Tagged preambles based novel cellular random access schemes

Abstract

Cellular Internet of Things (IoT) and machine-to-machine (M2M) communications have recently received considerable attention as major candidate technologies to develop a hyper-connected society. Among various research issues in cellular IoT/M2M communications, cellular random access (RA) is one of active research areas since the RA is a starting mechanism to communicate between each node and eNodeB. However, the conventional RA mechanism may reveal critical limitations for supporting a significantly large number of nodes, low-latency services, and ultra reliability in the fifth generation (5G) cellular networks. Therefore, in this dissertation, we first propose a novel concept of tagged preambles, which can deliver additional information with its own preamble index at the first step of the RA procedure. We address various features of the proposed tagged preambles and their detection method. Moreover, we propose a tagged preambles based random access mechanism in order to innovate the current cellular RA system. Then, the proposed tagged preambles based RA mechanism plays important roles in the following novel cellular RA schemes. In the first technical issue, we propose an `early preamble collision detection (e-PACD) scheme' for reliable and low-latency random access. The proposed e-PACD scheme enables faster preamble collision detection based on tagged preambles at the first step of the RA procedure and faster collision notification at the second step of the RA procedure, compared to the conventional preamble collision detection, which is done at the third step of the RA procedure and the conventional collision notification, which is done at the fourth step of the RA procedure. As a result, the proposed e-PACD scheme effectively enables us to avoid resource wastes on physical uplink shared channel (PUSCH) since the proposed e-PACD scheme disables nodes with collided preambles to proceed the remaining third and fourth steps of the RA procedure. In the second technical issue, we propose a `preamble collision resolution (PACR) scheme' based on captured multiple timing advance (TA) values for a massive number of TA-aware machine nodes. In the proposed PACR scheme, each of TA-aware nodes can obtain its exclusive PUSCH resources for the third step of the RA procedure by comparing both of its transmitted PA index and its own TA value with those in RA response (RAR) messages. As a result, the proposed PACR scheme can significantly improve the RA success probability and reduce the RA delay. In the third technical issue, we propose a `message-embedded random access (MERA) scheme' for small-sized data transmissions. The proposed MERA scheme can deliver short message bits based on message-embedded preambles at the first step of the RA procedure. Since the proposed MERA scheme does not require any resource scheduling mechanisms and extra resources on PUSCHs but only utilizes physical random access channel (PRACH), it is significantly effective to reduce control and signalling overheads and to save radio resources on PUSCH. As a result, the proposed MERA scheme can be utilized for connection-less small-sized data transmission for various IoT/M2M applications. When eNodeB needs to collect a set of data from a significantly large number of machine nodes belonging to a specific group, it may encounter an RA overload or a congestion problem due to a limited number of preamble resources and PUSCH resources in the RA procedure. Thus, in the last technical issue, we propose an `efficient group data collection mechanism (e-GDCM)'. The proposed e-GDCM effectively adjusts an access class barring (ACB) factor by considering both of the number of available preambles and the number of available PUSCH resources, and manage the RAs from a group of machine nodes by using a distinct group root number for their exclusive preamble transmissions. As a result, the comprehensive result of the proposed e-GDCM can give network operators an insight into effectively collecting a set of group data for various cellular IoT/M2M communication applications.