With the capability to configure wireless propagation environment, reconfigurable intelligent surface (RIS) has attracted wide attention from both academia and industry, in which measurement campaign of RIS in commercial networks is of great importance for performance evaluation. However, existing RIS configuration schemes in practical environments are generally angle-based which require accurate angle information and mainly consider single incident beam, or statistical methods with high sampling overhead. In this paper, we propose a phase shift design scheme for RIS referred to as multiple incident beam superposition (MIBS) scheme, which can be applied in scenarios with incident signals on the RIS from multiple directions. Instead of utilizing random sampling, the proposed scheme firstly employs an incident beam scanning process to extract the incident beam information by pre-calculated codebook to reduce sampling cost, and requires no complex channel estimation or prior channel information. Then the proposed scheme concentrates the incident beams toward the desired reflection direction through a phase shift superposition algorithm. Numerical simulations verify the excellent performance and a 90% sample reduction of the proposed scheme compared with existing methods under the condition of 1-bit RIS hardware for practical applications. Furthermore, a measurement campaign in 5G commercial networks is conducted to validate the advantages of the proposed MIBS scheme in optimizing crucial signal metrics, yielding a 6.76 dB RSRP gain, a 4.9 dB SINR gain and a 37% throughput improvement, showing great potential of RIS for coverage enhancement.

Reconfigurable intelligent surface (RIS) is a promising technology for 6G wireless communication. To learn from former successful deployed technique, a mature and widely deployed solution in 5G networks, the repeater, is a subject worth comparing. This paper presents a comparative study of RIS and commercial repeater through field trials in a typical indoor parking lot scenario. By providing empirical insights rather than algorithmic contributions, the study focuses on assessing their performance in terms of coverage, signal quality, and deployment characteristics. Field trials were conducted to measure key metrics such as reference signal received power (RSRP) and signal-to-interference-plus-noise ratio (SINR) under both point and area coverage scenarios. The results reveal that RIS achieves localized coverage improvements with enhanced signal reflection, whereas repeater excels in wide-area coverage through cascaded digital remote units (DRUs). The findings highlight the distinct advantages and limitations of each technology, providing practical insights for their deployment in indoor environments.

As a candidate technique to achieve sixth-generation wireless communication (6G), reconfigurable intelligent surface (RIS) has become popular in both academia and industry. For better exploration of the advantages of RIS, we compare the performances of RIS and network-controlled repeater (NCR) in 3GPP release-18. We first theoretically analyze the received signal power and signal-to-noise ratio performances for both RIS and NCR. Then, we simulate the reference signal received power and signal-to-interference-and-noise ratio performances at the system level for both RIS and NCR in the frequency range 1 and frequency range 2 bands. Finally, several insights on engineering applications are given based on the comparison between RIS and NCR.

Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node. By smartly reconfiguring the electromagnetic (EM) properties of the metasurface and adjusting the EM parameters of the reflected radio waves, RIS can turn the uncontrollable propagation environment into an artificially reconfigurable space, and thus, can significantly increase the communications capacity and improve the coverage of the system. In this paper, we investigate the far field channel in which the line-of-sight (LOS) propagation is dominant. We propose an antenna model that can characterize the radiation patterns of realistic RIS elements, and consider the signal power received from the two-hop path through RIS. System-level simulations of network performance under various scenarios and parameter configurations are performed, which show significant gain of RIS.

Reconfigurable intelligent surface (RIS) is an emerging technique employing metasurface to reflect the signal from the source node to the destination node. Essentially, RIS can be considered as a passive relay between the source and destination node. By contrast, relay node in a traditional network has to be active, consuming energy when it is relaying the signal or information. It is worth investigating the differences between RIS and relay. In this paper, we compare the performances between RIS and active relay for a general multiple-input multiple-output (MIMO) system. To make the comparison fair and comprehensive, both the performances of RIS and active relay are optimized with best-effort, by formulating a non-convex optimization problem respectively. In case of RIS, transmit beamforming and reflecting coefficients are jointly optimized. In case of active relay including half-duplex relay and full-duplex relay, transmit beamforming for both source and relay are optimized. The original nonconvex optimization problems are transformed into to a weighted mean-square error (MSE) minimization problem and solved by the proposed alternating optimization algorithm, respectively. Numerical results are presented to demonstrate the validity of the proposed algorithm.

In this paper, we propose the robust transmission design for an intelligent reflecting surface (IRS) aided distributed multi-antenna system under imperfect cascaded channel state information at transmitter (CSIT). The active transmit beamforming at access points and reflection coefficients at IRS are jointly optimized to maximize the worst-case sum rate subject to the transmit power constraint and unit-modulus reflection coefficients for all possible channel realizations in the uncertainty region. We propose the conservative approximation (CA) based robust optimization. Under the framework of alternative optimization algorithm, the transmit beamforming is first solved via weighted minimum mean square error method with the fixed reflection coefficients, and then the reflection coefficients are optimized via nearest point projection method. Since the CA method can introduce the rate saturation for non-scaling CSIT as signal-to-noise ratio scales, we investigate another robust optimization algorithm, cutting-set (CS) method, which solves the problem by alternating between an optimization step for a finite subset of the uncertainty region, and a pessimization step for updating the subset. The numerical simulation results illustrate that the CS method can reap better sum-rate performance than CA, and the deleterious effect of imperfect cascaded CSIT on the performance becomes more significant with the increase of the reflecting elements.