Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userRIS-Assisted MISO Communication: Optimal Beamformers and Performance Analysis
66
0
0.0
(
0
)
Added by
Neel Kanth Kundu
Publication date
2020
fields
Electronic Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We study a multiple-input single-output (MISO) communication system assisted by a reconfigurable intelligent surface (RIS). A base station (BS) having multiple antennas is assumed to be communicating to a single-antenna user equipment (UE), with the help of a RIS. We assume that the system operates in an environment with line-of-sight (LoS) between the BS and RIS, whereas the RIS-UE link experiences Rayleigh fading. We present a closed form expression for the optimal active and passive beamforming vectors at the BS and RIS respectively. Then, by characterizing the statistical properties of the received SNR at the UE, we apply them to derive analytical approximations for different system performance measures, including the outage probability, average achievable rate and average symbol error probability (SEP). Our results, in general, demonstrate that the gain due to RIS can be substantial, and can be significantly greater than the gains reaped by using multiple BS antennas.
rate research
Read More
Reconfigurable intelligent surfaces (RISs) have been deemed as one of potential components of future wireless communication systems because they can adaptively manipulate the wireless propagation environment with low-cost passive devices. However, due to double fading effect, the passive RIS can offer sufficient signal strength only when receivers are nearby and located at the same side as the incident signals. Moreover, RIS cannot provide service coverage for the users at the back side of it. In this paper we introduce a novel reflection and relay dual-functional RIS architecture, which can simultaneously realize passive reflection and active relay functionalities to enhance the coverage. The problem of joint transmit beamforming and dual-functional RIS design is investigated to maximize the achievable sum-rate of a multiuser multiple-input single-output (MU-MISO) system. Based on fractional programming (FP) theory and majorization-minimization (MM) technique, we propose an efficient iterative transmit beamforming and RIS design algorithm. Simulation results demonstrate the superiority of the introduced dual-functional RIS architecture and the effectiveness of the proposed algorithm.
In this work, we propose a beam training codebook for Reconfigurable Intelligent Surface (RIS) assisted mmWave uplink communication. Beam training procedure is important to establish a reliable link between user node and Access point (AP). A codebook based training procedure reduces the search time to obtain best possible phase shift by RIS controller to align incident beam at RIS in the direction of receiving node. We consider a semi passive RIS to assist RIS controller with a feedback of minimum overhead. It is shown that the procedure detects a mobile node with high probability in a short interval of time. Further we use the same codebook at user node to know the desired direction of communication via RIS.
Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and lowpower configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted multi-user wireless communication system and present a joint channel estimation and signal recovery algorithm in this paper. Specifically, we propose a bidirectional approximate message passing algorithm that applies the Taylor series expansion and Gaussian approximation to simplify the sum-product algorithm in the formulated problem. Our simulation results show that the proposed algorithm shows the superiority over a state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed algorithms.
In practice, residual transceiver hardware impairments inevitably lead to distortion noise which causes the performance loss. In this paper, 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.
Reconfigurable intelligent surfaces (RISs) are considered as potential technologies for the upcoming sixth-generation (6G) wireless communication system. Various benefits brought by deploying one or multiple RISs include increased spectrum and energy efficiency, enhanced connectivity, extended communication coverage, reduced complexity at transceivers, and even improved localization accuracy. However, to unleash their full potential, fundamentals related to RISs, ranging from physical-layer (PHY) modelling to RIS phase control, need to be addressed thoroughly. In this paper, we provide an overview of some timely research problems related to the RIS technology, i.e., PHY modelling (including also physics), channel estimation, potential RIS architectures, and RIS phase control (via both model-based and data-driven approaches), along with recent numerical results. We envision that more efforts will be devoted towards intelligent wireless environments, enabled by RISs.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
