Analysis and Optimization for RIS-Aided Multi-Pair Communications Relying on Statistical CSI

This article studies a reconfigurable intelligent surface (RIS)-aided cell-free massive multiple-input multiple-output system and formulate the max–min fairness problem that maximizes the minimum achievable rate among all the users by jointly optimizing the transmit beamforming at access points and the phase shifts at RISs. To address such a challenging problem, we first study the special single-user scenario and propose an algorithm that can transform the optimization problem into a semidefinite program (SDP) or an integer linear program for the cases of continuous or discrete phase shifts, respectively. Then, in order to solve the optimization problem for the multiuser scenario with continuous phase shifts, we propose an alternating optimization algorithm, which can alternately transform the problem into a second-order-cone program and an SDP. Finally, for the multiuser scenario with discrete phase shifts, we design a zero-forcing-based successive refinement algorithm, which can find the suboptimal transmit beamforming and phase shifts by means of alternating optimization. Numerical results show that compared with the benchmark schemes of random phase shifts and without using the RIS, the proposed algorithms can significantly increase the minimum achievable rate. It is also demonstrated that, compared with the case of programming continuous phase shifts, using 2-bit discrete phase shifts can practically achieve the same performance.

Active reconfigurable intelligent surface (RIS) is deemed a prospective candidate to compensate the double fading attenuation caused by the passive RIS, where each element can reflect and amplify the received signals through its low power integrating amplifiers. This paper investigates the physical layer security (PLS) for a non-orthogonal multiple access (NOMA) system through a deployed active RIS to defend multiple eavesdroppers (Eves), where the practical discrete RIS phase shift designs are taken into account. To characterize the secrecy performance, analytical expressions of secrecy outage probability (SOP) and effective secrecy throughput (EST) for an active RIS assisted NOMA (RIS-NOMA) system are derived based on heuristic approximations, which is in consideration of two scenarios with and without direct links. Furthermore, secrecy diversity orders are attained based on theoretical results, of which the convergence rates and gaps between the discrete and continuous phase shifting are further evaluated. The results reveal that a 4-bit quantization can achieve the secrecy diversity order of continuous phase shifts. Numerical results are furnished to corroborate the analyses, and illustrate that the security performance for active RIS-NOMA outperforms the passive RIS-NOMA and conventional cooperation communications under the same total power consumption. The impacts of phase quantization bit, amplification factor and the number of Eves as well as reflective elements on security performance are also substantiated by simulations.

In this letter, we study the robust beamforming design for the reconfigurable intelligent surface (RIS)-assisted communication systems from a multi-antenna access point (AP) to a single-antenna user under imperfect channel state information (CSI), where the RIS has only a finite number of phase shifts at each element. In particular, considering the cascaded AP-RIS-user channel estimation error, we aim to jointly optimize the transmit beamforming at the AP and discrete phase shifts of RIS to minimize the transmission power of AP, subject to a signal-to-noise ratio constraint at the user. To tackle the non-convex optimization problem, we decouple it into two subproblems and propose a novel alternative optimization framework. More specifically, the robust beamforming of AP is first obtained through S-Procedure and semidefinite relaxation. Then we recast the discrete phase shift constraint at RIS into an equivalent convex one, and propose an efficient algorithm to obtain a near optimal solution. Finally, the two subproblems are iteratively optimized to obtain joint robust beamforming. Simulation results show that the proposed scheme can approach the performance of the perfect CSI counterpart and substantially outperform traditional non-robust methods.

In this paper, we explore the use of reconfigurable intelligent surface (RIS) in unmanned aerial vehicle (UAV) based multiuser downlink communications, where a flying UAV serves multiple single antenna users through multiple RISs mounted on various buildings. More specifically, we consider the selection of RISs based on the outdated and imperfect channel state information (CSI) of the composite UAV-RIS-User channels at the UAV. After selection process, the UAV communicates to the user via the selected RISs and also with the direct link. Particularly, we derive an infinite series based expression for selection probability of RISs under both the outdated and imperfect CSI of composite channels based selection scheme. We also derive the statistical distribution of instantaneously received signal-to-noise ratio (SNR) under outdated and imperfect CSI conditions of both the direct and composite links at the user. Next, using the derived statistics, we analyze the network’s performance in terms of the average coverage probability (ACP) and average bit error rate (ABER) over the complete UAV flight time. Moreover, we discuss the behavior of ACP and ABER for very small and very large values of UAV transmit power, respectively. It is depicted through numerical results that selecting more RISs from a group of small-sized RISs may not be as advantageous as selecting fewer RISs from a group of large-sized RISs. Moreover, we also demonstrate the effect of several system parameters such as number of RIS reflecting elements, number of selected RISs, the severity of UAV-RIS and RIS-User links, and the severity of imperfect and outdated CSI on the network’s performance. The analytical results are corroborated with Monte-Carlo simulations.

Reconfigurable intelligent surfaces (RISs) represent a pioneering technology to realize smart electromagnetic environments by reshaping the wireless channel. Jointly designing the transceiver and RIS relies on the channel state information (CSI), whose feedback has not been investigated in multi-RIS-assisted frequency division duplexing systems. In this study, the limited feedback of the RIS-assisted wireless channel is examined by capitalizing on the ability of the RIS in channel customization. By configuring the phase shifters of the surfaces using statistical CSI, we customize a sparse channel in rich-scattering environments, which significantly reduces the feedback overhead in designing the transceiver and RISs. Since the channel is customized in terms of singular value decomposition (SVD) with full-rank, the optimal SVD transceiver can be approached without a matrix decomposition and feeding back the complete channel parameters. The theoretical spectral efficiency (SE) loss of the proposed transceiver and RIS design is derived by considering the limited CSI quantization. To minimize the SE loss, a bit partitioning algorithm that splits the limited number of bits to quantize the CSI is developed. Extensive numerical results show that the channel customization-based transceiver with reduced CSI can achieve satisfactory performance compared with the optimal transceiver with full CSI. Given the limited number of feedback bits, the bit partitioning algorithm can minimize the SE loss by adaptively allocating bits to quantize the channel parameters.

Active reconfigurable intelligent surface (RIS) emerges as an effective technique to resist the double-fading attenuation of passive RIS. By embedding with power harvesting function, it further evolves to zero-power active RIS, which can effectively enhance the flexibility of RIS deployment without external power demand. Nevertheless, existing works neglected the inherent difficulty of channel estimation (CE) for RIS-assisted systems, and the discrete phase shift constraint in practical deployment. In this paper we design a new element-wise RIS architecture and propose a distributed location-aided transmission scheme with low complexity to enhance the reflected gain for channel state information (CSI)-limited RIS-assisted near-field communications. Specifically, the new element-wise RIS provides dynamic element selection capability with low hardware resources. Based on Fresnel diffraction theory, we construct the mapping from locations in space-domain to phase distributions of waves in phase-domain and reveal the priority of elements for harvesting and reflecting. Then, the distributed beamforming design with the phase of determine-then-align is proposed, where the estimation overhead reduction stems from exempted requirements of RIS-associated CE at base station (BS). The asymptotic analysis indicates that the proposed scheme can achieve the optimal gain with a fixed proportion of reflective elements when RIS is large, followed by simulations to verify its superiority to other protocols.

Terahertz (THz) communication is considered to be a pivotal technology in new-generation communication networks. Due to its nature, THz waves attenuate significantly. A blockage will result in a significant power loss, therefore a line-of-sight (LOS) is required. Reconfigurable intelligent surface (RIS) technology is considered to be a promising solution to this problem. In literature, analyses are being done assuming that RIS having lossless reflections and continues phase shifts. In reality, surface reflections differ with the frequency of the incident wave and can have certain phase shifts. Moreover, the design tradeoff between the phase shift range and reflection amplitude should be considered. In this study, a graphene-based RIS has been designed and the communication performance is analyzed using its reflection coefficients and discrete phase shifts.

The incorporation of reconfigurable intelligent surface (RIS) into massive multiple-input-multiple-output (mMIMO) systems can unleash the potential of next-generation networks by improving the performance of user equipments (UEs) in service dead zones. However, their requirement for accurate channel state information (CSI) is critical, and especially, applications with UE mobility that induce channel aging make challenging the achievement of adequate quality of service. Hence, in this work, we investigate the impact of channel aging on the performance of RIS-assisted mMIMO systems under both spatial correlation and imperfect CSI conditions. Specifically, by accounting for channel aging during both uplink training and downlink data transmission phases, we first perform minimum mean square error (MMSE) channel estimation to obtain the UE effective channels with low overhead similar to conventional systems without RIS. Next, we derive the downlink achievable sum spectral efficiency (SE) with regularized zero-forcing (RZF) precoding in closed-form being dependent only on large-scale statistics by using the deterministic equivalent (DE) analysis. Subsequently, we present the attractive optimization of the achievable sum SE with respect to the phase shifts and the total transmit power that can be performed every several coherence intervals due to the slow variation of the large-scale statistics. Numerical results validate the analytical expressions and demonstrate the performance while allowing the extraction of insightful design conclusions for common scenarios including UE mobility. In particular, channel aging degrades the performance but its impact can be controlled by choosing appropriately the frame duration or by increasing the number of RIS elements.

In this letter, we present a reconfigurable intelligent surface (RIS)-assisted space shift keying (SSK) modulation and reflection phase modulation (RPM) scheme, where RIS embeds its own information in the reflection phase shift of the reflected radio frequency (RF) signal. More specifically, the RIS simultaneously performs two tasks: i) reflecting the impinging RF signal with a discrete phase shift and ii) embedding the information bits in the phase shift. We perform joint detection for the RPM and SSK symbols using a maximum likelihood detector, and a unified analytical framework is presented for theoretical analysis of the average bit error rate (ABER) and ergodic capacity of the proposed scheme. All numerical results are thoroughly verified through Monte Carlo simulation. Numerical results reveal that the proposed scheme outperforms the conventional SSK scheme.

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective and promising solution to extend the wireless signal coverage and improve the performance via passive signal reflection. Different from existing works which do not account for the cooperation between RISs or do not provide full space coverage, we propose the marriage of cooperative double-RIS with simultaneously transmitting and reflecting RIS (STAR-RIS) technologies denoted as RIS/STAR-RIS under correlated Rayleigh fading conditions to assist the communication in a massive multiple-input multiple-output (mMIMO) setup. The proposed architecture is superior since it enjoys the benefits of the individual designs. We introduce a channel estimation approach of the cascaded channels with reduced overhead. Also, we obtain the deterministic equivalent (DE) of the downlink achievable sum spectral efficiency (SE) in closed form based on large-scale statistics. Notably, relied on statistical channel state information (CSI), we optimise both surfaces by means of the projected gradient ascent method (PGAM), and obtain the gradients in closed form. The proposed optimization achieves to maximise the sum SE of such a complex system, and has low complexity and low overhead since it can be performed at every several coherence intervals. Numerical results show the benefit of the proposed architecture and verify the analytical framework. In particular, we show that the RIS/STAR-RIS architecture outperforms the conventional double-RIS or its single-RIS counterparts.

Reconfigurable intelligent surface (RIS) technology is a smart way of controlling the radio signal propagation to improve the capacity and coverage of wireless networks. RIS tunes the phase shifts of the incident signals in a dynamic fashion. Channel modeling is an important aspect in RIS-based mmWave communication for the next-generation wireless networks. However, to achieve maximum benefit from RIS-assisted wireless systems, it is essential to provide accurate channel state information (CSI). But, it is very challenging to get accurate CSI because of large number of RIS elements, their passive nature, and the training overhead involved during the channel estimation. To overcome the higher training overhead, in this article we aimed to take advantage of the correlation and sparsity of channels in RIS-assisted channel estimation. The objective of this work is to propose a simplified channel model for the RIS-assisted physical channel of a massive multi-input-multi-output (mMIMO) wireless communication system and analyze its performance in terms of transmitted powers, MIMO configurations, and achievable bit rates. The simulated results proved that the strategic placement of RIS with optimal phase shifts and optimal MIMO configuration can enhance the maximum achievable rate. The achievable rates of the proposed channel modeling are compared with the existing state-of-the-art methods to prove its efficiency. Also, the combination of mMIMO technology along with RIS-assisted communication provides degrees of freedom in terms of signal coverage, energy consumption, and system complexity.

This paper considers an active reconfigurable intelligent surface (RIS)-aided communication system, where an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M$</tex-math></inline-formula> -antenna base station (BS) transmits data symbols to a single-antenna user via an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> -element active RIS. We use two-timescale channel state information (CSI) in our system, so that the channel estimation overhead and feedback overhead can be decreased dramatically. For both the uplink and downlink systems, we derive the closed-form approximate expressions of the achievable rates (ARs) and propose the phase shift optimization schemes. In addition, we compare the performance of the active RIS system with that of the passive RIS system. The numerical results show that the active RIS system achieves a larger AR than the passive RIS system.

Reflective reconfigurable intelligent surface (RIS) technology is regarded as an innovative, cost- and power-effective solution that aims at influencing the wireless channel through controlled scattering. The technology can be realized by using metamaterials and/or resonant elements that scatter electromagnetic waves with a configurable phase shift. Most of the previous work on beamforming techniques for RIS assumes ideal hardware and, thus, continuous phase shifts. However, hardware constraints limit the phase shift resolution, manifested into the amount of discrete phase shifts that can be configured into each RIS element. This paper aims to offer a discrete phase shift beamforming algorithm for reflective RISs that targets minimization of the quantization error resulting from discretization of continuous phase shifts. The beamforming solution proves to be optimal under perfect channel knowledge for any discrete set of uniformly distributed phase shifts. The required complexity to find the optimal beamforming vector for our approach is found to be linear with the number of RIS elements, the minimum needed to obtain optimal results. Simulated behavior is validated by measurements, showing robustness against angle misalignments and distance variations.

Energy efficiency (EE) is one of the most important metrics for the beyond fifth generation (B5G) and the future sixth generation (6G) wireless networks. Reconfigurable intelligent surface (RIS) has been widely focused on EE enhancement for wireless networks because it is power-saving, programmable, and easy to be deployed. However, RIS is generally passive and thus difficult to obtain corresponding full channel state information (CSI), which severely impacts the EE enhancement of RIS-assisted wireless communications. To solve this problem, in this paper we propose the new single-active-antenna combined RIS transmitter structure, which can replace traditional multiple antennas to reduce hardware cost and power consumption. Based on the single-active-antenna combined RIS structure, we develop the Dumb RIS-Assisted Random Beamforming (Darb)-based Joint RIS-Elements and Transmit-power optimizAtion (Jeta) scheme, where dumb RIS randomly changes its phase shift according to isotropic distribution only depending on the CSI feedback from users to RIS-assisted transmitter. Then, we jointly design the number of RIS elements and optimize the transmit power to maximize the EE of RIS-assisted wireless communications. Simulation results show that compared with the traditional multi-antenna system, our developed Darb-based-Jeta scheme can significantly increase the EE without the full CSI.

Reconfigurable Intelligent Surface (RIS) is an emerging technology that can improve the spectrum and energy efficiency of next-generation wireless networks. However, attaining accurate channel state information (CSI) for the cascaded RIS channel is particularly challenging. Imperfect CSI is a major bottleneck to achieving the spectral efficiency benefit of RIS-assisted networks. Rate splitting (RS), a promising multiple access technology, has been shown to be able to achieve an improved spectrum efficiency and be robust to channel uncertainties. This paper investigates the interplay between RIS and RS by considering a RIS-assisted RS beamforming problem. Active beamforming at the base station (BS) and passive beamforming at the RIS are jointly considered to maximize the minimum user rate under both the perfect CSI case and the imperfect CSI case. A block coordinate descent (BCD) algorithm is developed to solve this non-convex problem. Compared with the conventional semi-definite relaxation (SDR) approach, the proposed method does not require that the covariance matrix of the common beamforming vector be rank-one. Moreover, we present theoretical results to help reveal the impact of the system parameters and explain the performance gain resulting from the integration of RIS and RS. Extensive simulation results are also provided to show that RIS-assisted RS can improve the max-min rate performance significantly compared with conventional multiple access technologies, such as non-orthogonal multiple access (NOMA) and space division multiple access (SDMA) with/without RIS, especially in overloaded systems. With the proposed method, RS shows great potential in combating realistic CSI errors in RIS-assisted networks.