Throughput-Oriented Non-Orthogonal Random Access Scheme for Massive MTC Networks

Abstract

Machine-type communications (MTC) technology, which enables direct communications among devices, plays an important role in realizing Internet-of-Things. However, a large number of MTC devices can cause severe collisions. As a result, the network throughput is decreased and the access delay is increased. To address this issue, a throughput-oriented non-orthogonal random access (NORA) scheme is proposed for massive machine-type communications (mMTC) networks. Specifically, by employing the technique of tagged preambles (PAs), multiple MTC devices (MTCDs) choosing the same PA can be distinguished and regarded as a non-orthogonal multiple access (NOMA) group, which enables multiple MTCDs to share the same physical uplink shared channel for transmissions by multiplexing in the power domain. The Sukhatme's classic theory and the characteristic function approach are adopted to formulate an optimization problem. The aim is to maximize the throughput subject to the constraints on the power back-off factor, the number of MTCDs included in a NOMA group, and the successful transmission probability. Based on the particle swarm optimization (PSO) algorithm, the formulated optimization problem is efficiently solved. The derived solution can be used to adjust the access class barring factor such that more MTCDs can obtain the access opportunities. Moreover, a lowcomplexity suboptimal solution is also developed, which can achieve near-PSO performance under high data rate requirement. Simulation results show that the proposed scheme can efficiently improve the network performance and comparison is made with the existing schemes. Index Terms-Massive machine-type communications (MTC) networks, non-orthogonal random access, power back-off.

A Successive Interference Cancellation Based Random Access Channel Mechanism for Machine-to-Machine Communications in Cellular Internet-of-Things

“…Then, the optimal throughput has been achieved at the connection phase using the estimated load [29]. A throughput oriented non-orthogonal random access scheme has been proposed in [30] that employs tagged preambles technique. With this technique, multiple devices choosing the same preamble can be identified as a non-orthogonal multiple access group.…”

“…With this technique, multiple devices choosing the same preamble can be identified as a non-orthogonal multiple access group. This enables the multiple devices to share the same PRACH by multiplexing in the power domain [30]. In [31], a compressive random access (CRA) scheme has been studied along with the conventional CRA-based random access scheme for M2M communication.…”

“…Moreover, the number of devices that are successful with both intra-slot and inter-slot SIC also increases with the slot number. Thus, the total number of RACH successes for the proposed mechanism increases Mechanism Parameter Value 3GPP-EAB [7] Average throughput 37% FRM [8] Average throughput 37% QDAM [12] Average throughput 91.67% Access delay M-ACB [13] Success rate 86% Time delays 1250 TDIA [14] Probability of successful 98% preamble transmission CBGP [15] Successful access probability 0.75 Average access delay 7000 SACB [23] Average access delay 500 EH-based ACB [26] Throughput 75% Preamble barring [29] Success probability 0.37 Normalized throughput 37% T-NORA [30] Average throughput Average access delay 2000 CRA [31] Normalized throughput 63% GF protocol [37] Success probability 0.8 NORA [4] Successful access probability 0.48 Average throughput 48% Average access delay 498 SIC-based RACH [6] Successful access probability 0. exponentially with the slot number and maximum can be attained at the last slot of the radio frame as observed in Fig. 7 (b).…”

Preamble Design and Collision Resolution in a Massive Access IoT System

“…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.…”

“…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.…”