To support passive Internet-of-Things (IoT) for future 6G networks, backscatter communication (BC) has emerged as a promising solution due to its ultra-low-power consumption nature. In this paper, we propose a novel multistatic passive IoT architecture which allows the reader to recover the information from multiple backscatter devices (BDs), excited by multiple remote continuous-waveform (CW) transmitters. At each BD, multiple backscatter antennas, in conjunction with cyclic delay transmission (CDT) and interleaved frequency division multiple access (IFDMA) framework, are deployed to achieve antenna gain, diversity advantage, as well as transmission orthogonality among the BDs. Furthermore, transmit beamforming at the CW transmitters and cyclic delays across the BDs are optimized to enhance the performance and ensure fairness among the BDs. Extensive simulation results have validated the effectiveness of the proposed framework under various scenarios, demonstrating substantial improvements in both reliability and fairness compared with conventional schemes.

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.

In symbiotic radio (SR) systems, backscatter devices (BDs) are able to achieve ultra-low-power transmissions by backscattering the primary signal of a primary transmission, offering a promising solution for future passive Internet-ofThings (IoT). This paper explores the use of multiple antennas at the BD, which allows it to combat fading in the cascaded channel of the backscatter link. To leverage the potential, the BD generates the secondary signal using Alamouti space-time coding across the multiple antennas. This enables the BD to transmit information without requiring channel state information (CSI) of the cascaded channel. Considering the secondary symbol period is identical to the primary symbol period in the SR system, we propose a theoretical model to evaluate the diversity order for both the primary and the secondary transmissions using their pairwise error probability (PEP). Interestingly, based on the theoretical results, it is found that the secondary signal cannot obtain the diversity gain provided by the space-time coding with the conventional non-biased constellation but can obtain it with a direct current (DC)-biased constellation. Extensive numerical results are provided to demonstrate the accuracy of the theoretical analysis and to show how to obtain the diversity gain for SR with space-time coding.

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.

Symbiotic radio (SR) has emerged as a promising technology for enabling efficient spectrum and power sharing between active and backscattering transmissions. In this paper, we investigate the reconfigurable intelligent surface (RIS)-assisted SR system, where the primary transmission uses orthogonal frequency division multiplexing (OFDM) and the RIS transmits the secondary signal by backscattering the primary signal. The primary OFDM block and the secondary symbol have identical symbol periods but may not be perfectly synchronized, which can introduce inter-carrier interference (ICI) in the received OFDM blocks, thereby hindering joint signal detection. To address this issue, we propose a novel pilot structure and receiver design for SR. Specifically, the RIS sent a training sequence at the beginning of the secondary transmission, enabling the receiver to detect the presence of ICI and estimate essential parameters. If ICI is detected, two effective methods for synchronization offset estimation are proposed. Then, joint signal detection is improved by properly decoupling primary and secondary signals, mitigating the impact of synchronization offsets. On the other hand, if ICI is absent, the secondary signal arrival is identified using the training sequence, and joint signal detection is directly performed without suffering ICI. Simulation results validate the accuracy of the proposed estimation methods and show that the proposed detection methods ensure the reliable detection of both primary and secondary signals, even in the presence of ICI.

Passive Internet-of-Things (IoT), as a new communication technology, is expected to enable massive device connectivity in a cost-effective and energy-efficient manner. One of the most important topics on Passive IoT is to find a suitable waveform that can be affordable for a wide range of IoT devices. In this paper, we propose a novel waveform design that leverages a low-power on-off keying (OOK) wave. This design cleverly reuses the orthogonal frequency division multiplexing (OFDM) signal generated by the legacy 5G base station, i.e., gNodeB (gNB). Additionally, we enhance the OOK waveform using a central part repetition scheme to acquire frequency diversity gains, thereby improving its resilience against fading channels in realistic environments. Thanks to the repetition being applied only to the central part, no additional bandwidth resources are needed to support the low-power waveform. Simulation results are provided to validate the effectiveness of our approach, demonstrating significant potential for low-power transmissions in passive IoT.

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.

To support the massive Internet-of- Things (IoT) network, symbiotic radio (SR) has emerged as a promising solution that enables passive IoT connections by exploiting active primary transmissions. Realizing the enhanced spectrum- and energy-efficiency promised by SR requires symbol synchronization between the primary and IoT signals, which, however, remains challenging for cost-limited IoT devices. In this paper, we investigate reconfigurable intelligent surface (RIS)-assisted SR (RSR) with imperfect symbol synchronization. Specifically, the primary transmission employs orthogonal frequency division multiplexing (OFDM), while the RIS enhances the primary transmission and concurrently transmits its secondary signal by passively backscattering the incident primary signal. Due to the unknown synchronization offset (SO) between primary and secondary signals, the reflected channel via the RIS exhibits variations within each OFDM block, consequently leading to inter-carrier interference (ICI) in the received signal. To mitigate this unfavorable effect, we propose a novel receiver design by utilizing virtual subcarriers within each OFDM block. By employing energy detection at the virtual subcarriers, the receiver can detect the arrival of the secondary signal based on the ICI. Furthermore, by compensating the loss of orthogonality in the received OFDM block, the receiver can blindly estimate the SO, thereby facilitating joint detection of primary and secondary signals. Simulation results validate that our proposed receiver significantly improves the bit error rate (BER) performance for RSR with imperfect symbol synchronization.

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 previous studies on reconfigurable intelligent surface (RIS)-aided spectrum sharing cognitive radio (CR), the potential of RIS in supporting secondary transmission may not be fully unleashed, due to the insufficient attention to its capacity to mitigate interference from the primary transmitter at the secondary receiver. To bridge this gap, this paper investigates a general active RIS (RIS)-aided CR system, in which the secondary user (SU) aims to minimize the transmit power while satisfying its own SINR constraint and the interference temperature constraint at the primary receivers. The SU needs to jointly optimize the transmit beamforming at the SU transmitter and the reflection coefficients at the active RIS. An improved alternating optimization (AO) algorithm is first proposed, which exploits the active RIS not only to enhance the transmission channel for the secondary transmission, as commonly addressed in most CR literatures, but also to mitigate interference from the primary transmitter. Additionally, a novel low-complexity channel customization (CC) algorithm is then proposed, which can efficiently customize the SU transmission channel toward a desired direction without the need for AO iterations. Simulation results show that the SU transmit power can be effectively reduced by exploiting the active RIS with the PU interference mitigation. Moreover, the proposed CC algorithm achieves the transmit power reduction with moderate performance loss as compared with the AO algorithm, but offers an efficient means to facilitate beamforming management in CR.

This paper characterizes the achievable rate region of the active reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) interference channel, where an active RIS is used to help multiple multi-antenna transmitters send information to their intended receivers in the presence of strong interference among them. All the transmitters are subject to the transmit power constraints, while the active RIS must satisfy the power budget constraint and the maximum amplitude constraint for each reflecting element (RE). Under these constraints, the rate-profile method is employed to approach the Pareto boundary of the rate region, which needs to solve a series of feasibility problems for a given rate profile. These problems can be solved by an alternating optimization algorithm. In each iteration, the sum of the rate tuples is sequentially optimized by the transmit beamforming vectors at the transmitters and the reflection coefficients matrix at the active RIS. Specifically, the transmit beamforming vectors are obtained by solving a sequence of second-order cone programming (SOCP) problems, and the reflection coefficients matrix is obtained by solving a sequence of semidefinite programming (SDP) problems along with Gaussian randomization. Simulation results show that, even with strong interference, the active RIS can offer a significant improvement in the rate region compared to the passive RIS under the same power budget.

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.

This paper investigates an active reconfigurable intelligent surface (RIS)-aided mmWave system, in which the base station (BS) proactively sends a positioning reference signal to localize the mobile station (MS). In particular, due to the propagation nature of mmWave, the direct link between the BS and the MS is usually blocked. Thus, the reference signal cannot directly reach the MS but can do so through the enhanced reflections provided by multiple active RISs in the surroundings. To harness the benefits of active RIS-aided wireless localization system, the multiple active RISs are designed to reflect the reference signal in a time-division manner, and the reflection coefficient matrix of each active RIS is designed via a codebook method. Then, based on the reflected reference signal, a root MUSIC-based angle of departure (AoD) estimation algorithm is proposed for the MS to estimate the AoD from each active RIS. After that, the MS is able to calculate its location with the estimated AoDs and the positions of the active RISs. In addition, the power splitting between the BS and the active RISs is considered to further improve the positioning accuracy when the total power consumption is given. The optimal power splitting ratio is obtained by minimizing Cramér-Rao lower bound of the AoD. Simulation results show the superiority of our proposed localization scheme and the significance of optimizing the power splitting ratio in the considered active RIS-aided system.

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.

Symbiotic radio (SR) is a promising solution to achieve high spectrum- and energy-efficiency due to its spectrum sharing and low-power consumption properties, in which the secondary system achieves data transmissions by backscattering the signal originating from the primary system. In this paper, we are interested in the pilot design and signal detection when the primary transmission adopts orthogonal frequency division multiplexing (OFDM). In particular, to preserve the channel orthogonality among the OFDM sub-carriers, each secondary symbol is designed to span an entire OFDM symbol. The comb-type pilot structure is employed by the primary transmission, while the preamble pilot structure is used by the secondary transmission. With the designed pilot structures, the primary signal can be detected via the conventional methods by treating the secondary signal as a part of the composite channel, i.e., the effective channel of the primary transmission. Furthermore, the secondary signal can be extracted from the estimated composite channel with the help of the detected primary signal. The bit error rate (BER) performance with both perfect and estimated CSI, the diversity orders of the primary and secondary transmissions, and the sensitivity to symbol synchronization error are analyzed. Simulation results show that the performance of the primary transmission is enhanced thanks to the backscatter link established by the secondary transmission. More importantly, even without the direct link, the primary and secondary transmissions can be supported via only the backscatter link.

Massive multiple-input multiple-output (MIMO) is a key enabling technology for next-generation communication systems. In massive MIMO cellular networks, coordinated beamforming (CBF), which jointly designs the beamformers of multiple base stations (BSs), is an efficient method to enhance the network performance. In this paper, we investigate the sum rate maximization problem in a massive MIMO mobile cellular network, where in each cell a multi-antenna BS serves multiple mobile users simultaneously via downlink beamforming. Although existing optimization-based CBF algorithms can provide near-optimal solutions, they require real-time and global channel state information (CSI), in addition to their high computation complexity. Due to the non-negligible delay of practical backhaul networks and the high-complexity optimization process, it is almost impossible to apply them in mobile cellular networks. Noting that the considered problem under the practical constraints can be modeled as a networked distributed partially observable Markov decision process, we propose a deep reinforcement learning-based distributed dynamic coordinated beamforming (DDCBF) scheme, which enables each BS to determine the beamformers with only local CSI and some historical information from other BSs. Besides, the beamformers can be calculated with a considerably lower computational complexity by exploiting neural networks and expert knowledge, i.e., a solution structure observed from the iterative procedure of the centralized optimization algorithms. Moreover, we provide extensive numerical simulations to validate the effectiveness of the proposed DRL-based approach. With lower computational complexity and less required information, the results show that the proposed approach can achieve comparable performance to the centralized iterative optimization algorithms.

Interference poses a significant challenge in wireless communications due to the broadcast and superposition nature of wireless media. Reconfigurable intelligent surfaces (RIS), a promising 6G technology, can manage interference by customizing radio propagation with controllable reflecting elements (REs). Active RIS, which amplifies signal amplitudes and adjusts phases with enhanced REs, shows potential in addressing strong interference. This paper investigates the active RIS-aided multiple-input single-output (MISO) interference channel, characterizing the achievable rate region under transmit-power constraints, maximum amplitude constraint on each RE, and a power budget constraint at the active RIS. Utilizing multiple antennas at transmitters and multiple enhanced REs at the active RIS, we explore the Pareto Boundary of the achievable rate region with the rate profile method. A general alternating optimization framework iteratively optimizes the transmit beamforming vector and the reflection coefficient matrix through convex optimization techniques. We also consider a stringent case where active RIS ensures interference-free transmissions, deriving a reflection coefficient matrix structure via subspace decomposition. Additionally, a suboptimal algorithm combining this structure with maximum-ratio-transmission (MRT) and zero-forcing (ZF) beamforming characterizes the achievable rate region. Simulation results demonstrate that active RIS significantly improves the rate region and ensures interference-free transmissions compared to passive RIS and relay under the same power budget.

In this paper, we investigate reconfigurable intelligent surface (RIS)-enabled full-duplex backscatter communications in multi-user symbiotic radio (SR) systems. Specifically, an RIS is integrated with a primary transmission in which the primary transmitter (PT) broadcasts common messages to multiple primary receivers (PRs) and the RIS. Thanks to the full-duplex backscatter communication nature, the RIS absorbs part of the PT signals to decode the PT messages and, meanwhile, reflects the remaining part to convey its own messages for the PRs. By doing so, the RIS and the PRs can receive common messages, like the pairing messages, from the PT, and simultaneously establish information links between them without requiring additional spectrum and radio resources. However, it brings a challenging task on how to properly design the reflection matrix to resolve the conflicts between the signal absorption and reflection in the RIS-enabled full-duplex backscatter communication. Towards this end, we formulate an optimization problem that aims to jointly optimize the PT transmit beamforming vector and the RIS reflection matrix subject to the transmission rate constraints for the PT and the RIS. The problem is solved by the proposed alternating optimization (AO) method combined with difference-of-convex (DC) algorithm. Simulation results are presented to show that the RIS-enabled full-duplex backscatter communication can efficiently save the transmit power as compared to its half-duplex counterpart.

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 investigates the reconfigurable intelligent surface (RIS) assisted symbiotic radio (RSR) system, where the primary transmission adopts orthogonal frequency division multiplexing (OFDM), and the RIS enables the secondary transmission by backscattering the primary signal. In particular, we propose a novel transmission protocol for the RSR system. With the help of the proposed protocol, the primary signal can be successfully detected without the knowledge of the secondary transmission at the RIS. Moreover, based on the detected primary signals, efficient channel estimation is achieved with a scalable training overhead. Furthermore, with the estimated channel state information (CSI), the passive beamforming vector of the RIS is optimized to maximize the weighted sum-rate of the primary and secondary transmissions. To solve this problem, we develop an effective algorithm based on the direct fractional programming (FP) approach, enabling the RIS to enhance the primary transmission and simultaneously transmit its own secondary signal. Simulation results validate the effectiveness of our proposed scheme and demonstrate that our proposed scheme outperforms the conventional ones with the same training length.

This paper considers an active reconfigurable intelligent surface (RIS)-aided multiple-input single-output (MISO) cognitive radio (CR) system where the active RIS is designed to assist the transmission of the secondary user (SU) by tuning its controllable reflecting elements (REs) with enhanced reflections. As each RE in active RISs can adjust the phases and amplify the incident signals, active RISs thus provide a more favorable channel condition for the considered CR system than conventional passive RISs do. We aim to maximize the achievable rate of the SU subject to the interference temperature (IT) constraints on the primary users (PUs) as well as the power budget constraint on the active RIS. Towards this end, we propose an alternating optimization algorithm to solve this rate maximization problem. More specifically, the transmit beamforming vector is obtained by solving a second-order core programming (SOCP) problem, and the reflect beamforming vector is obtained with the aid of the fractional programming (FP) technique. Numerical results are provided to compare the active RIS-aided CR system with the passive RIS-aided one, showing that under the same power budget, the active RIS notably outperforms the passive RIS when they are used to assist the transmission of the SU in the CR system.

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.

Symbiotic radio (SR) is a promising solution to achieve high spectrum- and energy-efficiency due to its spectrum sharing and low-power consumption properties, in which the secondary system achieves its data transmission by backscattering the signal originating from the primary system. In this paper, we are interested in the pilot design and signal detection when the primary transmission adopts orthogonal frequency division multiplexing (OFDM) scheme. In particular, in order to preserve the channel orthogonality among the OFDM sub-carriers, each secondary symbol is designed to span one OFDM symbol. The comb-type pilot is employed by the primary transmission, while the preamble pilot is used by the secondary transmission. With the designed pilot structures, the primary signal can be detected via the conventional methods by treating the secondary signal as a part of the composite channel. Furthermore, the secondary signal can be extracted from the estimated composite channel with the help of the detected primary signal. The bit error rate (BER) performance of the primary and secondary transmissions with both perfect and estimated CSI is analyzed. Simulation results show that the performance of the primary transmission is enhanced thanks to the backscatter link established by the secondary transmission. More importantly, even without the direct link, the primary and secondary transmissions can be supported via only the backscatter link.

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.

Symbiotic radio (SR) is a promising technology for Internet-of-Everything (IoE), which enables the IoE backscatter devices (BDs) to be integrated with an existing primary communication system with mutualistic benefits. In this paper, we consider an SR system where a two-way BD backscatters a portion of the incident signal for the backscatter transmission and receives the remaining part for the information decoding. Due to the nature of backscattering, there however exists a conflict between these two aims for the two-way backscatter communication. To reconcile the conflict and improve the overall performance, we particularly consider that the reconfigurable intelligent surface (RIS)-enabled two-way BD, with each reflecting element achieving the two-way backscatter communication. Based on the proposed system, we first investigate the achievable rates of the interested trans-missions when the RIS transmits its messages over the incident signal with the binary phase-shift keying (BPSK) scheme. We consider the joint design of the transmit beamforming at the primary transmitter and the reflection coefficients at the RIS to minimize the transmit power when these achievable rates meet their requirements. This transmit power minimization problem is then solved with an alternating optimization (AO) algorithm. Simulation results show that under the assistance from the RIS, the proposed two-way SR system is more energy-efficient.

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.

Reconfigurable Intelligent Surface (RIS) is a promising solution to reconfigure the wireless environment in a controllable way. To compensate for the double-fading attenuation in the RIS-aided link, a large number of passive reflecting elements (REs) are conventionally deployed at the RIS, resulting in large surface size and considerable circuit power consumption. In this paper, we propose a new type of RIS, called active RIS, where each RE is assisted by active loads (negative resistance), that reflect and amplify the incident signal instead of only reflecting it with the adjustable phase shift as in the case of a passive RIS. Therefore, for a given power budget at the RIS, a strengthened RIS-aided link can be achieved by increasing the number of active REs as well as amplifying the incident signal. We consider the use of an active RIS to a single input multiple output (SIMO) system. However, it would unintentionally amplify the RIS-correlated noise, and thus the proposed system has to balance the conflict between the received signal power maximization and the RIS-correlated noise minimization at the receiver. To achieve this goal, it has to optimize the reflecting coefficient matrix at the RIS and the receive beamforming at the receiver. An alternating optimization algorithm is proposed to solve the problem. Specifically, the receive beamforming is obtained with a closed-form solution based on linear minimum-mean-square-error (MMSE) criterion, while the reflecting coefficient matrix is obtained by solving a series of sequential convex approximation (SCA) problems. Simulation results show that the proposed active RIS-aided system could achieve better performance over the conventional passive RIS-aided system with the same power budget.

Conventionally, a substantial number of reflecting elements (REs) is deployed at the intelligent reflecting surface (IRS) to mitigate the effect of the double-fading attenuation in the IRS-aided link, leading to a large surface size and considerable power consumption. In this paper, a new type of IRS, called active IRS, is proposed to solve this challenge by allowing each RE to amplify the incident signal with the assistance of the active loads (negative resistances). Thus, given a power budget at the IRS, the IRS-aided link can be enhanced by increasing the number of active REs as well as amplifying the incident signal. Specifically, we consider the use of an active IRS-aided single input multiple output (SIMO) system, in which the received signal-to-noise ratio (SNR) is maximized, by optimizing not only the reflecting coefficient matrix at the IRS but also the receive beamforming at the receiver. To solve this non-convex problem, we propose an alternating optimization algorithm, that iteratively optimizes the two design variables. In particular, the receive beamforming is founded to be in the form of a linear minimum mean square error (MMSE) detector, and the reflecting coefficient matrix is obtained via the Charnes-Cooper transformation and the semi-definite programming (SDP). Simulation results show that under a practical power consumption model, the proposed active IRS-aided system achieves better performance over the conventional passive IRS-aided system with the same power budget.

In this article, a symbiotic radio (SR) system is proposed to support passive Internet of Things (IoT), in which a backscatter device (BD), also called IoT device, is parasitic in a primary transmission. The primary transmitter (PT) is designed to assist both the primary and BD transmissions, and the primary receiver (PR) is used to decode the information from the PT as well as the BD. The symbol period for BD transmission is assumed to be either equal to or much greater than that of the primary one, resulting in parasitic SR (PSR) or commensal SR (CSR) setup. We consider a basic SR system which consists of three nodes: 1) a multiantenna PT; 2) a single-antenna BD; and 3) a single-antenna PR. We first derive the achievable rates for the primary and BD transmissions for each setup. Then, we formulate two transmit beamforming optimization problems, i.e., the weighted sum-rate maximization (WSRM) problem and the transmit power minimization (TPM) problem, and solve these nonconvex problems by applying the semidefinite relaxation (SDR) technique. In addition, a novel transmit beamforming structure is proposed to reduce the computational complexity of the solutions. The simulation results show that for CSR setup, the proposed solution enables the opportunistic transmission for the BD via energy-efficient passive backscattering without any loss in spectral efficiency, by properly exploiting the additional signal path from the BD.

In this paper, we are interested in a symbiotic radio (SR) system, in which a passive full-duplex backscatter device (BD) is parasitic in an active primary transmission. The primary transmitter (PT) with multiple antennas is designed to broadcast common messages to the primary receiver (PR) and the BD, as well as to support passive information transmission from the BD to the PR. To do so, the full-duplex BD uses a fraction of the incident signal from the PT to decode the common messages, and simultaneously transmits its own information to the PR by backscattering the remaining part of the incident signal. We formulate a transmit power minimization problem by jointly designing the beamforming vector at the PT and the power splitting factor at the BD. This problem is first solved by the semi-definite relaxation technique together with a one-dimensional linear exhaustive search over the power splitting factor. Then, a suboptimal but low-complexity solution with closed-form expressions is proposed. Simulation results have shown that the proposed suboptimal solution achieves almost the same performance as the one obtained by the exhaustive search.

Ambient backscatter communication (AmBC) enables a tag to modulate its information bits over ambient RF carriers by intentionally changing its reflection coefficient, thus has emerged as a promising technique to achieve green communications for future Internet-of-Things. In this paper, we model a cooperative AmBC system from a spectrum- sharing perspective, where a cooperative receiver (C-RX) decodes the information from both a multi-antenna primary transmitter (PT) and a single-antenna secondary transmitter (i.e., tag). We consider two scenarios: first, the tag-symbol period equals the PT-symbol period; second, the tag-symbol period is an integer multiple of the PT-symbol period. For each scenario, we analyze the data rate via successive- interference-cancellation (SIC) based decoding, and formulate a problem to maximize the sum rate by optimizing the beamforming vector at the PT. The problems are transformed into semi-definite programming (SDP), and solved by using the technique of semi-definite relaxation (SDR). Furthermore, a novel transmit beamforming structure is proposed to reduce the computational complexity of beamforming optimization. Numerical results show that the cooperative AmBC system can achieve a higher sum rate than a conventional point-to-point system without a backscatter tag.