# Preamble Design and Collision Resolution in a Massive Access IoT System
## 1 Introduction  
The rapid evolution of the wireless communication technologies are inviting all human beings to the era of the Internet of Everything [1]. The future IoT system is required to guarantee diverse requirements for various applications, such as huge bandwidth, low latency, high reliability, etc. [2, 3]. As a result, huge amount of IoT devices need to access to the wireless networks to exchange data, which brings new challenge to the wireless network design [4]. Specifically, convention network scheduling mechanism is mainly designed for human to human communications that cannot sustain a large amount of simultaneous random access requests, since the preamble resources are quite limited. How to support massive random access for IoT devices consequently becomes a critical issue to realize the future Internet of Everything [5, 6]. In general, existing research focuses on how to optimize the high-layer performance of an IoT system through resource allocations [7, 8, 9, 10, 11, 12]. Such performance metrics include throughput, latency, access capacity, etc. The resource allocation schemes, however, can be realized only if the devices can be access to the IoT system. Hence, random access guarantee is one of the key issues to support massive devices to send data at the same time. Typically, more RA-attempting devices may lead to heavier load and more preamble collisions, which degrades the performance of an IoT system. Thus, it is necessary to design new preamble structure and RA scheme to reduce the congestion for the physical random access channel (PRACH). In the literature, the idea of performance improvement on PRACH can be generalized into three categories, i.e., resource increasing [13], user scheduling [14], andresource reusing [15]. In fact, resource increasing is costly and impractical, since the total resource of an IoT system is usually limited. In addition, preamble collision probability cannot be reduced through user scheduling since the number of preambles in an IoT system is finite. Differently, the idea of resource reusing can allow multiple devices to send identical preambles on the same PRACH, which is applicable to the massive access scenario. However, how to design a preamble structure and an RA scheme to efficiently reuse the PRACH resources for a massive access IoT system is still an open problem. Motivated by this, this paper proposes an effective preamble collision resolution scheme to sustain massive random access for an IoT system. A new preamble structure consisting of the shared sub-preamble and the dedicated sub-preamble is first designed. Based on the new designed preamble, a TA capturing scheme is then proposed to identify multiple devices that send identical sub-preambles to the gBN on the same PRACH. Thereafter, we propose a random access scheme to reduce the preamble collision probability. Furthermore, we prove analytically that the proposed RA scheme can guarantee better performance than the conventional one proposed by the 3 GPP. In addition, the effectiveness of the proposed scheme is validated by the extensive simulations. The contributions of this paper can be summarized as follows. * A new preamble structure is designed, where preamble diversity and location diversity are both acquired. The designed preamble is able to guarantee a much lower preamble collision probability than the conventional preamble designed by 3 GPP with ignorable detection impairment. * A multiple TA capturing scheme is proposed based on the designed preamble. With the idea that the sub-preambles sent by a device suffer from the same channel environment, the TA value of each device can be captured, which can be further used to device identification. * A new random access scheme is proposed and studied analytically. It is verified that the proposed scheme outperforms the conventional scheme in terms of preamble collision probability, RA success probability, etc. Hence, the proposed scheme is more applicable to the IoT systems where massive access is requested.