Asymptotic Optimality of Reconfigurable Intelligent Surfaces: Passive Beamforming and Achievable Rate

Reconfigurable intelligent surfaces (RISs) have recently emerged as a promising technology that can manipulate the properties of an incident wave, such as the frequency, amplitude, and phase, without the need for complex signal processing. In this paper, the asymptotic optimality of achievable rate in a downlink RIS system is analyzed under a practical RIS environment with its associated limitations. In particular, a passive beamformer that can achieve the asymptotic optimal performance by controlling the incident wave properties is designed, under practical reflection coefficients. In order to increase the achievable system sum-rate, a modulation scheme that can be used in an RIS without interfering with existing users is proposed and its average symbol error rate is asymptotically derived. Simulation results show that the proposed schemes are in close agreement with their upper bounds in presence of a large number of RIS reflecting elements thereby verifying that the achievable rate in practical RISs satisfies the asymptotic optimality.

[1]  Walid Saad,et al.  A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems , 2019, IEEE Network.

[2]  David Wetherall,et al.  Ambient backscatter: wireless communication out of thin air , 2013, SIGCOMM.

[3]  Tie Jun Cui,et al.  Information metamaterials and metasurfaces , 2017 .

[4]  Shi Jin,et al.  Programmable metasurface‐based RF chain‐free 8PSK wireless transmitter , 2019, Electronics Letters.

[5]  Walid Saad,et al.  Performance Analysis of Large Intelligent Surfaces (LISs): Uplink Spectral Efficiency and Pilot Training , 2019, ArXiv.

[6]  Walid Saad,et al.  Performance Analysis of Large Intelligent Surfaces (LISs): Asymptotic Data Rate and Channel Hardening Effects , 2018, IEEE Transactions on Wireless Communications.

[7]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[8]  Shi Jin,et al.  Wireless communications with programmable metasurface: Transceiver design and experimental results , 2018, China Communications.

[9]  Walid Saad,et al.  Reliability Analysis of Large Intelligent Surfaces (LISs): Rate Distribution and Outage Probability , 2019, IEEE Wireless Communications Letters.

[10]  Choong Seon Hong,et al.  On the Optimality of Reconfigurable Intelligent Surfaces (RISs): Passive Beamforming, Modulation, and Resource Allocation , 2019, IEEE Transactions on Wireless Communications.

[11]  Chau Yuen,et al.  Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimization , 2019, ICC 2020 - 2020 IEEE International Conference on Communications (ICC).

[12]  Erik G. Larsson,et al.  Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems , 2011, IEEE Transactions on Communications.

[13]  Mohamed-Slim Alouini,et al.  Wireless Communications Through Reconfigurable Intelligent Surfaces , 2019, IEEE Access.