Abstract
Recently, the reconfigurable intelligent surface (RIS)-aided communication system has emerged as a promising candidate for future millimeter-wave wireless communications. Due to the short wavelength of millimeter wave, the antennas on the base station (BS) and the elements on the RIS can be densely packed. It usually causes the BS and RIS to be blocked by rain, snow, or dust, which will change the channel’s characteristics and decrease the performance of communication system. In order to solve this problem, we propose an iterative compressed sense based algorithm for joint estimating the blockage coefficients of RIS and BS. Then, for the complete blockage scenario, we propose a low complexity algorithm for estimating the blockage coefficients. Our simulation results demonstrate the superior performance of the proposed algorithm to existing ones.
Highlights
As a new technology for generation wireless networks, reconfigurable intelligent surface (RIS) integrates a large number of passive reflection units with low hardware cost and energy consumption for intelligent transmission, which can improve the spectrum efficiency and the coverage capability of the communication system [1]
The system parameters are set as follows: We consider that the RIS is equipped with 100 elements and the base station (BS) is equipped with 10 antennas; The number of the BS-RIS channel path is 1, and the number of the RIS-user channel path is from the user to φlR2U are randomly chosen from [−π/2, π/2]; We set the probability of blocked RIS and blocked BS as 0.2
The curve normalized mean-squared error (NMSE) of b with [9] denotes the NMSE of BS blockage coefficient b estimated by the traditional diagnosis method for BS proposed in [9], which ignores the effect of RIS blockage
Summary
As a new technology for generation wireless networks, RIS integrates a large number of passive reflection units with low hardware cost and energy consumption for intelligent transmission, which can improve the spectrum efficiency and the coverage capability of the communication system [1]. Since the passive RIS elements cannot perform signal processing, channel estimation for RIS-aided systems is challenging. The diagnosis algorithm proposed in [11] is suitable for the scenario where the RIS is blocked but the BS is free. Input: Received signal y; The cascaded channel information GBRdiag(gRU); The phase coefficients of RIS θ (t); The number of iterations Niter. We defined that b ∈ CN×1 denotes the blockage coefficient vector of BS, whose n-th element bn is the random complex random variable with a modulus less than 1. We propose a compressed-based algorithm for joint estimation of the RIS blockage coefficients and the BS blockage coefficients according to the received signal y shown in (7)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
