TY - JOUR
T1 - Wireless information and energy transfer in MIMO communication with interference channels
AU - Luo, Xiaomei
AU - Li, Hang
AU - Wang, Xiangfeng
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2018
Y1 - 2018
N2 - In this paper, we consider a wireless information and energy transfer (WIET) system, which consists of multiple information transmitter-receiver pairs, and multiple additional energy transmitters to improve the energy transfer. For such a new WIET system, we investigate the energy efficiency (EE) under two different setups, respectively: the information transmitters and energy transmitters use the same and different frequency bands. For each setup, we propose a novel centralized beamformer design method to solve the EE maximization problem, which can be transformed into a convex optimization problem using semidefinite relaxation (SDR) technique. Moreover, we develop a distributed optimization algorithm to solve the SDR approximation formulation for each setup. Simulation results show that the same frequency setup can achieve larger EE value and less computational complexity, however, suffering from lower sum rate. For each setup, the distributed scheme has slightly worse performance than the centralized one, while enjoys less computational complexity, especially when the number of the additional energy transmitters is large.
AB - In this paper, we consider a wireless information and energy transfer (WIET) system, which consists of multiple information transmitter-receiver pairs, and multiple additional energy transmitters to improve the energy transfer. For such a new WIET system, we investigate the energy efficiency (EE) under two different setups, respectively: the information transmitters and energy transmitters use the same and different frequency bands. For each setup, we propose a novel centralized beamformer design method to solve the EE maximization problem, which can be transformed into a convex optimization problem using semidefinite relaxation (SDR) technique. Moreover, we develop a distributed optimization algorithm to solve the SDR approximation formulation for each setup. Simulation results show that the same frequency setup can achieve larger EE value and less computational complexity, however, suffering from lower sum rate. For each setup, the distributed scheme has slightly worse performance than the centralized one, while enjoys less computational complexity, especially when the number of the additional energy transmitters is large.
KW - Wireless information and energy transfer
KW - alternating direction method of multipliers
KW - distributed scheme
KW - semidefinite relaxation
UR - https://www.scopus.com/pages/publications/85055675378
U2 - 10.1109/ACCESS.2018.2877267
DO - 10.1109/ACCESS.2018.2877267
M3 - 文章
AN - SCOPUS:85055675378
SN - 2169-3536
VL - 6
SP - 65845
EP - 65861
JO - IEEE Access
JF - IEEE Access
M1 - 8502928
ER -