The optimization problem of the number of mirrors under energy efficiency (EE) maximization for vehicular visible light communication (VVLC) via mirror array-based intelligent reflecting surface (IRS) is investigated. Under considering that the formulated optimization problem is subject to the real and non-negative of the transmitted signal, the maximum power consumption satisfied luminous ability and eye safety, the minimum achievable rate, and the required bit error ratio (BER), EE is proved to be a unimodal function of the number of mirrors. Then, the binary search-conditional iteration (BSCI) algorithm is proposed for quickly finding the optimal number of mirrors with maximum EE. Numerical results demonstrate that fewer mirrors can obtain the maximum EE, and the computational complexity of the BSCI algorithm is reduced by ${10}^5$ orders of magnitude, compared with the Bubble Sort method.

In the visible light communication (VLC) for parallel vehicles, the light emitted by the headlamps cannot reach the photodiode (PD), which is the receiver installed on another vehicle. To solve this problem, the mirror array-based intelligent reflecting surface- (IRS-) aided VLC system is designed for parallel vehicles, and the system performance with different number of mirrors and transmission distance is analyzed. The maximum distance between adjacent IRSs is calculated via the exhaustive method, and the nearest neighbor iterative search (NNIS) algorithm is proposed for IRS node selection. Numerical results show that the SNR increases with the number of mirrors increasing. If the number of mirrors is in the IRS, the maximum distance between adjacent IRSs is 37 meters. When the interval between adjacent IRSs is 32 meters, the required BER can be satisfied with merely three IRSs working together according to the NNIS algorithm.

In this paper, focusing on the application of wireless sensor networks (WSNs) in smart agriculture, unmanned aerial vehicle (UAV)-mounted intelligent reflecting surface (IRS) is used to tackle the issue of Line-of-Sight (LoS) channel between a sensor node (SN) and the fusion center being blocked by obstacles. In particular, the optimal number of reflecting elements is studied under the condition that the spectral efficiency (SE) and energy efficiency (EE) are balanced when the UAV hovers to collect sensors’ data. Firstly, the relationship between SE and EE versus the number of reflecting elements for a single SN is analyzed, and then the Conditional Judgment-Binary Search algorithm (CJ-BS) is proposed to seek the optimum number of reflecting elements. Secondly, on this basis and considering that multiple sensor nodes (SNs) send data to the UAV by adopting time-division multiple access, this paper further analyzes the optimum number of reflecting elements when different SNs use the same or different numbers of reflecting elements (SNRE or DNRE scheme) at different time slots. Thirdly, to find the optimal one in these two schemes we analyze the EE and compare them. Under the above cases, we prove that the EE is a unimodal function of the number of reflecting elements. Simulation results show that with the increase of the number of reflecting elements and the hovering altitude, the relative EE improvement of SNRE versus DNRE first increases and then decreases. Furthermore, considering that the SNRE scheme’s complexity is lower, it is a better choice for practical implementation.

Uncrewedaerial vehicle (UAV)-carried intelligent reflecting surfaces (U-IRSs) can be utilized to assist blocked communications between sensor nodes (SNs) and the fusion center in wireless sensor networks (WSNs). This article investigates a U-IRS-assisted data collection system in WSNs that employs the hover priority scheme. Given the energy constraints of UAV, the combined energy consumption from UAV moving/hovering and IRS reflecting elements configuration circuitry poses significant challenges to improving the system’s energy efficiency (EE). To address this challenge, we formulate a multiobjective optimization problem under the constraints of UAV and SN power budgets to make a tradeoff between EE and spectral efficiency. Due to the nonconvexity of the formulated problem, we divide the main problem into three subproblems: user association, the number of reflecting elements, and UAV trajectory optimization. An alternating optimization algorithm integrating the genetic algorithm, the CJ-BS-based cyclic iteration algorithm, Dinkelbach’s algorithm, and the successive convex approximation method is proposed to solve these subproblems. Simulation results demonstrate that the proposed solution outperforms the UAV hovering directly above each SN scheme.

Polar codes have garnered significant attention since they were proposed due to their capacity-achieving properties and their low-complexity decoding process, and they were selected as the coding scheme for the control channel in 5G mobile communication technology. A successive cancellation list (SCL) decoder, aided by a cyclic redundancy check (CRC), performs the competitive error correcting performance for polar codes compared to other sophisticated codes. The SCL-Flip decoding algorithm is proposed to enhance the error correction performance of the SCL. However, the SCL-Flip is hampered by a high decoding complexity due to the necessary selection and sorting process of path metrics (PMs). Additionally, it requires a large number of iterations to achieve a good error correction performance. In this paper, we propose the error segment bit-flip (ES-SCL-Flip) decoding algorithm, a simplified bit-flip approach for the SCL decoder based on analyzing the distributions of the first error bit. Firstly, we construct an index set with a high probability of the first erroneous bit. Second, a bit-flip criterion is introduced to prevent the costly operation of the PM selection and sorting without compromising the error correction performance. Finally, a search strategy is employed that utilizes segmented error indication to target and rectify the initial error segment sequentially. The simulation results demonstrate that the ES-SCL-Flip decoder provides an improved error correction performance with only a minimal increase in decoding complexity compared to the conventional CRC-aided SCL decoder. This algorithm attains a commendable equilibrium between the error correction performance and decoding complexity.