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Volume 43 Issue 12
Dec.  2021
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Yongjun XU, Hao XIE, Qianbin CHEN, Qilie LIU. Beamforming Algorithm for MIMO-based Heterogeneous Networks with Hardware Impairments[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3571-3579. doi: 10.11999/JEIT200776
Citation: Yongjun XU, Hao XIE, Qianbin CHEN, Qilie LIU. Beamforming Algorithm for MIMO-based Heterogeneous Networks with Hardware Impairments[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3571-3579. doi: 10.11999/JEIT200776

Beamforming Algorithm for MIMO-based Heterogeneous Networks with Hardware Impairments

doi: 10.11999/JEIT200776
Funds:  The National Natural Science Foundation of China (61601071, 62071078), Natural Science Foundation of Chongqing (cstc2019jcyj-xfkxX0002), The Graduate Scientific Research Innovation Project of Chongqing (CYS20253, CYS20251), The Chongqing Science and Technology Innovation Leading Talent Support Program (CSTCCXLJRC201908), The Basic and Advanced Research Projects of CSTC (2019jcyj-zdxmX0008)
  • Received Date: 2020-09-01
  • Rev Recd Date: 2021-09-22
  • Available Online: 2021-10-27
  • Publish Date: 2021-12-21
  • Multiple-Input Multiple-Output (MIMO)-based Heterogeneous Network (HetNet) can improve system capacity and achieve more connectivity, which is dramatically concerned by academia and industry. Therefore, it becomes one of the key technologies in the next-generation communication system. However, due to the effect of factors such as amplifier nonlinearities, phase noise, and I/Q imbalance, these impairments become the bottlenecks for further improving the performance of beamforming in MIMO-based HetNets. In order to solve this problem, this paper studies the beamforming design in MIMO-based HetNets by considering hardware impairments ahead of time. Firstly, the resource allocation problem is formulated as the total transmit power minimization of the system with hardware impairments under the constraints of the maximum transmit power of each base station and the minimum signal-to-interference-plus-noise ratio of each user. Then, the original non-convex problem is transformed into an equivalent convex optimization problem by using the methods of the equivalent transformation and the semidefinite programming relaxation. Simulation results verify that the proposed algorithm has a low outage probability and can overcome the impact of hardware impairments by comparing it with the traditional beamforming algorithm with perfect hardware.
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