6ET (Session 3) – Reconfigurable Intelligent Surface (RIS) based Communications
Thursday, 9 June 2022, 16:00-17:30, Room A306
Session Chair: Malte Schellmann (Huawei Technologies German Research Center, DE), Henk Wymeersch (Chalmers University of Technology, SE)
Arbitrary Beam Pattern Approximation via RISs with Measured Element Responses
Moustafa Rahal (CEA-Leti, France); Benoit Denis (CEA-Leti Minatec, France); Kamran Keykhosravi and Musa Furkan Keskin (Chalmers University of Technology, Sweden); Bernard Uguen (University of Rennes I, France); George C. Alexandropoulos (University of Athens, Greece); Henk Wymeersch (Chalmers University of Technology, Sweden)
Smart radio environments (SREs) are seen as a key rising concept of next generation wireless networks, where propagation channels between transmitters and receivers are purposely controlled. One promising approach to achieve such channel flexibility relies on semi-passive reflective Reconfigurable intelligent surfaces (RISs), which can shape the bouncing multi-path signals for enhancing communication quality of service, making localization feasible in adverse operating conditions, or reducing unwanted electromagnetic emissions. This paper introduces a generic framework that aims at optimizing the end-to-end precoder controlled by RISs so that arbitrary beampatterns can be generated, given a predefined lookup table ofRIS element-wise complex reflection coefficients. This method is validated and illustrated for different targeted beam patterns in both the far-field and the near-field regimes while considering the prior characterization of real-life RIS hardware prototypes. These results show how, and to which extent, RIS configuration optimization can approximate the desired beams under realistic hardware limitations and low-complexity implementation practicability, or conversely, which RIS elements’ lookup tables would be more suitable. The latter can provide useful guidelines for future RIS hardware designs.
Cyclic-Prefixed Single-Carrier Transmission with Reconfigurable Intelligent Surfaces
Qiang Li (Jinan University, China); Miaowen Wen (South China University of Technology, China); Ertugrul Basar (Koc University, Turkey); George C. Alexandropoulos (University of Athens, Greece); Kyeong Jin Kim (Mitsubishi Electric Research Laboratories (MERL), USA); H. Vincent Poor (Princeton University, USA)
In this paper, a cyclic-prefixed single-carrier (CPSC) transmission scheme with phase shift keying (PSK) signaling is presented for broadband wireless communications systems empowered by a reconfigurable intelligent surface (RIS).
In the proposed CPSC-RIS, the RIS is configured according to the transmitted PSK symbols such that different cyclically delayed versions of the incident signal are created by the RIS to achieve cyclic delay diversity. A practical and efficient channel estimator is developed for CPSC-RIS and the mean square error of the channel estimation is expressed in closed-form. We analyze the bit error rate (BER) performance of CPSC-RIS over frequency-selective Nakagami-m fading channels. An upper bound on the BER is derived by assuming the maximum-likelihood detection. Our simulation results in terms of BER corroborate the performance analysis and the superiority of CPSC-RIS over the conventional CPSC without an RIS and orthogonal frequency division multiplexing with an RIS.
Deep Reinforcement Learning for Practical Phase Shift Optimization in RIS-Assisted Networks over Short Packet Communications
Ramin Hashemi, Samad Ali, Ehsan MoeenTaghavi, Nurul Huda Mahmood and Matti Latva-aho (University of Oulu, Finland)
We study the practical phase shift design in a non-ideal reconfigurable intelligent surface (RIS)-aided ultra-reliable and low-latency communication (URLLC) system under finite blocklength (FBL) regime by leveraging a novel deep reinforcement learning (DRL) algorithm named as twin-delayed deep deterministic policy gradient (TD3). First, assuming industrial automation system with multiple actuators, the signal-to-interference-plus-noise ratio (SINR) and achievable rate in FBL regime are identified for each actuator in terms of the phase shift configuration matrix at the RIS. The channel state information (CSI) variations due to feedback delay is also considered that results in channel coefficients’ obsolescence. Then, the problem framework is proposed where the objective is to maximize the total achievable FBL rate in all ACs, subject to the practical phase shift constraint at the RIS elements. Since the problem is intractable to solve using conventional optimization methods, we resort to employing an actor-critic policy gradient DRL algorithm based on TD3, which relies on interacting RIS with FA environment by taking actions which are the phase shifts at the RIS elements, to maximize the expected observed reward, which is defined as the total FBL rate. The numerical results show that optimizing the practical phase shifts in the RIS via the proposed TD3 method is highly beneficial to improve the network total FBL rate in comparison with typical DRL methods.
Capacity Boosting by IRS Deployment for Industrial IoT Communication in Cm- and mm-Wave Bands
Malte Schellmann (Huawei Technologies German Research Center, Germany)
This paper investigates a deployment of intelligent reflecting surfaces (IRS) in a scenario of industrial IoT communication, characterized by data transmission with high reliability under low latency constraints. In this scenario, channel diversity from independent radio links is of supreme importance, which can be enriched by IRS assisted links. By first dimensioning the size of the IRS to fulfill the far-field conditions for the carrier frequency used, the path-loss of the IRS assisted links is modeled based on the 3GPP path-loss models for indoor factories. An analysis of the achievable effective capacity is carried out for selected carrier frequencies in the cm- and mm-wave bands, where it is shown that
the IRS deployment can yield significant capacity gains compared to the baseline without IRS.
A NOMA-Enabled Hybrid RIS-UAV-Aided Full-Duplex Communication System
Sandeep Kumar Singh (National Sun Yat-sen University, Kaohsiung, Taiwan); Kamal Agrawal (Indian Institute of Technology Delhi, India); Keshav Singh (National Sun Yat-sen University, Kaohsiung, Taiwan); Chih-Peng Li (National Sun Yat-sen University, Taiwan); Zhiguo Ding (University of Manchester, United Kingdom (Great Britain))
In this paper, we investigate non-orthogonal multiple access (NOMA) enabled multiuser wireless communication network which uses a hybrid aerial full-duplex (FD) transmission consisting of a reconfigurable intelligent surface (RIS) mounted over an FD unmanned aerial vehicle (UAV) relay to assist the information transfer from the base station to all GUs simultaneously. We consider three different transmission modes: 1) FD-UAV-aided transmission, 2) RIS-aided transmission, and 3) joint RIS-FD-UAV transmission. Firstly, the joint passive beamforming (i.e., passive phase shift matrix) and position optimization problem is formulated to maximize the considered network’s achievable sum rate. Due to the coupling of optimization variables, the optimization problem becomes non-convex. Therefore, we utilize the block coordinate descent method to split the optimization problem into two sub-problems. We then use the Riemannian conjugate gradient (RCG) method and propose an algorithm to determine the optimal passive beamforming. Next, an iterative algorithm is proposed to obtain the optimal RIS/UAV coordinates. Finally, using both RCG and iterative algorithms, we jointly optimize the passive beamforming of RIS and the position of RIS/UAV. The effectiveness of the proposed algorithms is verified through extensive computer simulations.