李亦卿
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Personal Information
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Date of Birth:
1993-06-01 -
Date of Employment:
2022-07-12 -
School/Department:
计算机学院 -
Gender:
Female -
Status:
On-the-job -
Teacher College:
School of Computer Science
Other Contact Information:
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Telephone:
34687a723eac0ff313e12e1c64d548b24049657e0822725911fd49c4d7e0e045de94f690f8c37dd615b2a231b0f4847ecf20bb716285bf38df482aa5aad5ef328382ebb5f545a96834645e2bef6d4615375af90c3672a5cbe989e4ea08ca6fa10b52c9e99cd7662d76d9ca28403b70616f778f610c6355fb53f5f18d0ff33949 -
Email:
7c15073ef83d586dff621380cf9eacbec4b3b23278f2bfd50ced17d3db6f84c91f3d93520204c62d47e6c6d0c0dba138c17dd050e755a10854f78da7035deaeaa558e1bb20387c9f8ae13fb5ab6cfd953aade14f6fb956e05fe35fffece1468e934c71093d919d2da740badbc12e00b398185bd189b79c881b804e8c6804f5d1
Paper Publications
Current position: Home > Scientific Research > Paper Publications
Achievable Rate Region Maximization in Intelligent Reflecting Surfaces-Assisted Interference Channel
- Release time:2022-09-01
- Hits:
Impact Factor:
6.239DOI number:
10.1109/TVT.2021.3120308Journal:
IEEE Transactions on Vehicular TechnologyAbstract:
In the achievable rate region maximization for intelligent reflecting surfaces (IRSs)-assisted interference channel (IFC), where more than one pair of transceivers communicates and interferes with each other simultaneously. Specifically, we optimize the transmit power and passive beamforming vectors at all the IRSs to obtain the Pareto boundary of the achievable rate region in IFC, subject to the unit-modulus constraints for the passive beamforming vectors at the IRSs and transmit power budgets at the transmitters. To solve the formulated non-convex optimization problem efficiently, we resort to optimize each variable alternatively until convergence. The optimization of transmit power is based on a locally optimal fixed-point iteration method. Instead of using the conventional high-complexity and sub-optimal Gaussian randomization-aided semi-definite relaxation (SDR) technique for the passive beamforming design, we first propose a novel locally optimal homotopy optimization based majorization-minimization method. To further reduce the computational complexity, a locally optimal log-sum-exp approximation based manifold optimization method is also proposed. Simulation results validate that our proposed methods can significantly decrease the computational complexity and outperform the conventional SDR-based algorithm.Co-author:
zhangguangchi,cuimiaoFirst Author:
jmiaoCorrespondence Author:
Li YiqingDiscipline:
EngineeringFirst-Level Discipline:
Information and Communication EngineeringDocument Type:
JVolume:
70Issue:
12Page Number:
13406–13412ISSN No.:
1939-9359Translation or Not:
noDate of Publication:
2021-12-01Included Journals:
SCILinks to published journals:
https://ieeexplore.ieee.org/document/9576566