This paper investigates a symbiotic radio (SR) system composed of a multi-antenna radio frequency (RF) source, a backscatter device (BD), and a receiver. SR is an energy- and spectrum-efficient technology with great potential to enable passive Internet of Things (IoT). However, due to the double path loss in the reflecting link, the received BD signal is typically much weaker than the received RF source signal. As the dynamic range (DR) of the analog-to-digital converter (ADC) at the receiver is limited, it is challenging to recover the weak BD signal in the presence of a strong RF source signal after quantization. Additionally, when the low-resolution ADC is employed at the receiver, the introduced quantization noise (QN) will further deteriorate the bit error rate (BER) performance of the system. To mitigate these effects, we adopt optimal quantizers at the receiver and derive a linear quantized signal model, which considers practical modulation schemes and decoding processes. Based on this model, we define the DRs of both the ADC and the received signal, and derive analytical BER expressions for both the BD and RF source signals under the effect of QN. Subsequently, we formulate an optimization problem to minimize the BER of the BD signal via transmit beamforming, while accounting for the impact of ADC DR and QN. To solve the fractional optimization problem, we employ Dinkelbach’s algorithm in conjunction with the semidefinite relaxation (SDR) technique. Finally, simulation results demonstrate the effectiveness of the proposed beamforming design method and the performance gains achieved by employing optimal quantizers at the receiver.

Symbiotic radio (SR) is an emerging technology that exhibits high energy and spectral efficiency, where a cooperative receiver is designed to decode the primary and the secondary signals jointly. However, the ambiguity problem for joint detection arises due to the multiplication of the primary and secondary signals, which leads to a degradation in detection performance. To address this problem, the secondary transmitter (STx) could adaptively adjust the modulation scheme based on the channel responses of the direct and the reflecting links. Multiple antennas enable to reconfigure these channel responses through active beamforming at the primary transmitter (PTx) and passive beamforming at the STx, leading to the coupling of the beamforming and the adaptive modulation. Considering this coupling, we propose a joint beamforming and adaptive modulation design scheme for SR systems with multiple antennas. To enhance both the performance of primary and secondary transmissions, we focus on the composite signal, which includes the primary and the secondary signals. Accordingly, we formulate an optimization problem as maximizing the minimum Euclidean distance of the composite signal. This problem involves jointly optimizing the active beamforming at the PTx, along with the adaptive modulation and passive beamforming at the STx, subject to the passive reflection constraint at the STx and the average power constraint at the PTx. As the formulated problem is non-convex, we decompose the original problem into two subproblems, which are then solved iteratively using semi-definite programming and difference-of-convex algorithms. To reduce the computational complexity, we further propose a suboptimal scheme. Moreover, we derive the theoretical symbol error rate for the proposed scheme, gaining insights into the role of active beamforming at the PTx. Finally, simulation results show the superiority of the proposed scheme and verify the accuracy of the theoretical analysis.

In reconfigurable intelligent surface (RIS)-assisted symbiotic radios (SRs), an RIS serves not only as a transmitter to deliver its information by reflecting signals from a primary transmitter (PTx) but also as a helper to assist this primary transmission via reconfiguring wireless environments. In this paper, we are interested in an RIS-assisted multiple-input multiple-output (MIMO) SR system, where the RIS has two functions: (1) balancing the channel gains of multiple data streams from the PTx and (2) delivering its own multiple data streams. Considering the passive reflective nature of the RIS, we propose a novel multi-data-stream block delivery scheme, where the reflecting elements of the RIS are segmented into multiple blocks and each block transmits one data stream. The association between the data streams and the corresponding reflecting elements is represented by an indicator matrix. With this information delivery scheme, upper and lower bounds on the sum rate of RIS-assisted MIMO SR are determined and the primary and secondary transmissions’ achievable rates are characterized. Then, we jointly design the transmit covariance matrix at the PTx, the indicator matrix at the RIS, and the passive beamforming vector at the RIS by maximizing the derived upper bound on the sum rate. To show the advantages of RIS-assisted MIMO SR, we examine the traditional precoding matrix-based multi-data-stream delivery scheme of the RIS and explore a special case where the direct link is blocked. Finally, extensive numerical results demonstrate that when the RIS transmits multiple data streams, the system can achieve a higher sum rate compared with the case where the RIS purely enhances the primary transmission, thanks to the additional degree-of-freedom introduced by the RIS transmission.

This paper investigates a multi-user multiple-input single-output (MU-MISO) symbiotic radio (SR) system empowered by multiple reconfigurable intelligent surfaces (RISs). In this system, each RIS adopts a multi-functional reflection modulation scheme to simultaneously transmit data from Internet of Things (IoT) sensors and enhance the primary transmission. However, allocating all reflected power exclusively to IoT data transmission could compromise the capability of RISs to enhance the primary transmission. To address this issue, we propose a flexible power allocation scheme that partitions the power reflected from the RISs into two components: one for enhancing the primary transmission and the other for supporting IoT communication, fully exploiting the multi-functional potential of RISs. Subsequently, we formulate a joint optimization problem aimed at minimizing the transmit power subject to the rate requirements for both primary and RIS transmissions, involving the joint optimization of the beamforming at the base station (BS) and the reflection modulation design at the RISs. Given the non-convex constraints and the coupled variables within the problem, we develop an alternating optimization algorithm combined with difference-of-convex programming to efficiently solve the problem and determine the power allocation scheme. Furthermore, to reduce computational complexity, we consider uniform power allocation across all reflecting elements and introduce weighted parameters to flexibly balance between assisting primary transmission and supporting IoT communication. Simulation results demonstrate that our proposed power allocation scheme effectively balances the demands of the primary and RIS transmission, significantly reducing the required transmit power.

Symbiotic radio (SR) is an emerging technology that supports the secondary transmitter (STx) to share the spectrum and energy with the primary transmission. However, the STx’s reflection modulation may lead to detection ambiguity when jointly decoding the primary and the secondary signals. To address this problem, the STx could employ adaptive modulation to dynamically vary its modulation scheme according to the channel responses of both the direct and reflecting links. Multiple antennas provide a way to reconfigure the channel through active beamforming at the primary transmitter (PTx) and passive beamforming at the STx, which in turn impact the adaptive modulation design. Considering such interdependence, this paper proposes a joint beamforming and adaptive modulation design scheme for SR with multiple antennas. We formulate a problem that maximizes the minimum Euclidean distance of the composite signal subject to the passive reflection constraint of the STx and the transmit power constraint of the PTx. Due to the nonconvexity of the formulated problem, we decouple the original problem into two subproblems and then iteratively solve them by semi-definite programming and difference-of-convex algorithms. Moreover, the nearest neighbor union bound of the symbol error rate for the proposed scheme is analyzed. Finally, simulation results show that the proposed scheme can achieve a significant performance gain compared with the existing schemes.

This paper considers a multi-reconfigurable intelligent surface (RIS) empowered symbiotic radio (SR) system, where multiple RISs, operating as Internet-of-Things (IoT) devices, are used to transmit their modulated information bits by backscattering the incident primary signal and to assist the primary system simultaneously. Most existing works consider the modulation design for the single RIS scenario while lacking indepth investigation into the multi-RIS scenario. To fill this gap, we are interested in cooperatively optimizing the signal constellation and the associated phase shifts of all IoT devices to enhance the overall symbol error rate performance of both the primary and IoT transmissions. Towards this end, we formulate a problem to maximize the minimum Euclidean distance of the received noise-free signal from a signal detection perspective, subject to the peak amplitude constraints of the signal constellation and the passive reflection constraints of phase shifts. Due to the non-convexity of the formulated problem, an iterative algorithm is proposed to solve it. Besides, the structure of the optimized signal constellations in the absence of the direct link is sketched to draw useful insights. Finally, simulation results are provided to validate the superiority of the proposed cooperative constellation design methodology over the classic constellation design.

This paper proposes a partition-based reconfigurable intelligent surface (RIS)-assisted multi-user multiple-input single-output (MU-MISO) symbiotic radio (SR) system. Unlike conventional RIS designs in SR systems that utilize all elements for secondary transmissions, which restricts its ability to support the primary transmission, the RIS is divided into two subsurfaces: one enhances primary transmissions while the other transmits IoT information via spectrum sharing. We formulate a joint optimization problem to minimize transmit power under rate constraints for both primary and IoT transmissions through active beamforming and passive RIS phase-shift design. To tackle the non-convex constraints and variable coupling in the formulated problem, we propose efficient optimization techniques, including alternating optimization and difference-of-convex methods. Furthermore, we propose a low-complexity interference-free scheme leveraging partitioned RIS to eliminate inter-user interference, which is unachievable with conventional RIS design. Simulation results reveal that compared to the conventional scheme, which can be viewed as a special case of partition-based RIS where all the reflecting elements are used to transmit IoT information, partition-based RIS demonstrates superior performance, thereby validating the advantages of RIS partitioning in SR systems.

Reconfigurable intelligent surface (RIS) empowered symbiotic radio (SR) holds the potential to support ambient Internet-of-Things (IoT) due to its spectrum- and energy-efficient characteristics. In this system, the RIS not only assists the primary system but also transmits IoT device information. While most existing works focus on the modulation design for single RIS scenarios, there is a lack of investigation into multi-RIS scenarios. This paper addresses this gap by considering a multi-RIS-empowered SR system, where multiple RISs backscatter the incident primary signal to transmit IoT information to the receiver. We aim to cooperatively optimize the signal constellation and phase shifts of all RISs to improve the overall symbol error rate performance for both primary and IoT transmissions. To achieve this, we formulate a problem to maximize the minimum Euclidean distance of the received noise-free signal from a signal detection perspective, subject to constraints on the peak amplitude of the IoT signal constellation and the passive reflection capabilities of the RISs. Given the non-convex nature of the problem, we propose an efficient iterative algorithm. Additionally, we sketch the structure of the optimized IoT signal constellations in the absence of a direct link to provide essential insights. We also develop a low-complexity algorithm and signal detection method by leveraging the received signal structure. Finally, simulation results demonstrate the superiority of our cooperative constellation design methodology over the traditional PSK constellation designs.

Reconfigurable intelligent surface (RIS) has shown its potential in terahertz (THz) communications, due to its capability to expand coverage and compensate for the severe attenuation of THz signals. This paper investigates a large-scale RIS-assisted THz communications system in the near-field. Nevertheless, the beam squint effect of RIS, caused by the frequency-independent phase shifting circuit, results in severe array gain loss across the wide bandwidth. While true time delays (TTDs) that generate frequency-dependent phase shifts can mitigate beam squint, they often suffer from high power consumption. To address the drawback, we introduce a set of fixed true time delays (FTTDs) with low power consumption and low insertion loss for the RIS. These FTTDs, shared by the elements of RIS, can generate frequency-dependent phase shifts, thereby addressing the beam squint effect. To overcome the limitation of FTTDs being unable to change delays, we propose a dynamic architecture that consists of a switch network and two-layer phase shifters, allowing the elements of RIS to select the FTTDs. Subsequently, we analyze the theoretical array gain of the proposed FTTD-equipped RIS and determine the minimum number of FTTDs required for effective mitigation. Then, we formulate a problem of maximizing the achievable rate and propose a two-stage algorithm. Specifically, in the first stage, we obtain the optimal wideband beamforming design for both the BS and the RIS. In the second stage, we approximate this optimal design with the beamforming design from our proposed architecture. Finally, simulation results demonstrate that our proposed RIS design, with a small number of FTTDs, can achieve a near-optimal achievable rate and higher energy efficiency.

In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR) system, where an RIS assists a primary transmission by passive beamforming and simultaneously acts as an information transmitter by periodically adjusting its reflection coefficients. Such RIS functions innately enable a new type of communication channel, called multiplicative multiple access channel (M-MAC), where the primary and secondary signals are superposed in a multiplicative manner. To pursue the fundamental performance limits, in this paper, we focus on characterizing the capacity region for the RIS-assisted SR system. Due to the reflection nature of RISs, the signal transmitted from the RIS elements should satisfy a passive reflection constraint. In particular, we consider two types of passive reflection constraints, one for the case that the amplitudes of the reflection coefficients are fixed but the phases are adjustable, while the other for the case that both the amplitudes and the phases can be adjusted. Under the passive reflection constraints at the RIS as well as the average power constraint at the primary transmitter (PTx), we characterize the capacity region of RIS-assisted SR when the direct link from the PTx to the receiver is blocked. It is observed that: 1) the number of sum-rate-optimal points on the boundary of the capacity region is infinite; 2) for the rate pairs with the maximum sum rate, the optimal amplitude distribution of the primary signal is a continuous Rayleigh distribution, while for the remaining rate pairs on the capacity region boundary, the optimal amplitude distribution of the primary signal is discrete; 3) when both the amplitudes and the phases of the reflection coefficients are adjusted for the RIS, the capacity region is enlarged as compared to the phase-adjusted-only case.

In this paper, we consider a symbiotic radio (SR) system, which consists of a radio frequency (RF) source with multiple antennas, a backscatter device (BD), and a receiver, to support passive Internet of Things (IoT). The RF source transmits its signal (RF source signal) to the receiver via transmit beamforming while the BD transmits its signal (BD signal) to the receiver by modulating its information bits over the incident RF source signal. However, due to the double path loss of the reflecting link, the received BD signal is typically much weaker than the received RF source signal. Therefore, the dynamic range of the received signal may exceed that of the analog-to-digital converter (ADC), which will make the ADC unable to quantize the received BD signal. To address this issue, we exploit transmit beamforming to balance the strength of the received BD signal and the received RF source signal. To explore the effect of the ADC dynamic range on the system, we first quantitatively describe the dynamic ranges of both the ADC and the received signal and then analyze the bit error rates (BERs) of the BD signal and the RF source signal. Subsequently, we formulate an optimization problem to minimize the BER of the BD signal via transmit beamforming while considering the ADC dynamic range constraint. To solve the problem, we first adopt Dinkelbach’s algorithm to determine the minimum ADC resolution required to quantize the weak received BD signal, followed by semidefinite programming (SDP) to design the beamforming vector. Finally, simulation results reveal that the minimum ADC resolution is related to the transmit power and the relative strength between the direct link and the reflecting link.

Reconfigurable intelligent surface (RIS) has been widely exploited for secure communications in physical layer security (PLS) by destructing the eavesdropper's channel via reflect beamforming. In this paper, we investigate RIS-aided secure communications with a novel RIS design scheme. The proposed design leverages RIS to increase the achievable secrecy rate via transmitting the artificial noise (AN) instead. To do so, RIS modulates its information over the incident signal and reflects it to the legitimate receiver and eavesdropper. The RIS modulation scheme is a prior knowledge available at the legitimate receiver, but not available at the eavesdropper. Thus, the reflected signal through the RIS is naturally an additional multi-path component for the legitimate user but a type of AN for the eavesdropper, yielding a mutualistic symbiosis between the RIS and the legitimate user but a parasitic symbiosis between the RIS and the eavesdropper as demonstrated in symbiotic radio (SR). From this SR perspective, we consider an achievable secrecy rate maximization problem by optimizing the RIS reflect beamforming. To this end, we use the path-following algorithm to solve the problem iteratively. Further-more, the comparison of the conventional destruct-channel (DC)- RIS design and the proposed AN - RIS design is conducted. Finally, simulation results show that the proposed AN - RIS design outperforms the DC- RIS design in general cases where the reflecting link is weaker than the direct link of eavesdropper.

In an active reconfigurable intelligent surface (RIS), each reflecting element (RE) reflects the incident signal with not only reconfigurable phase shift but also controllable amplitude amplification. In this paper, we are interested in active RIS-aided interference channels in which$K$user pairs share the same time and frequency resources with the help of the active RIS. Thanks to the promising amplitude amplification capability, activating a moderate number of REs, rather than all of them, is sufficient for the active RIS to mitigate the cross channel interferences. Motivated by this, we propose a power-aware sparse reflect beamforming design for the active RIS-aided interference channels, which allows the active RIS to flexibly adjust the number of activated REs for the sake of saving power. Specifically, we first establish the power consumption model in which only those activated REs consume the biasing and operation power that supports the amplitude amplification. Based on the proposed model, we formulate a problem to maximize the sum rate of the$K$user pairs by designing the sparse reflect beamforming vector under the maximum amplification gain and the limited power budget constraints on the active RIS. Towards this end, we propose an iterative reweighted$\ell_{1}$-norm method in combination with fractional programming to find a sparse solution for the reflect beamforming vector. Numerical results show that the proposed sparse design can notably increase the sum rate of the$K$user pairs in interference channels even with the limited power budget.

In reconfigurable intelligent surface (RIS)-assisted symbiotic radios (SRs), an RIS delivers its information by periodically reflecting the signal from a primary transmitter (PTx) and simultaneously the RIS assists this primary transmission by passive beamforming. In this paper, we are interested in characterizing the multiple-input multiple-output (MIMO) channel capacity for RIS-assisted SR, where both PTx and RIS transmit multiple data streams. To this end, we propose a novel multi-data-stream delivery scheme for the RIS, where the reflecting elements of the RIS are divided into multiple parts and each part is used to transmit one data stream by periodically adjusting its reflection coefficients. With this information delivery scheme, we derive an upper bound on the MIMO channel capacity of an RIS-assisted SR system. To achieve it, we then jointly design the transmit covariance matrix at the PTx and the passive beamforming vector at the RIS by using an alternating optimization algorithm. Considering the high computational complexity of solving the transmit covariance matrix, we further propose two low-complexity algorithms, i.e., upper bound-based algorithm and singular value-based algorithm. Finally, extensive numerical results are presented to show the effectiveness of the proposed algorithms and demonstrate the advantages of the RIS to transmit multiple data streams.

In this article, we are interested in active reconfigurable intelligent surface (RIS)-aided interference channels in which K user pairs share the same time and frequency resources with the aid of active RIS. Thanks to the promising amplitude amplification capability, activating a moderate number of reflecting elements (REs) rather than all of them is sufficient for the active RIS to mitigate the cross-channel interferences. Motivated by this, we propose a power-aware sparse reflect beamforming (SRB) design for the active RIS-aided interference channels, which allows the active RIS to flexibly adjust the number of activated REs for the sake of reducing power costs. Specifically, we establish the power consumption model in which only those activated REs consume the biasing and operation power that supports the amplitude amplification, yielding an$\ell _{0}$-norm power consumption function. Based on the proposed model, we investigate a sum-rate maximization problem and an active RIS power minimization problem by carefully designing the SRB vector. To solve these problems, we first replace the nonconvex$\ell _{0}$-norm function with an iterative reweighted$\ell _{1}$-norm function. Subsequently, we employ fractional programming to solve the sum-rate maximization and utilize semidefinite programming combined with the difference-of-convex algorithm (DCA) to address the active RIS power minimization both of which are proven to converge well. Numerical results show that the proposed sparse designs can notably increase the sum rate of user pairs and decrease the power consumption of the active RIS in interference channels.

In reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR), the RIS acts as a secondary transmitter by modulating its information bits over the incident primary signal and simultaneously assists the primary transmission, then a cooperative receiver is used to jointly decode the primary and secondary signals. Most existing works of SR focus on using RIS to enhance the reflecting link while ignoring the ambiguity problem for the joint detection caused by the multiplication relationship of the primary and secondary signals. Particularly, in case of a blocked direct link, joint detection will suffer from severe performance loss due to the ambiguity, when using the conventional on-off keying and binary phase shift keying modulation schemes for RIS. To address this issue, we propose a novel modulation scheme for RIS-assisted SR that divides the phase-shift matrix into two components: the symbol-invariant and symbol-varying components, which are used to assist the primary transmission and carry the secondary signal, respectively. To design these two components, we focus on the detection of the composite signal formed by the primary and secondary signals, through which a problem of minimizing the bit error rate (BER) of the composite signal is formulated to improve both the BER performance of the primary and secondary ones. By solving the problem, we derive the closed-form solution of the optimal symbol-invariant and symbol-varying components, which is related to the channel strength ratio of the direct link to the reflecting link. Moreover, theoretical BER performance is analyzed. Finally, simulation results show the superiority of the proposed modulation scheme over its conventional counterpart.

This paper studies the reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR) system, where an RIS acts as a secondary transmitter to transmit its information by leveraging the primary signal as its RF carrier and simultaneously assists the primary transmission. Conventionally, all reflecting elements of the RIS are used to transmit the secondary signal, which, however, would limit its capability for assisting the primary transmission. To address this issue, we propose a novel RIS partitioning scheme, where the RIS is partitioned into two sub-surfaces, one to assist the primary transmission and the other to transmit the secondary signal. Naturally, there exists a fundamental tradeoff between the assistance and transmission capabilities of RIS regarding the surface partitioning strategy. Considering the coupling effect between the primary and secondary transmissions, we focus on the detection of the composite signal formed by the primary and secondary ones, based on which we propose a novel two-step detector. Then, we formulate the assistance-transmission tradeoff problem to minimize the bit error rate (BER) of the composite signal by jointly optimizing the surface partitioning strategy and the phase shifts of the two sub-surfaces, such that the overall BER of RIS-assisted SR is minimized. By solving this problem, we show that the optimized surface partitioning strategy depends on the channel strength ratio of the direct link to the reflected link. Moreover, performance analysis shows that when the direct link is blocked, exchanging the number of reflecting elements used for assistance and transmission can still achieve almost the same BER of the composite signal thanks to the coupling effect. Finally, extensive simulations show that our proposed RIS partitioning scheme outperforms the conventional schemes which use all reflecting elements for either assistance or transmission.

In RIS-assisted symbiotic radio (SR) systems, the RIS transmits messages by using the spectrum and energy of the primary transmission and simultaneously assists the primary transmission by passive beamforming. Due to the functionality of information transmission, the RIS could not always enhance the primary transmission. Instead, We observe that the performance of the primary transmission in terms of bit error rate (BER) will drop first and then improve with the increase in the number of reflecting elements of the RIS, i.e.,$K$. Motivated by this, in this paper, we are interested in a mutualistic condition on$K$for RIS-assisted SR, through which, the primary transmission could obtain the performance gain from the RIS. First, we design a transmission scheme for the RIS, which uses the different phase shifts to represent different transmission bits. Then, we optimize the phase shifts of the RIS, based on which, we derive an upper bound on BER for both primary and secondary transmissions. Compared with the BER performance in the absence of the RIS, we derive the mutualistic condition on the number of the reflecting elements$K$. Finally, simulation results are provided to verify the effectiveness of the theoretical analysis.

This paper explores the potential of reconfigurable intelligent surface (RIS) to null interference in a multi-user multiple-input single-output (MU-MISO) symbiotic radio (SR) system. Due to the periodic variations of the RIS phase shifts in the SR systems, it is challenging to use it to achieve interference-free reception in SR systems. To address this issue, we propose a RIS partitioning design for MU-MISO SR. By splitting RIS into two parts, one serves as a relay and removes interference among users, and the other one acts as a secondary transmitter for the Internet of Things (IoT) system, transmitting IoT information by periodically changing its phase shifts. Through this design, the MU-MISO SR system can be decomposed into multiple parallel MISO SR subsystems, each of which only contains the desired user signal and the RIS signal without interference from other users. To do so, we first explore the relationship between the number of reflecting elements and their interference-free capability. Then we formulate a power minimization problem to jointly optimize the transmit beamforming and the phase shifts of partitioned RIS. Finally, simulation results show that the proposed RIS partitioning design could help reduce power consumption, while at the same time achieving interference-free reception in SR.

In reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR) systems, the RIS transmits information by modulating its information bits over RF signals from a primary transmitter (PTx), and simultaneously, the RIS assists the primary transmission by passive beamforming. Considering the inevitable channel estimation errors arising in practice, in this paper, we are interested in quantifying the effects of imperfect knowledge of channels on the channel capacity for both primary and secondary transmissions in RIS-assisted SR. For the primary transmission, we first derive upper and lower bounds on the achievable rate with channel estimation errors. Based on the derived lower bound, we investigate the minimum number of reflecting elements of an RIS that can enable the performance enhancement of the primary transmission compared to the case without the RIS. For the secondary transmission, exact and asymptotic achievable rates are derived. Finally, extensive numerical results are presented to demonstrate the effects of the channel estimation errors together with the interrelationship between primary and secondary transmissions.

In the reconfigurable intelligent surface (RIS)-based symbiotic radio (SR) system, the RIS acts as a secondary transmitter by modulating its information over the primary signal and simultaneously assists the primary transmission, which leads to a mutualistic spectrum sharing relationship. To ensure that the primary transmission can gain more benefits from the secondary transmission, we propose a novel RIS design scheme for SR, which divides the phase-shift matrix into two sub-phase-shift matrices, one to assist the primary transmission and the other to transmit the secondary signal. To optimize the two sub-phase-shift matrices, we first introduce a mutualistic factor which describes the performance requirement of the primary transmission and then formulate the problem to minimize the bit error rate (BER) of the secondary transmission, under the constraint that the BER performance of the primary transmission is higher than the performance requirement controlled by the mutualistic factor. To solve this non-convex problem, we resort to the successive convex approximation technique to obtain a suboptimal solution. Finally, simulation results reveal an interesting tradeoff between the BER performance of the primary and secondary transmissions by adjusting the mutualistic factor.

In this paper, we are interested in reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR) systems, where an RIS assists a primary transmission by passive beam-forming and simultaneously acts as a secondary transmitter to modulate its own information by periodically adjusting its reflecting coefficients. The above modulation scheme innately enables a new multiplicative multiple access channel (M-MAC), in which the primary and secondary signals are superposed in a multiplicative and additive manner. To pursue the fundamental performance limits of the M-MAC, we focus on the characterization of the capacity region of such systems. Due to the passive nature of RISs, the transmitted signal of the RIS should satisfy the peak power constraint. Under this constraint at the RIS as well as the average power constraint at the primary transmitter (PTx), we analyze the capacity-achieving distributions of the transmitted signals and the optimal reflecting coefficients of the RIS. Then, we derive the maximum achievable rates for both primary and secondary transmissions and characterize the rate region of the M-MAC. It is observed that the secondary transmission can achieve the maximum rate when the PTx transmits signals with the constant envelope. Furthermore, the rate region of the M - MAC is strictly convex and larger than that of the conventional TDMA scheme.

This paper considers the reconfigurable intelligent surface (RIS)-assisted symbiotic radio (SR) system, in which the RIS, acting as a secondary transmitter (STx), transmits its information by leveraging the primary signal as its RF carrier and simultaneously assists the primary transmission. In such a system, when the RIS transmits information, it could only provide limited assistance for the primary transmission. Thus, there exists a fundamental tradeoff between the assistance and information transmission capabilities of the RIS. To study the tradeoff, in this paper, we propose a novel RIS design scheme which partitions the RIS surface into two sub-surfaces, one to assist the primary transmission and the other to transmit the secondary signal. Considering the coupling effect between these two transmissions in SR, we focus on the composite signal formed by the primary and secondary signals. Then, to optimize the surface partitioning strategy, we formulate the assistance-transmission tradeoff problem to minimize the bit error rate (BER) of the composite signal, so as to improve the overall BER performance of the primary and secondary signals. By solving the problem, we show that optimal surface partitioning is related to the strength ratio of the direct link to the reflected link. Finally, simulation results show that the proposed design outperforms the conventional design significantly, which provides the best tradeoff.

In this paper, we are interested in a simultaneously transmitting and reflecting RIS (STAR-RIS)-assisted SR system, where all elements of a STAR-RIS are divided into two groups, one operating in the reflection mode to enhance the primary transmission, and the other operating in the transmission mode to transmit its own information bits. For such a system, we aim to jointly design the receiver and the phase shifts of the STAR-RIS. To avoid the ambiguity problem caused by the multiplication feature of SR, we employ ASK and PSK modulation schemes at the primary transmitter and the STAR-RIS, respectively. With such modulation schemes, we design the signal detection schemes for both primary and secondary transmissions and then analyze their corresponding symbol error rate (SER) performance. To prioritize the QoS of the primary transmission and simultaneously minimize the SER of the secondary transmission, we formulate one optimization problem to optimize the mode-switching scheme and phase shifts design scheme for STAR-RIS. Due to the non-convexity of the formulated problem, we employ the penalty method together with the successive convex approximation (SCA) method to iteratively solve it. Finally, extensive simulation results are presented to demonstrate the advantages of the STAR-RIS-assisted SR system and the effectiveness of the joint phase shifts and receiver design scheme.

Reconfigurable intelligent surface (RIS) has recently emerged as a promising technology for wireless communications, which intelligently controls the phase shift of each unit cell to form desired beams. Most prior works on RIS consider time-division duplexing (TDD) systems, in which the same phase shifts can be applied to both uplink and downlink due to the channel reciprocity. However, for frequency-division duplexing (FDD) systems, using the same phase shifts will result in beam misalignment, thereby leading to performance degradation. To address this issue, in this article, we study the practical RIS design and beamforming optimization for FDD systems. By representing the phase shifts of RIS with the equivalent circuit model which includes the resistance, inductances, and tunable capacitance, we propose a methodology to design the circuit parameters (i.e., inductances and capacitance) to meet the desired reflection requirements (i.e., phase tuning range, reflectivity, and zero phase slope) of both the uplink and downlink transmissions in FDD systems. Given the designed inductances, a practical binary RIS reflection model corresponding to two reflection states is then proposed. Furthermore, based on the proposed reflection model, a problem is formulated to jointly optimize the active and passive beamforming such that the minimum array response gain of the uplink and the downlink is maximized. An efficient iterative algorithm is proposed to obtain a suboptimal solution. Simulation results show that our proposed RIS design outperforms those benchmarks which design the circuits by only optimizing either uplink or downlink.

In symbiotic radio (SR), the secondary transmitter (STx) modulates its information over the RF signal from the primary transmitter (PTx). This modulation technology, also called “modulation in the air”, leads to the multiplication of the primary and secondary signals. Thus, SR can be modeled as a multiplicative multiple access channel (M-MAC). In this paper, we propose a modulation scheme for such an M-MAC, which consists of two additive parts: the symbol-invariant component used to aid the primary transmission and the symbol-varying component used to deliver STx information. By optimizing these two components, we can strike a balance between the primary and secondary transmissions. Particularly, due to the coupling between these two transmissions in the M-MAC, we focus on the composite signal formed by the primary and secondary signals. Then, we optimize the above two components by maximizing the minimum Euclidean distance as well as minimizing the Hamming distance between the adjacent constellations of the composite signal. Furthermore, we derive the closed-form solution of the optimal modulation scheme, which is related to the ratio of the direct link to the backscatter link. Finally, simulation results are provided to verify the effectiveness of our proposed scheme.

Reconfigurable intelligent surface (RIS) has recently emerged as a promising technology for wireless communications, which intelligently controls the phase shift of each unit cell to form desired beams. Most prior works on RIS focus on a single frequency band, and thus for time-division duplexing (TDD) systems, the same phase shifts can be applied to both uplink and downlink. However, for the frequency-division duplexing (FDD) mode, if the same phase shifts are applied in both uplink and downlink, the directions of the uplink RIS beams will not be aligned with those of the downlink, which will in turn cause performance degradation. To address this issue, in this paper, we investigate the practical RIS design and optimization for FDD systems. By representing the reflection coefficients of RIS with the equivalent circuit model which includes the resistor, inductor and tunable capacitor, we first provide the guidelines on the circuit design to realize 2π phase control over the two frequency bands of the FDD system. In addition, we propose a low-resolution RIS configuration scheme with two tunable modes corresponding to two capacitances, and we formulate a max-min signal-to-noise ratio (SNR) problem to maximize the minimum SNR of uplink and downlink. To solve the non-convex problem, we propose an alternating optimization algorithm to obtain a suboptimal solution. Simulation results show that our proposed RIS design outperforms those benchmarks which design the circuits by only optimizing uplink or downlink.

In a backscatter communication system, the backscatter device (BD) transmits its messages to the backscatter receiver (BR) by reflecting the incident signal from an external radio frequency (RF) emitter, instead of using power-hungry active RF components themselves. Thus, backscatter communication has shown great potential for achieving low-power communication. The double-fading effect associated with the backscatter link, however, is a major limiting factor to achieve efficient backscatter communication. Reconfigurable intelligent surfaces (RISs), a recently developed technology, can be applied at the BD to enhance the backscatter link thanks to the fact that both RIS and backscatter communication share the same reflective principle. Such a design can also allow the backscatter communication system to capture the desired RF signal as a reflective carrier in a complex radio environment. In this article, a comprehensive overview of backscatter communication assisted by RIS is given. We first introduce the basics of backscatter communication, which covers the antenna scattering principle, backscatter modulation, and link budget calculation. Then, the details of RIS are discussed, which include antenna-based RIS and metamaterial-based RIS, followed by the discussion of the roles of RIS in backscatter communication. After that, we provide an overview of three types of backscatter communication systems assisted by RIS, including RIS-assisted unmodulated backscatter communication, RIS-assisted ambient backscatter communication, and RIS-assisted symbiotic radio. Emerging applications of these systems, technical challenges, and future opportunities in this emerging field are also presented.

In this paper, we investigate a large intelligent surface (LIS) assisted symbiotic radio (SR) system, in which a LIS device, operating as an Internet-of-Things (IoT) device, exploits the signal from a primary transmitter (PT) as its communication carrier to achieve its own information transmission, and concurrently serves as a desirable additional link to aid the primary transmission from the PT to a primary receiver (PR). A cooperative beamforming scheme (i.e., active transmit beamforming at the PT and passive reflecting beamforming at the LIS device) is proposed to minimize PT's transmit power under quality-of-service (QoS) constraints of both the primary and LIS device transmissions. Both continuous and discrete phase shift setups of the LIS device are considered. For the continuous phase shift setup, a closed-form solution is derived, analytically showing that by smartly configuring the phase shifts, the signals from primary link and backscatter link can add coherently at the PR; while for the discrete phase shift setup, a near-optimal solution for the 1-bit phase shifter is obtained via the semi-definite relaxation (SDR) technique, and a general successive refinement algorithm (SRA) is developed for any-bit phase shifter. Simulation results demonstrate that cooperative beamforming design can adaptively adjust beamformers to strike a balance between the primary and LIS device transmissions.