Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement

Abstract

Reconfigurable intelligent surfaces (RISs) comprised of tunable unit cells have recently drawn significant attention due to their superior capability in manipulating electromagnetic waves. In particular, RIS-assisted wireless communications have the great potential to achieve significant performance improvement and coverage enhancement in a cost-effective and energy-efficient manner, by properly programming the reflection coefficients of the unit cells of RISs. In this paper, free-space path loss models for RIS-assisted wireless communications are developed for different scenarios by studying the physics and electromagnetic nature of RISs. The proposed models, which are first validated through extensive simulation results, reveal the relationships between the free-space path loss of RIS-assisted wireless communications and the distances from the transmitter/receiver to the RIS, the size of the RIS, the near-field/far-field effects of the RIS, and the radiation patterns of antennas and unit cells. In addition, three fabricated RISs (metasurfaces) are utilized to further corroborate the theoretical findings through experimental measurements conducted in a microwave anechoic chamber. The measurement results match well with the modeling results, thus validating the proposed free-space path loss models for RIS, which may pave the way for further theoretical studies and practical applications in this field.

On the Performance of RIS-Assisted Dual-Hop Mixed RF-UWOC Systems

“…By inserting (15) and (30) into (29), and then applying [37,Eqs. (2.8) and (2.57)], the ACC of fixed-gain AF relaying can be derived in closed-form as…”

Joint Transmit Precoding and Reconfigurable Intelligent Surface Phase Adjustment: A Decomposition-Aided Channel Estimation Approach

“…2) Complexity analysis: The computational complexity is mainly contributed by the L rounds of pilot training in (5) and the subchannel estimation in (10). It is easy to verify that the complexity of a single round of pilot training is on the order of O(τ N 2 t ).…”

“…In this section, we deal with the precoding problem purely relying on the knowledge of the subchannels H m , rather than on the full CSI of H t and H r . 10 To circumvent the challenge of finding the closed-form optimal design of the phase shift vector and the digital precoder, we conceive a near-optimal two-stage precoding scheme. Firstly, the phase shift vector is determined using a fixed-point based method, based on which the digital precoder may then be derived by solving a convex optimization problem.…”

“…Upon using the MI metric, no common phase rotation applied to the entries ofμ changes the objective, and the joint precoding design may then be for- 10 Again, the existing precoders rely on the full CSI of Ht and Hr, and hence cannot be directly applied when only the knowledge of the subchannels is available. mulated as the following constrained optimization problem 11 (P2) :…”

“…In practical systems, the optimized phase adjustments provided by the RIS for subchannel estimation can be specified in advance as codebooks at the transceiver. Note that different choices of feasible codebooks do not change the training overhead, but the optimal codebooks given by Corollaries 1 and 2 can be used to minimize the MSE of the estimator, and also to simplify the classic LS algorithm formulated in (10), by letting (AA H ) −1 A = 1 L A. The main procedures of the proposed subchannel estimation method are summarized in Algorithm 1.…”