Index Modulation–Aided Mixed Massive Random Access

• Main Authors: Zijie Liang, Jianping Zheng, Jie Ni
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-06-01
• Series: Frontiers in Communications and Networks
• Subjects: index modulation; random access; compressed sensing; iterative receiver; non-Bayesian detection; tree decoder
• Online Access: https://www.frontiersin.org/articles/10.3389/frcmn.2021.694557/full

In this study, a mixed massive random access scheme is considered where part of users transmit both common information and user-specific information, while others transmit only common information. In this scheme, common information is transmitted by index modulation (IM)–aided unsourced random access (URA), while user-specific information is by IM-aided sourced random access (SRA). Practically, IM-aided URA partitions channel blocks of one transmission frame into multiple groups and then employs the IM principle to activate only part of the channel blocks in each group. IM-aided SRA allocates multiple pilot sequences to each user and activates only one pilot sequence whose index carries the data information. At the receiver, the covariance-based maximum likelihood detection (CB-MLD) is employed to recover the active compressed sensing (CS) code words of URA and information of SRA jointly. To stitch the common information at different blocks of URA, a modified tree decoder is proposed to take the IM constraint into account. Furthermore, to relax the strict threshold requirement and improve the performance, an iterative CS detector and tree decoder are employed to decode the common information, where successive signal reconstruction and interference cancellation are utilized. Finally, computer simulations are given to demonstrate the performance of the proposed scheme.