Abstract-Machine-type communication services in mobile cellular systems are currently evolving with an aim to efficiently address a massive-scale user access to the system. One of the key problems in this respect is to efficiently identify active users in order to allocate them resources for the subsequent transmissions. In this paper, we examine two recently suggested approaches for user activity detection: compressed-sensing (CS) and coded slotted ALOHA (CSA), and provide their comparison in terms of performance vs resource utilization. Our preliminary results show that CS-based approach is able to provide the target user activity detection performance with less overall system resource utilization. However, this comes at a price of lower energyefficiency per user, as compared to CSA-based approach.
In REF , two approaches, compressed sensing technique and coded slotted ALOHA, are compared in terms of detection accuracy and energy efficiency in user activity detection.
User activity detection in massive random access: Compressed sensing vs. coded slotted ALOHA
2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Computer Science Mathematics