In urban settings, the highly complex communication environment leads to a frequent occurrence blockage in the link between ground users and unmanned aerial vehicle (UAV), which renders the quality of communication poor. To address this issue, an UAV edge computing system based on reconfigurable intelligent surface (RIS) is proposed in this paper. The goal of this system is to minimize energy consumption by considering various factors such as user transmission power, intelligent reflector phase shift matrix, UAV trajectory, computational resource allocation and the stability of task queues. By applying the Lyapunov optimization theory, the original non-convex problem is decomposed into a series of optimization-related sub-problems. Additionally, it is possible to obtain the closed solution to the original problem through Lagrange dual, Karush-Kuhn-Tucker (KKT) conditions, and mixed differential genetic evolution algorithm (MDGEA). As indicated by the simulation results, the proposed RIS-assisted UAV edge computing system is more effective in reducing energy consumption for the system than traditional UAV mobile edge computing on the basis of maintaining queue stability.

The probability of Line-of-Sight (LOS) propagation is crucial for channel modelling and small cell network evaluation. In this letter, by taking the layout of building structures into account, an analytical LOS probability model is proposed for typical indoor scenarios, which have rectangular rooms and corridors. The proposed model is validated through Monte Carlo simulations. Numerical results show that the proposed model estimates the network performance accurately and efficiently.

Three-dimensional (3D) multi-input-multi-output (MIMO) is one of the enabling technologies for next-generation mobile communication. As the elevation angle in the 3D MIMO channel model might vary against the height of the base station (BS) antenna, it should be considered within channel modeling. In this paper, the impact of antenna height on the channel characteristics of the 3D MIMO channel is investigated by using the intelligent ray launching algorithm (IRLA). Three typical street scenarios, i.e., the straight street, the forked road, and the crossroad, are selected as benchmarks. The joint and marginal probability density functions (PDFs) of both the elevation angle of departure (EAoD) and the elevation angle of arrival (EAoA) are obtained through simulations. Moreover, the elevation angle spread (AS) and the elevation delay spread (DS) under various antenna heights are jointly discussed. Simulation results show that the characteristics of the PDFs of EAoD will vary under different street scenarios. It is observed that in order to obtain the maximum or minimum value of the AS and the DS, the BS antenna should be deployed at half of the building height.

The performance of indoor small-cell networks (SCNs) is affected by the indoor environment, such as walls, blockages, etc. In this article, we investigate the effect of interior wall attenuation on the performance of an indoor SCN. Specifically, the spatial distribution of interior walls is modeled based on the random shape theory, and the indoor base stations (BSs) are distributed following a homogeneous Poisson point process. The channel model includes the path loss, Rayleigh fading, and wall attenuation. We analytically derive the downlink coverage probability under the strongest received signal user association strategy, which is validated by Monte Carlo simulations for three typical interior wall layouts (i.e., random layout, binary orientation layout, and Manhattan grid). The analytical results show that for a given density of interior walls and signal strength attenuation per wall, there is an optimal BS density that maximizes the coverage probability, and the optimal BS density increases as the wall attenuation increases.

As a multi-carrier modulation technique, a high peak-to-average power ratio (PAPR) is a common issue suffered by orthogonal frequency division multiplexing with index modulation (OFDM-IM) due to its system structure. High PAPR may cause signal distortion, which affects correct symbol transmission. This paper tries to inject dither signals to the inactive (idle) sub-carriers, which is a unique transmission structure of OFDM-IM, to reduce PAPR. Unlike the previous works, which utilize all idle sub-carriers, the proposed PAPR reduction scheme utilizes selected partial sub-carriers. This method performs well in terms of bit error rate (BER) performance and energy efficiency, which are obvious drawbacks of the previous PAPR reduction works due to the introduction of dither signals. In addition, in this paper, phase rotation factors are combined with the dither signals to compensate for the PAPR reduction performance degradation due to the insufficient use of partial idle sub-carriers. Moreover, an energy detection scheme is designed and proposed in this paper in order to distinguish the index of phase rotation factor used for transmission. It is shown by extensive simulation results that the proposed hybrid PAPR reduction scheme is able to implement an impressive PAPR reduction performance among existing dither signa-based schemes as well as classical distortion-less PAPR reduction schemes. In addition, the proposed method obtains better error performance and energy efficiency than that of the previous works. At the error probability ${10}^{-4}$, the proposed method can achieve around 5 dB gain compared to the conventional dither signal-based schemes

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) is emerging as a robust technology, especially valued in vehicular communication scenarios for its resilience. In such dynamic environments, reliable channel estimation becomes critical to maintain system performance due to the fast time-varying and double dispersion channel nature. Despite the harsh conditions, OFDM-IM enhances system performance by leveraging inactive sub-carriers to convey additional information. However, these idle sub-carriers complicate channel estimation compared to traditional OFDM systems. In response to these challenges, this paper introduces an enhanced channel estimation scheme tailored for the IEEE 802.11p standard, which supports cooperative intelligent transport systems (C-ITS). Our proposed method, the enhanced time-domain reliable test frequency-domain interpolation with index pilots (E-TRFI-IP), strategically places pilots and utilizes the positions of inactive sub-carriers to facilitate accurate detection and prevent performance degradation from inadequate channel tracking. Additionally, to further improve channel estimation performance, a comparison threshold methodology for reliable sub-carriers test is introduced by utilizing the structure of IM and joint interpolation method. Extensive simulation results demonstrate that E-TRFI-IP significantly surpasses existing channel estimation methods for both OFDM and OFDM-IM in terms of channel estimation performance. Notably, OFDM-IM systems employing the E-TRFI-IP estimation scheme also exhibit superior performance in bit error rate (BER) compared to those using conventional OFDM-IM and other channel estimation techniques.