# Preamble Design and Collision Resolution in a Massive Access IoT System
## 2 Related Work  
In the literature, performance improvement for massive access IoT systems is usually carried out from two aspects, i.e., cross-layer resource optimization and physical layer design.  
On cross-layer resource optimization, researchers usually focused on performance optimization in terms of throughput, latency, and capacity. In [7], a throughput-oriented non-orthogonal random access (NORA) scheme was proposed to improve the access throughput for IoT networks by employing the technique of tagged preambles. With this, multiple devices shared the same physical uplink shared channel (PUSCH) for transmissions by multiplexing in the power domain. [PERSON] et al. proposed a hybrid NORA and data transmission scheme to address the signalling overhead and resource allocation problems of IoT with non-orthogonal multiple access [8]. A relaying threshold-based random access and data transmission scheme for grouped IoT networks was proposed in [9]. Except for throughput optimization in [7; 8; 9], [PERSON] et al. proposed an access class barring mechanism to accommodate heterogeneous IoT devices with different quality of service (QoS) requirements based on deep reinforcement learning algorithm in [10]. Additionally, a multi-slot pilot allocation scheme with unequal access latency protection for user equipments (UEs) was studied in [11]. The two solutions proposed in [10; 11] devoted to reduce the latency in IoT networks. Moreover, in [12], the receiver is designed for the uplink transmission of a massive MIMO system to improve network access gain, where human-type communications and IoT communications coexisted.  
On physical layer design, researchers usually focus on collision resolution. In [16], the multivariate Bernoulli model which exhibited the distributions of pilot states was proposed. With this, general correlation among device activities and relationship among the states of pilots assigned to one device could be specified. [PERSON] et al. proposed a protocol which implemented multi-user detection and channel estimation by compressed sensing technology [17]. This protocol ensured that multiple collided packets could be recovered in one single time slot with low signaling overhead. The estimation of round-trip delays of multiple signals in NORA based on the maximum likelihood criterion was studied to assist the detection of collision in an IoT network [18]. Additionally, a contention control method that regulated the number of devices competing simultaneously for the RA channel was studied in a distributed manner [19]. Moreover, an RA scheme was proposed in [20], which introduced virtual preambles and associated them with RA channel indexes to discern multiple low-cost IoT devices. Works [16; 17; 18; 19; 20] all devoted to collision probability reduction. However, there was little attention on preamble collision in the physical layer of IoT. Please note that preamble detection is the prime of a successful random access.  
Recently, preamble collision resolution was studied under the assumption that the TA values of the IoT devices were fixed [15]. Specifically, the TA value of each device was unique and the colliding devices could be discerned by the gNB. However, as the number of available preambles was finite, the scheme proposed in [15] was not applicable to the massive access scenario. Therefore, how to reduce preamble collision is still a challenge for an IoT system where huge amount of devices request access simultaneously, which motivates this paper.