Robust Transmission Design Research Articles

Robust Transmission Design for RIS-Assisted Multi-Cluster Wireless Powered Communications With Hardware Impairments

Robust Transmission Design for RIS-Assisted Multi-Cluster Wireless Powered Communications With Hardware Impairments

Robust transmission design for active IRS-aided multiuser MIMO cognitive radio systems with non-linear energy harvesting models

Robust transmission design for active IRS-aided multiuser MIMO cognitive radio systems with non-linear energy harvesting models

Outage Constrained Robust Transmission Design for IRS-Aided Secure Communications With Direct Communication Links

Outage Constrained Robust Transmission Design for IRS-Aided Secure Communications With Direct Communication Links

Robust Transmission Design for RIS-aided Full-Duplex-RSMA V2X Communications via Multi-agent DRL

Robust Transmission Design for RIS-aided Full-Duplex-RSMA V2X Communications via Multi-agent DRL

Robust Transmission Design for RIS-Assisted Integrated Sensing and Communication Systems

Robust Transmission Design for RIS-Assisted Integrated Sensing and Communication Systems

Performance Analysis and Optimization of IRS-Aided Covert Communication With Hardware Impairments

Residual hardware impairments widely exist in transceivers and intelligent reflecting surface (IRS) in practical systems, which lead to serious signal distortion, causing performance loss and covert transmission challenging. In this paper, we study the robust transmission design for an IRS-aided covert communication system in the presence of transceiver and IRS hardware impairments. To maximize the signal-to-noise ratio at the legitimate receiver and satisfy the covertness requirement, the transmit power at the source and the reflection coefficients at the IRS are jointly optimized. Since the optimization variables are coupled, an alternating optimization algorithm is proposed to solve the optimization problem. Specifically, in each iteration, the analytical expression of the optimal transmit power is obtained, and the penalty successive convex approximation algorithm is adopted to obtain the optimal reflection coefficients. Numerical results show the performance loss caused by hardware impairments. Besides, by comparing the values of Kullback-Leibler divergence, results also illustrate that the proposed transmission scheme is more robust to the hardware impairments, as the nonrobust designed parameters can not satisfy the covert constraint.

Robust Transmission Design for RIS-Aided Wireless Communication With Both Imperfect CSI and Transceiver Hardware Impairments

Reconfigurable intelligent surface (RIS) has recently been regarded as a potential technique to enhance the performance of wireless communication systems by creating additional communication links. However, it is almost impossible to get the perfect channel state information (CSI) from the base station (BS) to the Internet of Things Devices (IoTDs) and the RIS-related channels. Furthermore, residual transceiver hardware impairments inevitably affect the performance of wireless communication systems. Hence, we study the robust design for an RIS-aided wireless communication system based on the imperfect CSI and hardware impairments. Minimizing the power consumption of BS is formulated by ensuring the minimum signal-to-interference-plus-noise ratio (SINR) demands of the IoTDs and the unit-modulus constraints of the RIS. Specifically, after approximating the nonconvex constraints by using the S-procedure and the successive convex approximation (SCA) methods, we adopt the block coordinate descent (BCD) technique to iteratively optimize one set of variables while keeping the other variables fixed in various channel uncertainty scenarios. Simulation results demonstrate that the influence of transceiver hardware impairments can be effectively decreased by deploying RIS even with channel uncertainty, which is more advantageous than increasing the number of BS’s antennas.

考虑硬件损耗的智能反射面辅助无线携能通信系统

In order to verify the impact of transceiver hardware impairments on the performance of communication system, we explore the robust transmission design of an intelligent reflecting surface (IRS) aided simultaneous wireless information and power transfer (SWIPT) communication system in consideration of hardware impairments of transceiver. Under the constraints of maximum transmitting power of base station, the minimum receiving energy of the energy collector and IRS passive beamforming, the optimization objective is set to maximize the weighted sum rate of all information receivers. And the block coordinate descent (BCD) algorithm is used to decompose the optimization problem into multiple optimization subproblems for alternate optimization. The Lagrange dual method and maximization minimization (MM) algorithm are respectively adopted to solve the optimization problems of active beamforming and IRS passive beamforming. Simulation results validate the impact of transceiver hardware impairments on system performance, and also confirm that the hardware impairment at information receiver is more obvious than the hardware impairment at base station transmitter.

Robust transmission design for artificial noise aided multiuser broadcast system in inaccurate channel state information scenario with users of different importance

In this article, robust beamforming (BF) and artificial noise (AN) design method is proposed for multiuser broadcast secure transmission under secrecy outage probability (SOP) constraints. A special scenario is assumed that the transmitter cannot obtain the accurate channel state information (CSI) of the users' channel, and different users have different priorities and importance. This special scenario makes traditional BF algorithms and AN design methods unable to guarantee the effective and secure transmission of information. To deal with intractable non-convex problems in this new design, a series of optimization methods like Bernstein-type inequality (BTI) and S-Procedure are employed to transform these problems into solvable functions. Moreover, a search algorithm is explored for simplifying the computational complexity of the optimization algorithm. After that, the new robust algorithm is compared with former methods in inaccurate CSI scenarios by numerical simulation, which shows the advantages of our algorithm.

Special issue on reconfigurable intelligent surface for B5G & 6G

Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) is recently recognized as one of the most promising technologies to effectively increase coverage and improve communication performance for future wireless communications beyond 5G and 6G (B5G & 6G). Specifically, the RIS is a planar surface consisting of an array of passive reflecting elements, each of which can independently induce a controllable reflection coefficient on the incident signal. By installing an RIS on the facade of buildings, an additional virtual line of sight (LoS) link can be established between the base station (BS) and the user. By judiciously adjusting the phase shifts of the reflecting elements, the reflected signal can be constructively superimposed with the signal from the direct path to enhance the desired signal power or destructively mitigate unfavourable signals such as multi-user interference or signal leakage to eavesdroppers. The RIS is less expensive to deploy than conventional active transmitters since its reflecting elements only passively reflect the incoming signal without any signal processing operations and does not require costly and power-hungry radio frequency (RF) chains. Moreover, it is lightweight and has limited layer thickness, so it can be easily integrated into the environment. Despite the above-mentioned appealing advantages of RIS, it also brings some new signal processing challenges such as channel estimation, robust transmission design, angle/position estimation, distributed algorithm design, etc.

Robust security transmission design for multi-user peer-to-peer wireless relay networks

In this article, we studied the robust security transmission design for multi-user peer-to-peer relay networks, where all users demand secure communication and the eavesdropper is passive. Although the previous researches have designed the physical-layer security schemes under perfect channel state information, this study focuses on investigating the robust transmission design in the presence of a passive eavesdropper. Our goal is to maximize the artificial noise power to confuse the passive eavesdropper and subject to the worst-case signal-to-interference-noise-ratio constraints for all users under a bounded spherical region for the norm of the channel state information error vector from the relays to the destinations and the individual power constraints of all relay nodes. Mathematically, the original robust problem is difficult to solve due to its non-linearity and non-convexity. We propose to adopt S-Procedure and rank relaxation techniques to convert it to a semidefinite programming convex problem. The numerical results show the advantage of the proposed robust method.

Robust Transmission Design for RIS-Aided Communications With Both Transceiver Hardware Impairments and Imperfect CSI

Reconfigurable intelligent surface (RIS) or intelligent reflecting surface (IRS) has recently been envisioned as one of the most promising technologies in the future sixth-generation (6G) communications. In this letter, we consider the joint optimization of the transmit beamforming at the base station (BS) and the phase shifts at the RIS for an RIS-aided wireless communication system with both hardware impairments and imperfect channel state information (CSI). Specifically, we assume both the BS-user channel and the BS-RIS-user channel are imperfect due to the channel estimation error, and we consider the channel estimation error under the statistical CSI error model. Then, the transmit power of the BS is minimized, subject to the outage probability constraint and the unit-modulus constraints on the reflecting elements. By using Bernstein-type inequality and semidefinite relaxation (SDR) to reformulate the constraints, we transform the optimization problem into a semidefinite programming (SDP) problem. Numerical results show that the proposed robust design algorithm can ensure communication quality of the user in the presence of both hardware impairments and imperfect CSI.

Secure Wireless Communication in RIS-Aided MISO System With Hardware Impairments

In practice, residual transceiver hardware impairments inevitably lead to distortion noise which causes the performance loss. In this letter, we study the robust transmission design for a reconfigurable intelligent surface (RIS)-aided secure communication system in the presence of transceiver hardware impairments. We aim for maximizing the secrecy rate while ensuring the transmit power constraint on the active beamforming at the base station and the unit-modulus constraint on the passive beamforming at the RIS. To address this problem, we adopt the alternate optimization method to iteratively optimize one set of variables while keeping the other set fixed. Specifically, the successive convex approximation (SCA) method is used to solve the active beamforming optimization subproblem, while the passive beamforming is obtained by using the semidefinite program (SDP) method. Numerical results illustrate that the proposed transmission design scheme is more robust to the hardware impairments than the conventional non-robust scheme that ignores the impact of the hardware impairments.

A Framework of Robust Transmission Design for IRS-Aided MISO Communications With Imperfect Cascaded Channels

Intelligent reflection surface (IRS) has recently been recognized as a promising technique to enhance the performance of wireless systems due to its ability of reconfiguring the signal propagation environment. However, the perfect channel state information (CSI) is challenging to obtain at the base station (BS) due to the lack of radio frequency (RF) chains at the IRS. Since most of the existing channel estimation methods were developed to acquire the cascaded BS-IRS-user channels, this paper is the first work to study the robust beamforming based on the imperfect cascaded BS-IRS-user channels at the transmitter (CBIUT). Specifically, the transmit power minimization problems are formulated subject to the worst-case rate constraints under the bounded CSI error model and the rate outage probability constraints under the statistical CSI error model, respectively. After approximating the worst-case rate constraints by using the S-procedure and the rate outage probability constraints by using the Bernstein-type inequality, the reformulated problems can be efficiently solved. Numerical results show that the negative impact of the CBIUT error on the system performance is greater than that of the direct CSI error.

Robust Beamforming With Pilot Reuse Scheduling in a Heterogeneous Cloud Radio Access Network

This paper considers a downlink ultradense heterogeneous cloud radio access network, which guarantees seamless coverage and can provide high date rates. In order to reduce channel state information (CSI) feedback overhead, incomplete intercluster CSI is considered, i.e., each remote radio head or macro base station only measures the CSI from user equipments (UEs) in its serving cluster. To reduce pilot consumption, pilot reuse among UEs is assumed, resulting in imperfect intracluster CSI. A two-stage optimization problem is then formulated. In the first stage, a pilot scheduling algorithm is proposed to minimize the sum mean square error (MSE) of all channel estimates. Specifically, the minimum number of required pilots along with a feasible pilot allocation solution are first determined by applying the Dsatur algorithm, and adjustments based on the defined level of pilot contamination are then carried out for further improvement. Based on the pilot allocation result obtained in the first stage, the second stage aims at maximizing the sum spectral efficiency (SE) of the network by optimizing the beam vectors. Due to incomplete intercluster CSI and imperfect intracluster CSI, an explicit expression of each UE's achievable rate is unavailable. Hence, a lower bound on the achievable rate is derived based on Jensen's inequality, and an alternative robust transmission design algorithm along with its distributed realization are then proposed to maximize the derived tight lower bound. Simulation results show that compared with the existing algorithms, the system performance can be greatly improved by the proposed algorithms in terms of both sum MSE and sum SE.

Robust Transmission Design for Multicell D2D Underlaid Cellular Networks

This paper investigates the robust transmission design (RTD) of a multi-cell device-to-device (D2D) underlaid cellular network with imperfect channel state information (CSI). The bounded model is adopted to characterize the CSI impairment and the aim is to maximize the worst-case sum rate of the system. To protect cellular communications, it is assumed that the interference from all D2D transmitters to each base station (BS) is power-limited. It is first shown that the worst-case signal-to-interference-plus-noise ratio (SINR) of each D2D link can be obtained directly, while that of cellular links cannot be similarly found since the channel estimation error vectors of cellular links are coupled in the SINR expressions. To solve the nonconvex problem, the objective function of the original problem is replaced with its lower bound, and the resulted problem is decomposed into multiple semidefinite programming (SDP) subproblems which are convex and have computationally efficient solutions. An iterative RTD algorithm is then proposed to obtain a suboptimal solution. Simulation results show that D2D communication can significantly increase the performance of the conventional cellular systems while causing tolerable interference to cellular users. In addition, the proposed RTD algorithm outperforms the conventional non-robust transmission design greatly in terms of network spectral efficiency.

Joint Pilot Allocation and Robust Transmission Design for Ultra-Dense User-Centric TDD C-RAN With Imperfect CSI

This paper considers the unavailability of complete channel state information (CSI) in ultra-dense cloud radio access networks. The user-centric cluster is adopted to reduce the computational complexity, while the incomplete CSI is considered to reduce the heavy channel training overhead, where only large-scale inter-cluster CSI is available. Channel estimation for intra-cluster CSI is also considered, where we formulate a joint pilot allocation and user equipment (UE) selection problem to maximize the number of admitted UEs with fixed number of pilots. A novel pilot allocation algorithm is proposed by considering the multi-UE pilot interference. Then, we consider robust beam-vector optimization problem subject to UEs’ data rate requirements and fronthaul capacity constraints, where the channel estimation error and incomplete inter-cluster CSI are considered. The exact data rate is difficult to obtain in closed form, and instead we conservatively replace it with its lower-bound. The resulting problem is non-convex, combinatorial, and even infeasible. A practical algorithm, based on UE selection, successive convex approximation and semi-definite relaxation approach, is proposed to solve this problem with guaranteed convergence. We strictly prove that the semidefinite relaxation is tight with probability 1. Finally, extensive simulation results are presented to show the fast convergence of our proposed algorithm and demonstrate its superiority over the existing algorithms.

Distributed QoS Based Robust Transmission Design for MISO Wiretap Channel with Cooperative Jamming

A communication network that consists of a transmitter, a legitimate receiver, an eavesdropper and several friendly helpers is considered. Both the transmitter and the helpers are equipped with multiple antennas while the legitimate receiver or the eavesdropper has one antenna. The transmitter and the helpers have the channel state information to the legitimate receiver. The channels to the eavesdropper are partially known and modeled with uncertainty ellipsoids. The transmitter applies maximum ratio transmission to the legitimate receiver. The helpers generate interference to degrade the receiving performance of the eavesdropper. The transmit power of the helpers is optimized with the worst-case secrecy rate requirement as the Quality of Service constraint. Based on robust convex optimization, a centralized optimization problem is developed for the helpers to generate interference efficiently with minimum total transmit power. A distributed algorithm is developed which scales well with a large number of helpers.