Matrix graph signals, which are associated with two factor graphs, are ubiquitous in daily life, such as time-varying physical signals in sensor networks and rating matrices in recommendation systems. In practice, due to the row-wise and column-wise smoothness, they are modeled as bandlimited (BL) graph signals on the product of two factor graphs. In this paper, we propose a fast sampling method for BL product graph signals by minimizing the reconstruction mean squared error (MSE). First, we formulate the MSE-based sampling objective for BL signals on a product graph. Next, we simplify the greedy subproblem using matrix inversion approximation, which involves straightforward computations between the defined joint low-pass impulse responses (JLIRs). To eliminate the huge computation and storage complexity, we propose a strategy to directly compute the greedy evaluation score based on low-dimensional LIRs on two factor graphs, leveraging the property of Kronecker product. Employing this strategy, we also extend existing popular LIR-based methods to sample signals from single graphs to product graphs with low complexity. Extensive experiments on synthetic and real-world product graph signals demonstrate that our proposed method maintains superior MSE performance compared to other extended graph sampling schemes.

ABSTRACT This paper investigates a buffer‐aided cooperative non‐orthogonal multiple access scheme for simultaneous wireless information and power transfer systems, where the near users are equipped with data and energy buffers. To improve the overall energy efficiency, the transmission mode of the considered system adaptively chooses the base station or near‐user transmission mode. Given the target quality of service and limited resources, the long‐term power consumption minimization is formulated by a mixed integer non‐linear programming problem, where the model selection, user scheduling, and power consumption are jointly optimized. To efficiently tackle such a challenging problem, we transform the original problem into an instantaneous non‐convex problem by employing the Lyapunov optimization framework. Then, using the successive convex approximation algorithms, we approximate the instantaneous non‐convex problem as a linear programming problem, where the Karush–Kuhn–Tucker solution of the power allocation can be obtained. The optimality and complexity of the proposed scheme are theoretically analyzed. The simulation results show that the proposed scheme can achieve a near‐optimal performance and significantly improves the energy efficiency compared with the conventional transmission schemes.

Integrated sensing and communication (ISAC) is emerging as a key technology and research focus for future vehicular communication networks (VCN). It achieves efficient reuse of wireless infrastructure and spectrum resources through the collaborative design of sensing and communication functionalities. However, this integration leads to inevitable mutual interference, and the complexity of channel conditions further complicates the coordination of these functionalities. This paper primarily focuses on the joint sensing-communication performance analysis of ISAC-enabled VCN. Specifically, we model the spatial distribution of roads using a Poisson line process, while the locations of vehicles and roadside units (RSUs) are represented by two one-dimensional Poisson point processes. We characterize the dynamic interference distribution caused by RSUs during the sensing and communication phases and calculate the probability of successful perception (PSP) for a typical pair. Furthermore, for this typical pair, we meticulously derive the communication coverage probability based on the derived PSP for such a pair. To provide a detailed analysis of the interaction between communication and sensing functionalities, we evaluate their trade-off relationship and derive the joint probability of ISAC coverage. Moreover, we perform comprehensive simulations to verify the theoretical results. Additionally, the numerical results demonstrate how different parameters impact the network performance, providing guidance for network deployment and resource allocation under certain performance requirements.

Ambient backscatter which utiliees the ambient radio‐frequency signals to enable transmissions between battery‐less devices has attracted considerable attention in academia and industry. This study addresses the questions of full‐duplex (FD) and self‐interference cancellation (SIC) for ambient backscatter which adopts dual‐antenna structure to achieve persistent information transmission and energy harvesting. The authors construct the physical‐layer network coding (PNC) mapping principle of on–off keying in the dual‐antenna structure and propose the PNC‐based FD algorithm to eliminate the self‐interference in the information domain. Furthermore, the bit‐error‐ratio and throughput performances are analysed under conventional half‐duplex mode and the proposed FD mode, respectively. In order to facilitate system complexity and reduce power consumption, they design a hardware prototype to achieve SIC which consists of low‐power passive analogue components. Numerical results are provided to confirm the theoretical studies. Circuit simulations demonstrate that the circuit is commendably consistent with the design concept.