The combination of rate splitting multiple access (RSMA) and integrated sensing and communication (ISAC) has recently played a constructive role in various emerging applications associated with sixth-generation networks. However, in complex urban environments, the network performance may be severely restricted by transmission blockages. With the help of intelligent reflecting surfaces (IRS), this paper leverages a virtual line-of-sight link to guarantee the qualityof-service (QoS). First, a three-dimensional (3D) geometry-based stochastic channel model (GBSM) is developed to characterize the IRS-empowered ISAC networks with RSMA. Based on the proposed channel model, we formulate an energy efficiency (EE) maximization problem, subject to transceiver beamforming constraints, IRS phase shift constraints, and QoS constraints. The impact of some important system parameters on the EE is numerically investigated using the proximal policy optimization (PPO) method. One key observation of our results is that the system EE degrades significantly at higher frequencies even for double-Rayleigh fading channels, which may make it difficult for the subsequent sensing link establishment.

Dynamic gesture recognition using millimeter-wave radar has a broad application prospect in the industrial Internet of Things (IoT) field. However, the existing methods in the random dynamic interference environment, such as throwing objects and waving and easily cause wrong recognition. This article proposes a dynamic gesture recognition method based on a convolutional neural network (CNN)-Transformer network to solve this problem. First, we reshape the original echoes acquired by the frequency-modulated continuous-wave (FMCW) millimeter-wave radar into 3-D data blocks in terms of Chirps $\times $ Samples $\times $ Frames. And we employ the mean elimination method to eliminate the static interference. Second, we extract dynamic gestures’ distance and Doppler information with the 2-D fast Fourier transform and obtain the range-time map and Doppler-time maps. And we employ the coherent accumulation method to improve the signal-to-noise ratio (SNR). Third, we construct the CNN-Transformer network model for dynamic gesture recognition. The CNN is used to extract the local features of gestures, and multiple Transformer modules are stacked to extract deeper effective features. Finally, we build a data set for gesture recognition, including six kinds of dynamic gestures and two kinds of random interference. The experimental results show that the proposed method has a gesture recognition accuracy of more than 98% and 96% in the noninterference scene and the random dynamic interference scene, respectively, which are superior to the conventional recognition methods.

This paper investigates cellular base station (BS)-enabled wireless systems featuring downlink integrated sensing and communications, a critical enabler for the low-altitude economy. To serve a sensing target and multiple communication users simultaneously, a hybrid active-passive reconfigurable intelligent surface (RIS) is employed. A key challenge arises from the inherent downtilt of cellular BS antennas, which often results in high-altitude targets (e.g., unmanned aerial vehicles) being sensed predominantly via antenna sidelobes, thereby substantially constraining sensing performance. To jointly enhance both communication and sensing capabilities, we formulate a radar signal-to-noise ratio maximization problem. This formulation involves the co-optimization of beamforming vectors and RIS phase shifts, subject to constraints on transmit power, hybrid RIS power consumption, discrete RIS phase shifts, and communication user quality of service requirements. Addressing the non-convexity and NP-hardness of this problem, we propose a novel mixture-of-experts (MoE)-based proximal policy optimization (PPO) approach. Specifically, the MoE architecture is integrated within PPO to alleviate the learning complexity and mitigate gradient interference inherent in a single policy network. This is achieved by employing expert networks that specialize in distinct regions of the state space, orchestrated by a gating network that dynamically weights their contributions, thereby promoting accelerated convergence and enhanced optimization efficiency. Numerical results demonstrate that even for a target flying above the cellular BS, the deployment of a hybrid RIS with as few as 4 active elements, each providing an amplitude amplification of 2, yields a remarkable 18.5% improvement in sensing SNR, which translates to substantially enhanced sensing accuracy and reliability for low-altitude targets.

In this letter, we study user grouping and beamforming for high altitude platform (HAP) massive multiple-input multiple-output (MIMO) systems. We first exploit the fact that the signal power mainly concentrates on statistical-eigenmode (SE), and we then use it to perform user grouping and design the outer beamformer. The user grouping is realized based on the average chordal distance between the SEs instead of the chordal distance between the covariance eigenspaces of the users in the same group. In this case, the complexity of a singular value decomposition is avoided. The outer beamformer is designed using reduced-dimensional SEs of the users, and the computational complexity is lower than in the case where the statistical correlation matrix is used. Numerical results demonstrate the performance enhancement of the proposed beamforming scheme in HAP massive MIMO systems compared to the existing schemes based on channel correlation matrix.

The measurement results in land mobile satellite (LMS) communication scenario have shown that the propagation characteristic of LMS channel is a non-stationary process. In this paper, a non-stationary three-dimensional (3-D) wideband geometry-based stochastic model (GBSM) and the corresponding simulation model are proposed for high-altitude platform (HAP) multiple-input multiple-output (MIMO) communication system. The proposed GBSM uses two-dimensional (2-D) one-ring and 3-D multi-cylinders to model moving scatterers and near and far stationary scatterers, respectively. In the proposed GBSM, we assume that the multipath components (MPCs) scattering from the far stationary scatterers could appear again after their disappearance, and a two-state continuous-time Markov process is used to model the dynamic properties of MPCs such as MPCs appearance and disappearance, and the closed-form expressions of the survival probabilities of MPCs are derived. In the proposed GBSM, the long distance and small-scale time-variant parameters are also used to investigate the non-stationarities of HAP-MIMO channel. Using the survival probabilities of MPCs, the statistical properties of the proposed 3-D GBSM are derived. The numerical results demonstrate that the proposed 3-D GBSM is more practical to characterize the HAP-MIMO channel.

In this paper, we use directional antenna arrays instead of large-scale antenna arrays to combat the severe propagation path loss, and propose a novel beam channel model for millimeter-wave (mmWave) unmanned aerial vehicle (UAV) multiple-input multiple-output (MIMO) communication systems. The sparsity of mmWave channel and the directivity gain of mmWave antenna arrays are considered in the proposed model, and the antenna directivity gain is affected by the beamwidth, i.e., the narrower the beam, the higher the antenna directivity gain. Also, the beamwidth affects the number of active clusters, i.e., the wider the beam, the more the active clusters. Based on the proposed beam channel model, the influence of antenna directivity gain on the channel statistical characteristics including space-time correlation, frequency correlation function, and achievable rate is investigated. It is found that the directional antenna arrays can reduce Doppler spread caused by the movement of UAV and receiver and the mmWave communication systems using directional antenna arrays with high directivity gains can achieve an equivalent performance gain to that of the mmWave communication systems using omni-directional large-scale antenna arrays. Furthermore, considering the correlation between transmit and receive antenna elements, we obtain a closed-form expression of the tight upper bound of achievable rate, which is validated by using previously reported analytical upper bound and the simulation results.