TY - JOUR
T1 - Hybrid LMMSE Transceiver Optimization for Distributed IoT Sensing Networks with Different Levels of Synchronization
AU - Liu, Heng
AU - Wang, Shuai
AU - Gong, Shiqi
AU - Zhao, Nan
AU - An, Jianping
AU - Quek, Tony Q.S.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - In this article, we investigate the analog-digital hybrid transceiver optimization for distributed Internet-of-Things (IoT) sensing networks consisting of a multiantenna fusion center (FC) and several multiantenna sensor nodes. Analog-digital hybrid transceiver is an economic way to realize tradeoffs between hardware cost and performance for multiantenna communications. Under the nonconvex unit modulus constraints and transmit power constraint at each sensor, two synchronization schemes are considered for the hybrid linear minimum mean-square error (LMMSE) transceiver optimization. First, a centralized algorithm is proposed, in which the hybrid transceivers are computed at the FC. Based on the framework of alternating direction method of multipliers (ADMMs), the unit modulus constraints can be satisfied by projecting the elements of analog transceivers onto the unit modulus circle. However, the centralized algorithm usually suffers from strict synchronous requirements and high communication overhead. In order to accommodate the inevitable computing and communication delays in distributed IoT sensing networks, an asynchronous distributed ADMM (AD-ADMM) algorithm is proposed. By using the aged information, the hybrid transceivers are computed at the sensors without the coordination of the FC. Thus, the AD-ADMM algorithm can greatly reduce the computation overhead of the FC and improve the scalability of IoT sensing networks. Simulation results are presented to show that both the centralized ADMM and AD-ADMM algorithms perform closely to the fully digital counterpart.
AB - In this article, we investigate the analog-digital hybrid transceiver optimization for distributed Internet-of-Things (IoT) sensing networks consisting of a multiantenna fusion center (FC) and several multiantenna sensor nodes. Analog-digital hybrid transceiver is an economic way to realize tradeoffs between hardware cost and performance for multiantenna communications. Under the nonconvex unit modulus constraints and transmit power constraint at each sensor, two synchronization schemes are considered for the hybrid linear minimum mean-square error (LMMSE) transceiver optimization. First, a centralized algorithm is proposed, in which the hybrid transceivers are computed at the FC. Based on the framework of alternating direction method of multipliers (ADMMs), the unit modulus constraints can be satisfied by projecting the elements of analog transceivers onto the unit modulus circle. However, the centralized algorithm usually suffers from strict synchronous requirements and high communication overhead. In order to accommodate the inevitable computing and communication delays in distributed IoT sensing networks, an asynchronous distributed ADMM (AD-ADMM) algorithm is proposed. By using the aged information, the hybrid transceivers are computed at the sensors without the coordination of the FC. Thus, the AD-ADMM algorithm can greatly reduce the computation overhead of the FC and improve the scalability of IoT sensing networks. Simulation results are presented to show that both the centralized ADMM and AD-ADMM algorithms perform closely to the fully digital counterpart.
KW - Alternating direction method of multipliers (ADMMs)
KW - Internet of Things (IoT)
KW - asynchronous distributed optimization
KW - hybrid transceiver optimization
UR - http://www.scopus.com/inward/record.url?scp=85099232054&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2021.3049384
DO - 10.1109/JIOT.2021.3049384
M3 - Article
AN - SCOPUS:85099232054
SN - 2327-4662
VL - 8
SP - 14458
EP - 14470
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 19
ER -