Wireless powered mobile edge computing (WP-MEC) has been recognized as a promising solution to enhance the computational capability and sustainable energy supply for low-power wireless devices (WDs). However, when the communication links between the hybrid access point (HAP) and WDs are hostile, the energy transfer efficiency and task offloading rate are compromised. To tackle this problem, we propose to employ multiple intelligent reflecting surfaces (IRSs) to WP-MEC networks. Based on the practical IRS phase shift model, we formulate a total computation rate maximization problem by jointly optimizing downlink/uplink IRSs passive beamforming, downlink energy beamforming and uplink multi-user detection (MUD) vector at HAPs, task offloading power and local computing frequency of WDs, and the time slot allocation. Specifically, we first derive the optimal time allocation for downlink wireless energy transmission (WET) to IRSs and the corresponding energy beamforming. Next, with fixed time allocation for the downlink WET to WDs, the original optimization problem can be divided into two independent subproblems. For the WD charging subproblem, the optimal IRSs passive beamforming is derived by utilizing the successive convex approximation (SCA) method and the penalty-based optimization technique, and for the offloading computing subproblem, we propose a joint optimization framework based on the fractional programming (FP) method. Finally, simulation results validate that our proposed optimization method based on the practical phase shift model can achieve a higher total computation rate compared to the baseline schemes.
The objective of the work is to enhance the signal-to-interference-plus-noise ratio (SINR) coverage probability in UAV-assisted 6G wireless networks. Therefore, the work analyzed and compared the coverage probability of conventional and IRS-assisted UAV communications models. The research obtained that the employment of IRS in UAV-assisted wireless networks enhances the SINR coverage probability significantly. Moreover, the installment of IRS in UAV networks reduces the energy consumption of the network.
Distributed intelligent reflecting surfaces (IRSs) deployed in multi-user wireless communication systems promise improved system performance. However, the signal-to-interference-plus-noise ratio (SINR) analysis and IRSs optimization in such a system become challenging, due to the large number of involved parameters. The system optimization can be simplified if users are associated with IRSs, which in turn focus on serving the associated users. We provide a practical theoretical framework for the average SINR analysis of a distributed IRSs-assisted multi-user MISO system, where IRSs are optimiz…
In this letter, we study efficient channel estimation for an intelligent reflecting surface (IRS)-assisted orthogonal frequency division multiplexing (OFDM) system to achieve minimum training time. First, a fast channel estimation scheme with reduced OFDM symbol duration is proposed for arbitrary frequency-selective fading channels. Next, under the typical condition that the IRS-user channel is line-of-sight (LoS) dominant, another fast channel estimation scheme based on the novel concept of sampling-wise IRS reflection variation is proposed. Moreover, the pilot signal and IRS training reflect…
Non-orthogonal multiple access (NOMA) scheme enables serving users with the same resource block i.e. frequency or time by multiplexing the signal of the users. Intelligent reflecting surfaces (IRS) or reconfigurable intelligent surfaces (RIS) is a potential approach for increasing transmission efficiency by modifying signal propagation by tweaking typically passive reflective components. IRS reconfigures the wireless network in this manner to improve system performance. The research considered an IRS-assisted downlink NOMA system. This work modified the reference model by adopting an IRS-speci…
We consider an ambient backscatter communication (AmBC) system aided by an intelligent reflecting surface (IRS). The optimization of the IRS to assist AmBC is extremely difficult when there is no prior channel knowledge, for which no design solutions are currently available. We utilize a deep reinforcement learning-based framework to jointly optimize the IRS and reader beamforming, with no knowledge of the channels or ambient signal. We show that the proposed framework can facilitate effective AmBC communication with a detection performance comparable to several benchmarks under full channel k…
This paper proposes a novel network framework of intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) non-orthogonal multiple access (NOMA) networks, where IRS is used to enhance the NOMA performance and the wireless power transfer (WPT) efficiency of SWIPT. We formulate a problem of minimizing base station (BS) transmit power by jointly optimizing successive interference cancellation (SIC) decoding order, BS transmit beamforming vector, power splitting (PS) ratio and IRS phase shift while taking into account the quality-of-service (QoS) re…
Intelligent reflecting surface (IRS) is a promising technology for beyond 5th Generation of the wireless communications. In fully passive IRS-assisted systems, channel estimation is challenging and should be carried out only at the base station or at the terminals since the elements of the IRS are incapable of processing signals. In this letter, we formulate a tensor-based semi-blind receiver that solves the joint channel and symbol estimation problem in an IRS-assisted multi-user multiple-input multiple-output system. The proposed approach relies on a generalized PARATUCK tensor model of the …
This paper investigates the downlink communications of intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) systems. To maximize the system throughput, we formulate a joint optimization problem over the channel assignment, decoding order of NOMA users, power allocation, and reflection coefficients. The formulated problem is proved to be NP-hard. To tackle this problem, a three-step novel resource allocation algorithm is proposed. Firstly, the channel assignment problem is solved by a many-to-one matching algorithm. Secondly, by considering the IRS reflection coef…
Intelligent reflecting surfaces (IRSs) have shown huge advantages in many potential use cases and thus have been considered a promising candidate for next-generation wireless systems. In this paper, we consider an IRS-assisted multigroup multicast (IRS-MGMC) system in a multiple-input single-output (MISO) scenario, for which the related existing literature is rather limited. In particular, we aim to jointly design the transmit beamformers and IRS phase shifts to maximize the sum rate of the system under consideration. In order to obtain a numerically efficient solution to the formulated non-co…
An intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) massive multiple input multiple output (MIMO) system with transmit antenna selection (TAS) using orthogonal space-time block codes (OSTBC) scheme is proposed in this paper. This system combines TAS and IRS with hybrid analog-digital beamforming (HBF) for 60 GHz mmWave communications in order to exploit the benefits of TAS, OSTBC, analog beamforming (ABF), and transmit digital precoding techniques. The proposed system, however, benefits from the transmit diversity gain of OSTBC scheme as well as from the signal-to-noise r…
Intelligent reflecting surfaces (IRSs) are revolutionary enablers for next-generation wireless communication networks, with the ability to customize the radio propagation environment. To fully exploit the potential of IRS-assisted wireless systems, reflective elements have to be jointly optimized with conventional communication techniques. However, the resulting optimization problems pose significant algorithmic challenges, mainly due to the large-scale non-convex constraints induced by the passive hardware implementations. In this paper, we propose a low-complexity algorithmic framework incor…
An intelligent reflecting surface (IRS) consists of a large number of low-cost reflecting elements, which can steer the incident signal collaboratively by passive beamforming. This way, IRS reconfigures the wireless environment to boost the system performance. In this paper, we consider an IRS-assisted uplink non-orthogonal multiple access (NOMA) system. The objective is to maximize the sum rate of all users under individual power constraint. The considered problem requires a joint power control at the users and beamforming design at the IRS, and is nonconvex. To handle it, semidefinite relaxa…
In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered for the imperfect IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case w…
The analysis and optimization of single intelligent reflecting surface (IRS)-assisted systems have been extensively studied, whereas little is known regarding multiple-IRS-assisted systems. This paper investigates the analysis and optimization of a double-IRS cooperatively assisted downlink system, where a multi-antenna base station (BS) serves a single-antenna user with the help of two multi-element IRSs, connected by an inter-IRS channel. The channel between any two nodes is modeled with Rician fading. The BS adopts the instantaneous CSI-adaptive maximum-ratio transmission (MRT) beamformer, …
Intelligent reflecting surfaces (IRSs) with the ability to reconfigure inherent electromagnetic reflection and absorption characteristics in real-time provide unparalleled prospects to improve wireless connectivity in adverse circumstances. Unmanned aerial vehicles (UAV)-assisted wireless networks are evolved as a reliable solution to combat non-line of sight (NLoS) scenarios. Thereby, the IRS-empowered UAV-assisted cellular networks will be a significant role-player to improve the coverage and user experiences. The paper aimed to minimize the path loss and maximize the achievable data rate in…
This letter investigates the uplink outage performance of intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA). We consider the general case where all users have both direct and reflection links, and all links undergo Nakagami-m fading. We approximate the received powers of the NOMA users as Gamma random variables via moments matching. This allows for tractable expressions of the outage under interference cancellation (IC), while being flexible in modeling various propagation environments. Our analysis shows that under certain conditions, the presence of an IRS m…
In cognitive radio (CR) communication systems, achieving high secondary user (SU) rate in the presence of strong cross-link interference with the primary user (PU) is challenging. In this letter, we exploit the emerging intelligent reflecting surface (IRS) technology to tackle this problem. Specifically, we investigate an IRS-assisted CR communication system where an IRS is deployed to assist in the spectrum sharing between a PU link and an SU link. We aim to maximize the achievable SU rate subject to a given signal-to-interference-plus-noise ratio target for the PU link, by jointly optimizing…
In this paper, we investigate an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system design in a clutter environment. Assisted by an IRS equipped with a uniform linear array (ULA), a multi-antenna base station (BS) is targeted for communicating with multiple communication users (CUs) and sensing multiple targets simultaneously. We consider the IRS-assisted ISAC design in the case with Type-I or Type-II CUs, where each Type-I and Type-II CU can and cannot cancel the interference from sensing signals, respectively. In particular, we aim to maximize th…
Intelligent reflecting surface (IRS) is a promising technology that enables the precise control of the electromagnetic environment in future wireless communication networks. To leverage the IRS effectively, the acquisition of channel state information (CSI) is crucial in IRS-assisted communication systems, which, however, is challenging. In this paper, we propose the optimal pilot power allocation strategy for the channel estimation of IRS-assisted communication systems, which is capable of further improving the achievable rate performance with imperfect CSI. More specifically, first of all, w…
In this letter, we analyze the performance of the intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) systems in the presence of imperfect phase compensation. We derive an upper bound on the imperfect phase compensation to achieve minimum required data rates for each user. Using this bound, we propose an adaptive user pairing algorithm to maximize the network throughput. We then derive bounds on the power allocation factors and propose power allocation algorithms for the paired users to achieve the maximum sum rate or ensure fairness. Through extensive …
In this paper, we study a new intelligent refracting surface (IRS)-assisted high-mobility communication with the IRS deployed in a high-speed moving vehicle to assist its passenger's communication with a static base station (BS) on the roadside. The vehicle's high Doppler frequency results in a fast fading channel between the BS and the passenger/user, which renders channel estimation for the IRS with a large number of refracting elements a more challenging task as compared to the conventional case with low-mobility users only. In order to mitigate the Doppler effect and reap the full IRS pass…
This paper studies an intelligent reflecting surface (IRS)-assisted multiuser multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system. In this system, a multi-antenna access point (AP) uses transmit beamforming to send both information and energy signals to a set of receivers each for information decoding (ID) or energy harvesting (EH), and a dedicatedly deployed IRS properly controls its reflecting phase shifts to form passive reflection beams for facilitating both ID and EH at receivers. Under this setup, we jointly optimize the (active) inform…
Using stochastic geometry tools, we develop a comprehensive framework to analyze the downlink coverage probability, ergodic capacity, and energy efficiency (EE) of various types of users (e.g., users served by direct base station (BS) transmissions and indirect intelligent reflecting surface (IRS)-assisted transmissions) in a cellular network with multiple BSs and IRSs. The proposed stochastic geometry framework can capture the impact of channel fading, locations of BSs and IRSs, arbitrary phase-shifts and interference experienced by a typical user supported by direct transmission and/or IRS-a…
The realization of practical intelligent reflecting surface (IRS)-assisted multi-user communication (IRS-MUC) systems critically depends on the proper beamforming design exploiting accurate channel state information (CSI). However, channel estimation (CE) in IRS-MUC systems requires a significantly large training overhead due to the numerous reflection elements involved in IRS. In this paper, we adopt a deep learning approach to implicitly learn the historical channel features and directly predict the IRS phase shifts for the next time slot to maximize the average achievable sum-rate of an IRS…
Intelligent reflecting surfaces (IRSs) are emerging as promising enablers for the next generation of wireless communication systems, because of their ability to customize favorable radio propagation environments. However, with the conventional passive architecture, IRSs can only adjust the phase of the incident signals limiting the achievable beamforming gain. To fully unleash the potential of IRSs, in this paper, we consider a more general IRS architecture, i.e., active IRSs, which can adapt the phase and amplify the magnitude of the reflected incident signal simultaneously with the support o…
Intelligent reflecting surfaces (IRSs) have been introduced into wireless communications systems due to their great potential to smartly customize and reconfigure radio propagation environments in a cost-effective manner. Despite the promising advantages of IRSs, academic research on IRSs is still in its infancy. In particular, the design and analysis of IRS-assisted wireless communication systems critically depend on an accurate and tractable modeling of the IRS. In this article, we first present and compare three IRS models, namely the conventional independent diffusive scatterer-based model…
Due to the passive nature of Intelligent Reflecting Surface (IRS), channel estimation is a fundamental challenge in IRS-aided wireless networks. Particularly, as the number of IRS reflecting elements and/or that of IRS-served users increase, the channel training overhead becomes excessively high. To tackle this challenge, we propose in this paper a new anchor-assisted two-phase channel estimation scheme, where two anchor nodes, namely A1 and A2, are deployed near the IRS for helping the base station (BS) to acquire the cascaded BS-IRS-user channels. Specifically, in the first phase, the partia…
In this letter, we optimize the channel estimator of the cascaded channel in an intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) multi-antenna system. In this system, the receiver is equipped with a hybrid architecture adopting quantized beamforming. Different from traditional multiple-input multiple-output (MIMO) systems, the design of channel estimation is challenging since the IRS is usually a passive array with limited signal processing capability. We derive the optimized channel estimator in a closed form by reformulating the problem of cascaded channel estimation in…
Channel estimation is a practical challenge for intelligent reflecting surface (IRS) aided wireless communication. As the number of IRS reflecting elements or IRS-aided users increases, the channel training overhead becomes excessively high, which results in long delay and low throughput in data transmission. To tackle this challenge, we propose in this paper a new anchor-assisted channel estimation approach, where two anchor nodes, namely A1 and A2, are deployed near the IRS for facilitating its aided base station (BS) in acquiring the cascaded BS-IRS-user channels required for data transmiss…
In this paper, we focus on the coverage probability of a double-intelligent reflecting surface (IRS) assisted wireless network and study the impact of multiplicative beamforming gain and correlated Rayleigh fading. In particular, we obtain a novel closed-form expression of the coverage probability of a single-input single-output (SISO) system assisted by two large IRSs while being dependent on the corresponding arbitrary reflecting beamforming matrices (RBMs) and large-scale statistics in terms of correlation matrices. Taking advantage of the large-scale statistics, i.e., statistical channel s…
In this paper, we study an unmanned aerial vehicle (UAV) communication system, where a ground node (GN) communicate with a UAV assisted by intelligent reflecting surface (IRS) in the presence of a jammer with imperfect location information. We aim to improve the achievable average rate via the joint robust design of UAV trajectory, IRS passive beamforming and GN's power allocation. However, the formulated optimization problem is challenging to solve due to its non-convexity and coupled variables. To overcome the difficulty, we propose an alternating optimization (AO) based algorithm to solve i…
In the intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information (CSI) is a crucial impediment for achieving the passive beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-assisted communications, $KMN+KM$ channel coefficients should be estimated if the passive IRS cannot estimate its channels with the base station (BS) and users due to its lack of radio frequency (RF) chains, where $K$, $N$ and $M$ denote the number of users, reflecting …
In this work, we characterize the outage probability (OP) of an intelligent reflecting surface (IRS) assisted multi-user multiple-input-single-output (MU-MISO) communication system. Using a two-step approximation method, we approximate the signal-to-interference-plus-noise ratio (SINR) for any downlink user by a Log-Normal random variable. The impact of various system parameters is studied using the closed-form expression of OP. It is concluded that the position of IRS has a critical role, but an appropriate increase in the number of IRS elements would help to compensate for the loss in perfor…
The high reflect beamforming gain of the intelligent reflecting surface (IRS) makes it appealing not only for wireless information transmission but also for wireless power transfer. In this letter, we consider an IRS-assisted wireless powered communication network, where a base station (BS) transmits energy to multiple users grouped into multiple clusters in the downlink, and the clustered users transmit information to the BS in the manner of hybrid non-orthogonal multiple access and time division multiple access in the uplink. We investigate optimizing the reflect beamforming of the IRS and t…
In intelligent reflecting surface (IRS) assisted communication systems, the acquisition of channel state information (CSI) is a crucial impediment for achieving the beamforming gain of IRS because of the considerable overhead required for channel estimation. Specifically, under the current beamforming design for IRS-assisted communications, $KMN+KM$ channel coefficients should be estimated, where $K$, $N$ and $M$ denote the numbers of users, IRS reflecting elements, and antennas at the base station (BS), respectively. To accurately estimate such a large number of channel coefficients within a …
In this paper, we propose a fairness-aware rate maximization scheme for a wireless powered communications network (WPCN) assisted by an intelligent reflecting surface (IRS). The proposed scheme combines user scheduling based on time division multiple access (TDMA) and (mechanical) angular displacement of the IRS. Each energy harvesting user (EHU) has dedicated time slots with optimized durations for energy harvesting and information transmission whereas, the phase matrix of the IRS is adjusted to focus its beam to a particular EHU. The proposed scheme exploits the fundamental dependence of the…
In this paper, a novel intelligent reflecting surface (IRS)-assisted wireless powered communication network (WPCN) architecture is proposed for power-constrained Internet-of-Things (IoT) smart devices, where IRS is exploited to improve the performance of WPCN under imperfect channel state information (CSI). We formulate a hybrid access point (HAP) transmit energy minimization problem by jointly optimizing time allocation, HAP energy beamforming, receiving beamforming, user transmit power allocation, IRS energy reflection coefficient and information reflection coefficient under the imperfect CS…
In this paper, we investigate the outage performance of an intelligent reflecting surface (IRS)-assisted non-orthogonal multiple access (NOMA) uplink, in which a group of the surface reflecting elements are configured to boost the signal of one of the user equipments (UEs), while the remaining elements are used to boost the other UE. By approximating the received powers as Gamma random variables, tractable expressions for the outage probability under NOMA interference cancellation are obtained. We evaluate the outage over different splits of the elements and varying pathloss differences betwee…
Intelligent reflecting surface (IRS) is a promising technology for the 6th generation of wireless systems, realizing the smart radio environment concept. In this paper, we present a novel tensor-based receiver for IRS-assisted multiple-input multiple-output communications capable of jointly estimating the channels and the transmitted data streams in a semi-blind fashion. Assuming a fully passive IRS architecture and introducing a simple space-time coding scheme at the transmitter, the received signal model can be advantageously built using the PARATUCK tensor model, which can be seen as a hybr…
In this letter, we investigate an unmanned aerial vehicle (UAV) communication system, where an intelligent reflecting surface (IRS) is deployed to assist in the transmission from a ground node (GN) to the UAV in the presence of a jammer. We aim to maximize the average rate of the UAV communication by jointly optimizing the GN's transmit power, the IRS's passive beamforming and the UAV's trajectory. However, the formulated problem is difficult to solve due to the non-convex objective function and the coupled optimization variables. Thus, to tackle it, we propose an alternating optimization (AO)…
In a practical massive MIMO (multiple-input multiple-output) system, the number of antennas at a base station (BS) is constrained by the space and cost factors, which limits the throughput gain promised by theoretical analysis. This paper thus studies the feasibility of adopting the intelligent reflecting surface (IRS) to further improve the beamforming gain of the uplink communications in a massive MIMO system. Under such a novel system, the central question lies in whether the IRS is able to enhance the network throughput as expected, if the channel estimation overhead is taken into account.…
In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a large number of passive reflecting elements. In the literature, it has been proved that nonorthogonal multiple access (NOMA) can achieve the capacity region when the channels are quasi-degraded. However, in a conventional communication scenario, it is difficult to guarantee the quasi-degradation, because the channels are determined by the propagation environments and cannot be reconfigured. To overcome this difficulty, we foc…
Beamforming design for intelligent reflecting surface (IRS)-assisted multi-user communication (IRS-MUC) systems critically depends on the acquisition of accurate channel state information (CSI). However, channel estimation (CE) in IRS-MUC systems causes a large signaling overhead for training due to the large number of IRS elements. In this paper, taking into account user mobility, we adopt a deep learning (DL) approach to implicitly learn the historical line-of-sight (LoS) channel features and predict the IRS phase shifts to be adopted for the next time slot for maximization of the weighted s…
The fundamental intelligent reflecting surface (IRS) deployment problem is investigated for IRS-assisted networks, where one IRS is arranged to be deployed in a specific region for assisting the communication between an access point (AP) and multiple users. Specifically, three multiple access schemes are considered, namely non-orthogonal multiple access (NOMA), frequency division multiple access (FDMA), and time division multiple access (TDMA). The weighted sum rate maximization problem for joint optimization of the deployment location and the reflection coefficients of the IRS as well as the …
Intelligent reflecting surfaces (IRSs) are envisioned as a low-cost solution to achieve high spectral and energy efficiency in future communication systems due to their ability to customize wireless propagation environments. Although resource allocation design for IRS-assisted multiuser wireless communication systems has been exhaustively investigated in the literature, the optimal design and performance of such systems are still not well understood. To fill this gap, in this paper, we study optimal resource allocation for IRS-assisted multiuser multiple-input single-output (MISO) systems. In …
In this paper, we study the resource allocation for an intelligent reflecting surface (IRS)-assisted uplink system, where the base station is equipped with multiple antennas. We propose to jointly optimize the transmit power of the users, active beamforming at the base station, and passive beamforming at the IRS to maximize the overall system energy efficiency while maintaining users' minimum rate constraints. This problem belongs to a highly intractable non-convex bi-quadratic programming problem, for which an iterative solution based on block coordinate descent is proposed. Extensive simulat…
This work studies secure transmission in intelligent reflecting surfaces (IRS)-assisted MIMO systems when an active eavesdropper is available in the network. We consider a scenario in which the eavesdropper performs an active pilot attack to contaminate the channel estimation at the base station. Invoking the method of secure regularized zero forcing, we develop an algorithm that designs beamforming vectors, as well as phase-shifts at the IRS, such that the active attacker is blinded. Our numerical investigations confirm that the proposed algorithm can suppress the active eavesdropper effectiv…
We investigate the joint uplink-downlink configuration of an intelligent reflecting surface (IRS) for multi-user frequency-division-duplexing (FDD) and time-division-duplexing (TDD) systems. This is motivated in FDD since uplink and downlink transmissions occur simultaneously and hence an IRS must be jointly configured for both transmissions. In TDD, while a joint design is not strictly necessary, it can significantly reduce feedback overhead, power consumption, and configuration periods associated with updating the IRS. To compute the trade-off between uplink and downlink rates achieved by a …
