has not been utilized for user activity detection. This paper endeavors to develop advanced receivers in a holistic manner for joint activity detection, channel estimation, and data decoding. In particular, a turbo receiver based on the bilinear generalized approximate message passing (BiG-AMP) algorithm is developed. In this receiver, all the received symbols will be utilized to jointly estimate the channel state, user activity, and soft data symbols, which effectively exploits the common sparsity pattern. Meanwhile, the extrinsic information from the channel decoder will assist the joint channel estimation and data detection. To reduce the complexity, a low-cost side information-aided receiver is also proposed, where the channel decoder provides side information to update the estimates on whether a user is active or not. Simulation results show that the turbo receiver is able to reduce the activity detection, channel estimation, and data decoding errors effectively, while the side information-aided receiver notably outperforms the conventional method with a relatively low complexity.

翻译：在大规模机器类通信场景下，大量具有突发业务特征的设备需在有限无线资源上接入网络。尽管无授权随机接入已成为实现大规模接入的潜在机制，但其潜力尚未得到充分释放。具体而言，现有研究大多忽略了接收导频与数据信号中存在的公共稀疏模式，且信道解码的辅助信息未被用于用户活动检测。本文旨在以整体方式开发先进接收机，实现联合活动检测、信道估计与数据解码。具体地，提出一种基于双线性广义近似消息传递（BiG-AMP）算法的Turbo接收机。该接收机利用所有接收符号联合估计信道状态、用户活动与软数据符号，从而有效利用公共稀疏模式。同时，信道解码器的外信息将辅助联合信道估计与数据检测。为降低复杂度，本文还提出一种低成本侧信息辅助接收机，其通过信道解码器提供侧信息来更新用户活动性估计。仿真结果表明，Turbo接收机能有效降低活动检测、信道估计与数据解码的错误率，而侧信息辅助接收机以相对较低的复杂度显著优于传统方法。