TY - JOUR
T1 - Massive machine-to-machine communications in cellular network
T2 - Distributed queueing random access meets MIMO
AU - Yuan, Jiantao
AU - Shan, Hangguan
AU - Huang, Aiping
AU - Quek, Tony Q.S.
AU - Yao, Yu Dong
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2017
Y1 - 2017
N2 - Machine-type communications are emerging as a new paradigm for enabling a broad range of applications from the massive deployment of sensor devices to mission-critical services. To support massive machine-to-machine (M2M) communications with delay constraints in cellular networks, we design an efficient random access and data transmission system known as distributed queueing random access-multiple-input multiple-output (DQRA-MIMO) data transmission system. This system has the advantages of both efficient collision resolution of DQRA protocol and the efficient data transmission of MIMO technology. To obtain higher throughput under delay constraint and limited time-frequency resources, we match the ability of collision resolution with the capability of MIMO transmission by optimally configuring system parameters. The closed-form expression of throughput is derived, which is a function of the total user equipments' traffic arrival rate, average packet number of each arrival, number of base station antennas, and number of access request (AR) slots. An optimization problem is formulated to maximize the throughput to obtain the optimal number of AR slots given a certain delay constraint for M2M traffic. Numerical and simulation results reveal that, for a given requirement of average delay, the proposed optimized DQRA-MIMO system, which dynamically adjusts time-frequency resource division to maximize throughput, can provide a higher throughput than that of a baseline approach.
AB - Machine-type communications are emerging as a new paradigm for enabling a broad range of applications from the massive deployment of sensor devices to mission-critical services. To support massive machine-to-machine (M2M) communications with delay constraints in cellular networks, we design an efficient random access and data transmission system known as distributed queueing random access-multiple-input multiple-output (DQRA-MIMO) data transmission system. This system has the advantages of both efficient collision resolution of DQRA protocol and the efficient data transmission of MIMO technology. To obtain higher throughput under delay constraint and limited time-frequency resources, we match the ability of collision resolution with the capability of MIMO transmission by optimally configuring system parameters. The closed-form expression of throughput is derived, which is a function of the total user equipments' traffic arrival rate, average packet number of each arrival, number of base station antennas, and number of access request (AR) slots. An optimization problem is formulated to maximize the throughput to obtain the optimal number of AR slots given a certain delay constraint for M2M traffic. Numerical and simulation results reveal that, for a given requirement of average delay, the proposed optimized DQRA-MIMO system, which dynamically adjusts time-frequency resource division to maximize throughput, can provide a higher throughput than that of a baseline approach.
KW - Machine-to-machine communications
KW - collision resolution
KW - distributed queueing
KW - multiple-input multiple-output (MIMO)
KW - random access
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U2 - 10.1109/ACCESS.2017.2670614
DO - 10.1109/ACCESS.2017.2670614
M3 - Article
AN - SCOPUS:85018515013
VL - 5
SP - 2981
EP - 2993
JO - IEEE Access
JF - IEEE Access
M1 - 7857734
ER -