IRS-Aided Wireless Relaying: Deployment Strategy and Capacity Scaling

Intelligent reflecting surface (IRS) has emerged as a cost-efficient technique to improve the wireless network’s capacity and performance. Existing works on IRS have mainly considered IRS being deployed in the environment to dynamically control the wireless channels between the base station (BS) and its served users in favor of their communications. In contrast, we propose in this paper a new integrated IRS-BS architecture by deploying IRSs inside the BS’s antenna radome to directly reconfigure the signal radiation to/from the BS’s antennas. In other words, the IRSs can be considered as auxiliary passive arrays with real-time reconfigurability equipped at the BS to enhance its communication performance cost-effectively. Since the distance between the integrated IRSs and BS’s antenna array is practically small (in the order of several to tens of wavelengths), the path loss among them is significantly reduced as compared to conventional IRS deployed much farther away from the BS, while the real-time control of the IRS’s reflection by the BS becomes easier to implement. However, the resultant near-field channel model also becomes drastically different from its far-field counterpart for conventional far-away IRSs in the literature. Thus, we propose an element-wise channel model for IRS to characterize the channel vector between each single-antenna user and the antenna array of the BS, which includes the direct (without any IRS’s reflection) as well as the single and double IRS-reflection channel components. Based on this channel model, we formulate a problem to optimize the reflection coefficients of all IRS reflecting elements for maximizing the uplink sum-rate of the users. By considering two typical cases with/without perfect channel state information (CSI) at the BS, the formulated problem is solved efficiently by adopting the successive refinement method and iterative random phase algorithm (IRPA), respectively. Numerical results validate the substantial capacity gain of the integrated IRS-BS architecture over the conventional multi-antenna BS without integrated IRS. Moreover, the proposed algorithms significantly outperform other benchmark schemes in terms of sum-rate, and the IRPA without CSI can approach the performance upper bound with perfect CSI as the training overhead increases.

In this paper, we build up a new intelligent reflecting surface (IRS) aided multiple-input multiple-output (MIMO) channel model, named the cascaded LoS MIMO channel, that is applicable to both near-field and far-field scenarios. The proposed channel model consists of a transmitter (Tx) and a receiver (Rx) both equipped with uniform linear arrays (ULAs), and an IRS is used to enable communications between the transmitter and the receiver through the line-of-sight (LoS) links seen by the IRS. When modeling the reflection of electromagnetic waves at the IRS, we take into account the curvature of the wavefront on different reflecting elements. Based on the established channel model, we show that an IRS-assisted MIMO channel is able to support spatial multiplexing solely by the cascaded LoS links. We generalize the notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Rayleigh distance</i> originally coined for the single-hop MIMO channel to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">full multiplexing region (FMR)</i> for the cascaded LoS MIMO channel, where the FMR is the union of all the Tx-IRS and IRS-Rx distance pairs that enable full multiplexing communication. We derive an inner bound of the FMR under a special passive beamforming (PB) strategy named reflective focusing, and provide the corresponding orientation settings of the antenna arrays that achieve full multiplexing.

The integration of intelligent reflecting surfaces (IRS) into free-space optical (FSO) communication systems is considered as a promising and innovative approach to overcoming existing challenges due to the strict line-of-sight (LoS) requirements faced by conventional FSO setups, thereby ensuring more flexible and controllable links and expanding the communication coverage area. Nonetheless, the configuration of IRS-assisted FSO systems remains relatively novel, requiring investigation into optimizing IRS placement to enhance system performance while mitigating interference and obstacles in dynamic environmental conditions. This work aims to evaluate the improvement of the system performance achieved through optimized IRS positioning while accounting for the main degrading factors inherent in FSO systems and IRS design. We present a comprehensive model for a multilink terrestrial IRS-assisted FSO system, taking into consideration key degrading factors such as pointing errors stemming from both transmitter and IRS jitter, IRS dimensions, and turbulence-induced fading. Furthermore, we derive closed-form expressions for the probability density function of channel coefficients, average bit error rate, and outage probability. Our results indicate that optimal IRS placement is in proximity to the transmitter, taking into account all channel impairments. Furthermore, we showed that optimal IRS placement tends to shift towards the receiver side as the IRS jitter increases. Consequently, the analysis presented offers valuable insights for efficiently designing IRS-assisted FSO systems, particularly regarding IRS placement in the presence of pointing errors.

We consider a wireless communication system, where a transmitting source is assisted by both a reconfigurable intelligent reflecting surface (IRS) and a decode-and-forward half-duplex relay (hybrid IRS-relay scheme) to communicate with a destination receiver. All devices are equipped with multiple antennas, and transmissions occur in two stages. In stage 1, the source splits the transmit message into two sub-messages, transmitted to the destination and the relay, respectively, using block diagonalization to avoid interference. Both transmissions will benefit from the IRS. In stage 2, the relay re-encodes the received sub-message and forwards it (still through the IRS) to the destination. We optimize power allocations, beamformers, and configurations of the IRS in both stages, in order to maximize the achievable rate at the destination. We compare the proposed hybrid approach with other schemes (with/without relay and IRS), and confirm that high data rate is achieved for the hybrid scheme in case of optimal IRS configurations.

Intelligent reflecting surface (IRS) has emerged as an innovative and disruptive solution to boost the spectral and energy efficiency and enlarge the coverage of wireless communication systems. However, the existing literature on IRS mainly concentrates on wireless communication systems assisted by single or multiple distributed IRSs, which are not always effective. In view of this issue, this paper considers a special double-IRS-assisted wireless communication system, where IRS1 and IRS2 are deployed near the base station (BS) and the user, respectively, and the transmitted signals reach the user via the cascaded BS-IRS1-IRS2-user channel only. We cooperatively optimize transmit and passive beamforming on the two IRSs based on the particle swarm optimization (PSO) algorithm to maximize the received signal power. Simulation indicates that despite no direct line-of-sight (LoS) path from the BS to the user, an excellent signal-to-noise ratio (SNR) is available at the receiver with the aid of two IRSs, which demonstrates that it is feasible to assist communication by double reflection links composed of two IRSs. Additionally, we unexpectedly find that when the positions of the two IRSs are fixed, by exchanging the positions of the BS and the user, the obtainable SNRs are similar.

In this work, we consider an intelligent reflecting surface (IRS)-assisted covert wireless detection system, where a transmitter aims to improve the detection accuracy of its transmission at a legitimate receiver, but avoid this transmission being detected by a warden. Considering Rician fading channels and a bounded noise uncertainty model, the detection performance at the legitimate receiver and warden is thoroughly analyzed. Then, the optimal design of the transmit power and IRS reflection matrix is proposed for maximizing the detection performance at the legitimate transceiver subject to a covertness constraint (i.e., the detection accuracy at the warden is less than a specific tolerable level). Our design is solely based on the line-of-sight (LoS) channel components and thus partially eliminates the need for acquiring the IRS's instantaneous channels, which takes a step towards the practical deployment of IRS. Our examination shows that IRS can still improve the covert detection performance even when only the LoS channel components are known and the improvement increases as the LoS components become more dominant.

Intelligent Reflecting Surfaces (IRS) is a groundbreaking innovative technique to boost energy and spectral efficiency in upcoming wireless systems, enabling simultaneous wireless information and power transfer (SWIPT). This paper optimizes Energy Harvesting Efficiency (EHE) in a multi-input multi-output (MIMO) SWIPT system, where an access point (AP)/base station (BS) uses an IRS to serve multi energy receivers (ERs) and information receivers (IRs). We formulate an EHE optimization problem, designing active and passive beamforming while satisfying the AP/BS power constraints, IRS unit-modulus constraints and IR rate demands in a linear EH model. The Linear Matrix Inequalities (LMIs) are approximated for efficient solutions. And second-order cone programming (SOCP) is solved via convex optimization (CVX), while the penalty convex-concave procedure (CCP) guarantees convexity to non-convex problems. Next, an alternating optimization (AO)-reliant iterative algorithm derived sub-optimal solutions with slack variables. According to simulation results, for all ERs within a linear EH design/model, the proposed algorithm improves total EHE by 40% to 45% compared to randomize, No-IRS, and decode-and-forward (DF) relay strategies. Ultimately, highlighting IRS’s benefit in improving quality of service (QoS) by tweaking its elements and AP/BS antennas.

We consider an intelligent reflecting surface (IRS)-assisted communication system as a cost-effective technique to enhance secrecy rate performance in physical-layer security (PLS) systems. In this letter, the randomized radiation (RR)-based PLS algorithm, which uses active antenna arrays to randomize the radiation pattern, is adopted in IRS through passive beamforming. We show that RR cannot be simply applied to IRS because the secrecy rate is subject to the phase-dependent amplitude variations in IRS. Therefore, we provide an exact and closed-form expression for the secrecy rate of RR using IRS. Based on the analysis, we introduce a constant phase shift into the IRS elements and identify it as a key parameter to optimize the secrecy performance through a genetic algorithm.

Combining intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) offers a new degree of freedom to improve the coverage performance. However, it is more challenging to secure the air-ground transmission, due to the line-of-sight (LoS) links established by UAV. Since IRS is a promising solution for wireless environment reconfiguration, in this paper, we propose an aerial IRS-assisted secure transmission design in wireless networks. In particular, an access point (AP) equipped with a uniform planar array serves several single-antenna legitimate users in the presence of multiple single-antenna eavesdroppers, whose precise positions are unknown. An IRS is mounted on the UAV to help establish desired virtual LoS links between the AP and legitimate users, while ensuring their security. We aim to maximize the worst-case sum secrecy rate by jointly optimizing the hovering position of UAV, the transmit beamforming of AP and the phase shifts of IRS, subject to the requirement of minimum rate for legitimate users. To tackle this non-convex problem, we first decompose it into three subproblems, which are transformed into convex ones via successive convex approximation. An alternating algorithm is then proposed to solve them iteratively. Simulation results show the effectiveness of the proposed scheme and the security improvement by the joint optimization.

In many intelligent reflecting surface (IRS) aided communication systems, the IRS is deployed to provide a line-of-sight (LOS) link between the transmitter and receiver. In order to maximize the efficiency of the system, deploying the IRS at the correct position and orientation is important. We propose a method to find the optimal IRS orientation that maximizes the received power or achievable rate at locations within a desired geographical area. As shown through both analytical and simulation results, the proposed methodology on optimizing IRS orientation based on the receiver or transmitter locations significantly improves the overall system performance. For example, there is an approximately 8.1 bps/Hz achievable rate improvement by installing the IRS at the optimal orientation compared to an arbitrary orientation in a typical deployment scenario.

This letter studies the joint active and passive beamforming in intelligent reflecting surface (IRS)-enhanced wireless powered mobile edge computing (MEC) networks, in which a hybrid access point (HAP) is deployed to charge multiple wireless devices (WDs) and assist in computation of the offloaded tasks from the WDs. An IRS is deployed to enhance the downlink wireless power transfer (WPT) and the uplink tasks offloading (TO). To maximize the systems’ sum computation rate, an optimization problem is formulated by jointly optimizing the time assignment of WPT and TO, the active beamforming at the HAP, the transmit power and computing frequency of the WDs, and the passive beamforming at the IRS. To tackle the non-convex problem, we present an efficient algorithm by utilizing the alternating optimization (AO) and semidefinite relaxation (SDR) techniques. Simulation results show that by deploying IRS in the system, a significant computation rate gain can be achieved. Especially, when the IRS is closer to the WDs or the HAP, the much higher computation rate can be reached.

Intelligent reflecting surfaces (IRSs) are a promising technology for future-generation wireless networks by extending coverage region to blind spots and increasing mmWave propagation paths in non-line of sight environments. User association (UA) in dense millimeter wave (mmWave) networks is vital to characterizing connections among base stations (BSs) and mobile users for load balancing, interference management, and maximizing network utility. However, it has yet to be examined thoroughly in a multi-IRS-aided network. This paper presents a new UA scheme that takes cell interference into account for a multi-cell mmWave cellular network aided with multiple IRSs. We formulate a network spectral efficiency maximization problem by jointly optimizing active beamforming (AB) at the BSs, passive beamforming (PB) at the IRSs, and user-BS association with consideration of the impact of IRSs. We then propose a computationally efficient iterative algorithm based on alternating optimization (AO) to resolve this intractable mixed-integer non-convex problem. A fractional programming technique is used to optimize active beamforming at the BSs and passive beamforming at the IRSs, and a penalization method combined with successive convex programming is applied for UA optimization, which is shown to reach the optimal solution. Simulation results show significant performance improvements obtained by the proposed algorithm, providing higher spectral efficiency compared to several benchmark algorithms, while having a low computational complexity.

UAV-mounted IRS assisted wireless powered mobile edge computing systems: Joint beamforming design, resource allocation and position optimization

Multi-UAV and IRS placement for secure data transmission in NOMA-enabled wireless networks

Intelligent Reflecting Surface (IRS) is envisioned as a revolutionary solution for providing high data rate communication, better signal coverage and physical layer security through controlling the transmission environment of electromagnetic (EM) wave. In this paper, based on a single IRS and millimeter channel model, the optimal multi-user transmission sum rate is derived with the maximal ratio combining (MRC) beamformer. The conditions to achieve such a maximum sum rate are expressed as a function of placement of transceivers, number of IRS elements and its spacing. We first transformed the single IRS assisted non-scattering mmWave channel into a high-rank multiple-in multiple-out (MIMO) channel. The result shows that even without rich scattering, each single antenna user can enjoy the maximal passive beamforming gain while keeping spatial orthogonality to leverage the maximal spatial diversity when the corresponding conditions are satisfied. Simulation results verify the existence and accuracy of optimal placement of multi-user transmission and present that the transmission sum rate of IRS channel scales by the number of IRS elements with different spacing settings.