Ergodic Capacity of Intelligent Omni-Surface-Aided Communication Systems With Phase Quantization Errors and Outdated CSI

In this article, we study the performance of an intelligent omni-surface (IOS)-aided communication system, considering the impacts of actual phase quantization errors and outdated channel state information (CSI). Different from the conventional reflective reconfigurable intelligent surface that can only reflect the incident signals, IOS can offer effective communication service to mobile users via the reflective or the transmissive operation. As for the transmissive scenario, we derive the accurate closed-form ergodic capacity (EC) expressions taking into account the phase quantization errors in both the near- and far-fields. To further obtain practical physical insights, tight upper- and lower-bound expressions for EC are provided. It is found that when the transmit power and the quantization bits are sufficiently large, the EC performance would become saturated due to the existence of outdated CSI. Also, the impacts of the phase quantization errors, the outdated CSI, and channel parameters on the considered system performance are revealed. Furthermore, the correctness of our derived expressions is validated by extensive Monte-Carlo simulation results.

[1]  Shuai Zhang,et al.  On the Study of Reconfigurable Intelligent Surfaces in the Near-Field Region , 2022, IEEE Transactions on Antennas and Propagation.

[2]  Derrick Wing Kwan Ng,et al.  Wireless Energy Transfer in RIS-Aided Cell-Free Massive MIMO Systems: Opportunities and Challenges , 2022, IEEE Communications Magazine.

[3]  Yan Zhang,et al.  Reconfigurable Intelligent Surfaces With Outdated Channel State Information: Centralized vs. Distributed Deployments , 2022, IEEE Transactions on Communications.

[4]  H. Poor,et al.  Intelligent Omni-Surface: Ubiquitous Wireless Transmission by Reflective-Transmissive Metasurface , 2020, 2011.00765.

[5]  Derrick Wing Kwan Ng,et al.  Improving Sum-Rate of Cell-Free Massive MIMO With Expanded Compute-and-Forward , 2021, IEEE Transactions on Signal Processing.

[6]  H. Vincent Poor,et al.  Simultaneously Transmitting and Reflecting (STAR) Intelligent Omni-Surfaces, Their Modeling and Implementation , 2021, 2108.06233.

[7]  Gongpu Wang,et al.  Channel and Phase Shift Estimation for TM-aided OTFS Railway Communications , 2021, 2021 IEEE/CIC International Conference on Communications in China (ICCC Workshops).

[8]  Xiaojun Yuan,et al.  Full-Dimensional Rate Enhancement for UAV-Enabled Communications via Intelligent Omni-Surface , 2021, IEEE Wireless Communications Letters.

[9]  Ying Wang,et al.  Learning-Based Robust and Secure Transmission for Reconfigurable Intelligent Surface Aided Millimeter Wave UAV Communications , 2021, IEEE Wireless Communications Letters.

[10]  Octavia A. Dobre,et al.  Coverage Characterization of STAR-RIS Networks: NOMA and OMA , 2021, IEEE Communications Letters.

[11]  Shashank Shekhar,et al.  Outage Probability Expressions for an IRS-Assisted System With and Without Source-Destination Link for the Case of Quantized Phase Shifts in κ – μ Fading , 2021, IEEE Transactions on Communications.

[12]  Bo Ai,et al.  RIS-Aided Next-Generation High-Speed Train Communications: Challenges, Solutions, and Future Directions , 2021, IEEE Wireless Communications.

[13]  H. Poor,et al.  STAR: Simultaneous Transmission and Reflection for 360° Coverage by Intelligent Surfaces , 2021, IEEE Wireless Communications.

[14]  Derrick Wing Kwan Ng,et al.  Smart and Reconfigurable Wireless Communications: From IRS Modeling to Algorithm Design , 2021, IEEE Wireless Communications.

[15]  A. Al-Dweik,et al.  Capacity Analysis of IRS-Based UAV Communications With Imperfect Phase Compensation , 2021, IEEE Wireless Communications Letters.

[16]  Zhu Han,et al.  Reconfigurable Intelligent Surfaces in 6G: Reflective, Transmissive, or Both? , 2021, IEEE Communications Letters.

[17]  Anas M. Salhab,et al.  Accurate Performance Analysis of Reconfigurable Intelligent Surfaces Over Rician Fading Channels , 2021, IEEE Wireless Communications Letters.

[18]  Derrick Wing Kwan Ng,et al.  Robust and Secure Sum-Rate Maximization for Multiuser MISO Downlink Systems With Self-Sustainable IRS , 2021, IEEE Transactions on Communications.

[19]  Ming Zheng Chen,et al.  Path Loss Modeling and Measurements for Reconfigurable Intelligent Surfaces in the Millimeter-Wave Frequency Band , 2021, IEEE Transactions on Communications.

[20]  Felipe A. P. de Figueiredo,et al.  Large Intelligent Surfaces With Discrete Set of Phase-Shifts Communicating Through Double-Rayleigh Fading Channels , 2020, IEEE Access.

[21]  Octavia A. Dobre,et al.  Towards the Use of Re-configurable Intelligent Surfaces in VLC Systems: Beam Steering , 2020, 2009.06822.

[22]  Lingyang Song,et al.  Beyond Intelligent Reflecting Surfaces: Reflective-Transmissive Metasurface Aided Communications for Full-Dimensional Coverage Extension , 2020, IEEE Transactions on Vehicular Technology.

[23]  Derrick Wing Kwan Ng,et al.  Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User Communications , 2020, IEEE Transactions on Wireless Communications.

[24]  Caijun Zhong,et al.  Performance Analysis of Intelligent Reflecting Surface Aided Communication Systems , 2020, IEEE Communications Letters.

[25]  Mohamed-Slim Alouini,et al.  Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead , 2020, ArXiv.

[26]  Wessam Ajib,et al.  A Comprehensive Study of Reconfigurable Intelligent Surfaces in Generalized Fading , 2020, ArXiv.

[27]  Bo Ai,et al.  Millimeter Wave Communications With Reconfigurable Intelligent Surfaces: Performance Analysis and Optimization , 2020, IEEE Transactions on Communications.

[28]  Xiao Lu,et al.  Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey , 2019, IEEE Communications Surveys & Tutorials.

[29]  Lingyang Song,et al.  Reconfigurable Intelligent Surfaces Assisted Communications With Limited Phase Shifts: How Many Phase Shifts Are Enough? , 2019, IEEE Transactions on Vehicular Technology.

[30]  Qiang Cheng,et al.  Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement , 2019, IEEE Transactions on Wireless Communications.

[31]  Derrick Wing Kwan Ng,et al.  Prospective Multiple Antenna Technologies for Beyond 5G , 2019, IEEE Journal on Selected Areas in Communications.

[32]  Justin P. Coon,et al.  Communication Through a Large Reflecting Surface With Phase Errors , 2019, IEEE Wireless Communications Letters.

[33]  B. Shihada,et al.  What should 6G be? , 2019, Nature Electronics.

[34]  Xiaohu You,et al.  An overview of transmission theory and techniques of large-scale antenna systems for 5G wireless communications , 2016, Science China Information Sciences.

[35]  Victor Adamchik,et al.  The algorithm for calculating integrals of hypergeometric type functions and its realization in REDUCE system , 1990, ISSAC '90.

[36]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

[37]  Zhu Han,et al.  Intelligent Reflective-Transmissive Metasurfaces for Full-Dimensional Communications: Principles, Technologies, and Implementation , 2021, ArXiv.