The Internet of Nan-othings (IoNTs) have been extensively explored as potential communication technologies for in-body applications. The transmission of information from within the body to the external environment has become a popular and pressing issue that needs to be addressed. Neural communication has been proposed as a promising method, utilizing an action potential (AP), transient changes in membrane potential, as a fundamental unit for communication. Current research conceptualizes the membrane potential into two states: an excited state that generates an AP upon stimulation and a resting state absent of stimulation. However, this assumption overlooks the inherent oscillatory characteristics of membrane potential, which exhibit a discernible sensitivity to specific input frequencies. In this paper, we incorporate the oscillations characterized by the Izhikevich model into the channel model. Here, APs are generated when the inter-spike interval closely aligns with, or is a multiple of, the oscillatory period. Following this, we introduce an adaptive coding and modulation strategy. To represent “1”, a pair of pulses, separated by one period, are used to stimulate an AP. In contrast, to represent”0”, two consecutive pulses, distanced by half a period, are employed to inhibit the membrane potential. The transmission efficiency is evaluated by bit error rate (BER) and mutual information (MI). Numerical simulation results demonstrate that the proposed neural communication system is biologically plausible and exhibits higher resistance to interference. This research opens up possibilities for connecting IoNTs to external networks.

A 3-D arbitrary-elevation two-cylinder reference model is proposed for multiple-input-multiple-output (MIMO) air-to-air communications in unmanned aerial vehicle (UAV) channels. This model accounts for not only the Line-of-Sight (LoS) but also the single-bounced at the transmitter (SBT) and the single-bounced at the receiver (SBR), as well as the double-bounced (DB) rays. Therefore, it is endowed with a high adaptability to various UAV-to-UAV communication scenarios. From the reference model, a closed-form expression of the space-time correlation function (ST-CF) is derived. This expression is shown to be the generalizations of many existing correlation functions from the 2-D one-ring, the 3-D low-elevation one-cylinder, the 2-D two-ring, and the 3-D low-elevation two-cylinder model. Corresponding deterministic and stochastic simulation models are also developed in addition to the reference model. The well agreements between the channel capacities obtained from the simulation models and those from the derived ST-CF not only display the usefulness of the simulators but also confirm the correctness of the derivations. Based on the derived closed-form ST-CF, the effects of some model parameters on the capacity are evaluated in a computationally efficient manner.

In this paper, a three-dimensional (3D) geometry-based stochastic model (GBSM) empowered by reconfigurable intelligent surface (RIS) is presented for multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communication systems. Owing to the channel non-stationarity, spherical wavefront, and antenna configurations in RIS-empowered V2V channel, the geometry-based channel models suffer from high computational complexity, thereby leading to high hardware burden. To address this issue, a novel beam domain channel model (BDCM) is generated from the proposed geometry-based channel model through a beamforming operation based on discrete Fourier transform (DFT). To describe the non-stationarities of the V2V channels empowered by RIS, the channel model presented in this paper introduces real-time velocities and accelerations to capture the motion features of the communication terminals. The propagation characteristics including spatial cross-correlation functions (CCFs), temporal autocorrelation functions (ACFs), frequency correlation functions (FCFs), and channel capacities of the proposed communication system are derived and discussed. Some comparisons between the propagation characteristics of the proposed GBSM and those based on BDCM with respect to the different physical parameters of RIS and different environmental variables are investigated. Furthermore, numerical results indicate that the proposed channel model works well by changing the velocity parameters in different motion states.

Large-scale reconfigurable intelligent surface (RIS) can effectively enhance the performance of millimeter wave (mmWave) unmanned aerial vehicle (UAV) to ground communication link with obstructed line-of-sight (LoS) path by exploiting more reflecting units. However, the non-negligible array dimension of large-scale RIS and the mobile property of the terminals bring significant variations in propagation char-acteristics, making conventional channel models inapplicable. To address this issue, we propose a dynamic sub-array partition scheme to divide the large-scale RIS into sub-arrays by exploiting the Rayleigh distance criterion and the mobile property of the transceivers. Based on the proposed scheme, a novel non-stationary channel model for large-scale RIS auxiliary mmWave UAV-to-ground mobile networks is developed, which outperforms existing models with well balance between model complexity and accuracy. Numerical results are provided to verify our analysis.

In this paper, we consider the channel modeling of a heterogeneous vehicular integrated sensing and communication (ISAC) system, where a dual-functional multi-antenna base station (BS) intends to communicate with a multi-antenna vehicular receiver (MR) and sense the surrounding environments simultaneously. The time-varying complex channel impulse responses (CIRs) of the sensing and communication channels are derived, respectively, in which the sensing and communication channels are correlated with shared clusters. The proposed models show great generality for the capability in covering both monostatic and bistatic sensing scenarios, and as well for considering both static clusters/targets and mobile clusters/targets. Important channel statistical characteristics, including time-varying spatial cross-correlation function (CCF) and temporal auto-correlation function (ACF), are derived and analyzed. Numerically results are provided to show the propagation characteristics of the proposed ISAC channel model. Finally, the proposed model is validated via the agreement between theoretical and simulated as well as measurement results.

In recent years, with the improvement of mobile communication network performance, cell-free mMIMO with fully integrated and distributed processing has been widely studied, and wireless access networks have also become a widely studied topic in the academic community. This article analyzes the spectral efficiency of a new full spectrum cell-free wireless access network architecture with multiple EDUs and derives the performance upper and lower bounds of its traversal achievable rate. The full set formula and distributed processing can be used as two special cases; Secondly, the article further considers the distribution of users and large-scale fading models and studies the location distribution of RRUs. It is concluded that a uniform distribution of RRUs is beneficial for user traversal and speed improvement, and RRUs in multiple EDUs need to be as intertwined as possible, which is different from traditional multi-node clustering centralized collaborative processing; The article further proposes an modified genetic algorithms (GA), which simulates the performance of a new full spectrum cellfree wireless network with pilot pollution. The performance is compared with that of multi-RRU clustering group collaboration processing through Monte Carlo simulation.

In this paper, we propose a three-dimensional (3D) physics-based double reconfigurable intelligent surface (RIS) cooperatively assisted multiple-input multiple-output (MIMO) stochastic channel model for unmanned aerial vehicle (UAV)-to-ground communication scenarios. The double-RIS is distributed on the surface of buildings can assist the UAV transmitter to reflect its own signals to the ground receiver (GR), and simultaneously enhance the propagation by passive beamforming on the RISs. In the proposed channel model, we derive thepath power gainsfor different propagation links between the UAV and GR, thus enabling the proposed channel model to effectively characterize both large- and small-scale fading characteristics of realistic UAV-to-ground communication systems. Furthermore, we derive the critical propagation properties of the proposed channel model, including the spatial cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), and frequency correlation functions (FCFs), with respect to different RIS reflection phase configurations as well as different RIS orientation angles. Numerical simulation results demonstrate the propagation characteristics of the proposed double-RIS assisted UAV-to-ground channel model behave better than those of traditional channel models with single-RIS link or LoS link, thereby validating the necessity of introducing double-RIS into UAV-to-ground communication.

Reconfigurable intelligent surface (RIS)-assisted communications has been a hot topic due to its promising advantages for future wireless networks. Existing works on RIS-assisted channel modeling have mainly focused on far-field propagation condition with planar wavefront assumption. In essence, the far-field condition does not always hold because the RIS array dimension may be comparable to the terminal distance, especially in RIS-assisted mobile networks. To this end, we propose a hybrid far- and near-field stochastic channel model for characterizing a RIS-assisted vehicle-to-vehicle (V2V) propagation environment, which takes into account both far-field and near-field propagation conditions. To achieve the balance between the modeling accuracy and complexity for the investigation of the RIS-assisted V2V propagation characteristics, we develop a sub-array partitioning scheme to dynamically divide the entire RIS array into several smaller sub-arrays, which makes planar wavefront assumption applicable for the sub-arrays. Important channel statistical properties, including spatial cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), and frequency correlation functions (FCFs), are derived and investigated. Simulation results are provided to show the performance of the proposed sub-array partition based hybrid far- and near-field modeling solution for RIS-assisted V2V channels.

Reconfigurable intelligent surface (RIS) consisting of a large number of programmable near-passive units has been a hot topic in wireless communications due to its capability in providing smart radio environments to enhance the communication performance. However, the existing research are mainly based on simplistic channel models, which will, in principle, lead to inaccurate analysis of the system performance. In this paper, we propose a general three-dimensional (3D) wideband non-stationary end-to-end channel model for RIS assisted multiple-input multiple-output (MIMO) communications, which takes into account the physical properties of RIS, such as unit numbers, unit sizes, array orientations and array configurations. By modeling the RIS by a virtual cluster, we describe the end-to-end channel by a superposition of virtual line-of-sight (V-LoS), single-bounced non-LoS (SB-NLoS), and double-bounced NLoS (DB-NLoS) components. We also derive an equivalent cascaded channel model and show the equivalence between end-to-end and cascaded modeling of RIS channels. Then, a sub-optimal solution with low complexity is used to derive the RIS reflection phases. The impact of physical properties of RIS, such as unit numbers, unit sizes, array orientations, array configurations and array relative locations, on channel statistical characteristics has been investigated and analyzed, the results demonstrate that the proposed model is helpful for characterizing the RIS-assisted communication channels.

Unmanned aerial vehicle (UAV) communications exploiting millimeter wave (mmWave) can satisfy the increasing data rate demands for future wireless networks owing to the line-of-sight (LoS) dominated transmission and flexibility. In reality, the LoS link can be easily and severely blocked due to poor propagation environments such as tall buildings or trees. To this end, we introduce a reconfigurable intelligent surface (RIS), which passively reflects signals with programmable reflection coefficients, between the transceivers to enhance the communication quality. Specifically, in this paper we generalize a three-dimensional (3D) non-stationary wideband end-to-end channel model for RIS auxiliary UAV-to-ground mmWave multiple-input multiple-output (MIMO) communication systems. By modeling the RIS as a virtual cluster, we study thepower delivering capabilityof RIS as well as thefading characteristicof the proposed channel model. Important channel statistical properties are derived and thoroughly investigated, and the impact of RIS reflection phase configurations on these statistical properties is studied, which provides guidelines for the practical system design. The agreement between theoretical and simulated as well as measurement results validate the effectiveness of the proposed channel model.

For efficiently investigating the statistical properties of wideband multiple-input multiple-output (MIMO) channels for vehicle-to-vehicle (V2V) communication scenarios, we propose a novel computationally efficient solution to estimate the parameters of the proposed channel model for different propagation delays in this paper. To be specific, we first introduce a Unitary transformation method to estimate the propagation delay of the proposed channel model for the first tap in the preliminary stage before the mobile transmitter (MT) and mobile receiver (MR) move. Then, we estimate the real-time angular parameters based on the estimated delay and moving time/directions/velocities of the MT and MR. Furthermore, we estimate the expressions of the real-time complex channel impulse responses (CIRs), which can be used to characterize the physical properties of the proposed channel model, by substituting the estimates of the time-varying AoD and AoA and model parameters into the complex CIRs. Numerical results of the channel characteristics fit the theory results very well, which validate that the proposed channel model is practical for characterizing the beyond fifth-generation (B5G) V2V communication systems.

Considering mobile terminals with time-varying velocities and randomly moving clusters, a novel multi-mobility non-stationary wideband multiple-input multiple-output (MIMO) channel model for future intelligent vehicle-to-everything (V2X) communications is proposed. To describe the non-stationarity of multi-mobility V2X channels, the proposed model employs a time-varying acceleration model and a random walk process to describe the motion of the communication terminals and that of the scattering clusters, respectively. The evolution of the model parameters over time and the stochastic characteristics of the phase shift caused by the time-varying Doppler frequency are derived. The proposed model is sufficiently general and suitable for characterizing various V2X communication scenarios. Under two-dimensional (2D) non-isotropic scattering scenarios, the important channel statistical properties of the proposed model are derived and thoroughly investigated. The impact of the random walk process of the clusters and the velocity variations of the communication terminals on these statistical properties is studied. The simulation results verify that the proposed model is useful for characterizing V2X channels.