• Corpus ID: 239616057

The Optimal Pilot Power Allocation Strategy for Multi-IRS Assisted Communication Systems

@article{An2021TheOP,
  title={The Optimal Pilot Power Allocation Strategy for Multi-IRS Assisted Communication Systems},
  author={Jiancheng An and Chao Xu and Lu Gan and Chau Yuen and Lajos Hanzo Hanzo},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.11534}
}

• Jiancheng An, Chao Xu, +2 authors L. Hanzo
• Published 22 October 2021
• Computer Science
• ArXiv

Intelligent reflecting surface (IRS) is a promising technology that enables the precise control of the electromagnetic environment in future wireless communication networks. To leverage the IRS effectively, the acquisition of channel state information (CSI) is crucial in IRS-assisted communication systems, which, however, is challenging. In this paper, we propose the optimal pilot power allocation strategy for the channel estimation of IRS-assisted communication systems, which is capable of further improving the achievable rate performance with imperfect CSI. More specifically, first of all, we introduce a multiIRS assisted communication system in the face of practical channel estimation errors. Furthermore, the ergodic capacity with imperfect CSI is derived in an explicit closed-form expression under the singleinput single-output (SISO) consideration, which is dependent on the specific pilot power for estimating different reflection channels. Secondly, we formulate the optimization problem of maximizing the ergodic capacity with imperfect CSI, subject to the constraint of the average uplink pilot power. Thirdly, the method of Lagrange multipliers is invoked to solve the ergodic rate maximizing problem and thus to obtain the optimal pilot power allocation strategy. The resultant pilot power allocation solution suggests allocating more amount of power to the pilots for estimating the weak reflection channels, which is L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/N004558/1, EP/P034284/1, EP/P034284/1, EP/P003990/1 (COALESCE), of the Royal Society’s Global Challenges Research Fund Grant as well as of the European Research Council’s Advanced Fellow Grant QuantCom. J. An and L. Gan are with the School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China. (e-mail: [e-mail]; [e-mail]). C. Xu and L. Hanzo are with the School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, U.K. (e-mail: [e-mail]; [e-mail]). C. Yuen is with the Engineering Product Development (EPD) Pillar, Singapore University of Technology and Design, Singapore 487372 (e-mail: [e-mail]). October 25, 2021 DRAFT