Beixiong Zheng

Rotatable antenna (RA) is a promising technology that can exploit new design dimensions by optimizing the three-dimensional (3D) boresight directions of directional antennas. In this letter, we investigate an RA-enhanced cell-free system for downlink transmission, where multiple RA-equipped access points (APs) cooperatively serve multiple single-antenna users over the same time-frequency resource. Specifically, we aim to maximize the sum rate of all users by jointly optimizing the AP-user associations and the RA boresight directions. Accordingly, we propose a two-stage strategy to solve the AP-user association problem, and then employ fractional programming (FP) and successive convex approximation (SCA) techniques to optimize the RA boresight directions. Numerical results demonstrate that the proposed RA-enhanced cell-free system significantly outperforms various benchmark schemes.

In the evolving landscape of mobile edge computing (MEC), enhancing communication reliability and computation efficiency to support increasingly stringent low-latency services remains a fundamental challenge. Rotatable antenna (RA) is a promising technology that introduces new spatial degrees-of-freedom (DoFs) to tackle this challenge. In this letter, we investigate an RA-enabled MEC system where antenna bore-sight directions can be independently adjusted to proactively improve wireless channel conditions for latency-critical users. We aim to minimize the maximum computation latency by jointly optimizing the MEC server’s computing resource allocation, receive beamforming, and the deflection angles of all RAs. To address the resulting non-convex problem, we develop an efficient alternating optimization (AO) framework. Specifically, the optimal edge computing resource allocation is derived based on the Karush–Kuhn–Tucker (KKT) conditions. Given the computing resources, the receive beamforming is optimized using semidefinite relaxation (SDR) combined with a bisection search. Furthermore, the RA deflection angles are optimized via fractional programming (FP) and successive convex approximation (SCA). Simulation results verify that the proposed RA-enabled MEC scheme significantly reduces the maximum computation latency compared with conventional benchmark methods.

The integration of fluid antenna systems (FAS) into integrated sensing and communication (ISAC) networks offers promising reconfigurability for air–ground scenarios in low-altitude economic (LAE) environments. This paper investigates a monostatic FAS-aided ISAC architecture comprising a two-dimensional (2D) FAS-based transmit array and a fixed-position receive array, aiming to enhance the joint performance across multiple ground user equipments (GUEs) and one aerial user equipment (AUE). A joint optimization problem is formulated to maximize a weighted utility metric integrating the communication signal-to-interference-plus-noise ratio (SINR) of the AUE and the sensing signal-to-clutter-plus-noise ratio (SCNR), subject to the transmit power constraint, inter-antenna spacing constraint, deployment geometry, and the minimum SINR requirement of GUEs. The resulting problem involves coupled spatial variables and fractional structures, which are addressed via an alternating optimization (AO) framework. Specifically, the receive beamformer is derived in closed form, the transmit beamformer is optimized via fractional programming (FP) and successive convex approximation (SCA), and the antenna positions are iteratively refined on a per-element basis through second-order Taylor expansion to construct convex surrogate upper bounds. Numerical results verify that the proposed FAS-enhanced ISAC system substantially outperforms benchmark schemes.

Integrated sensing and communication (ISAC) is regarded as a promising solution for the development of the emerging low-altitude economy (LAE). Given the necessity of accurate and realistic wireless channel models for ISAC evaluation and optimization, this paper proposes an LAE-oriented ISAC channel modeling framework. By incorporating the target unmanned aerial vehicle (UAV) scattering response, we decouple the ISAC channel into target and background channels. For the target channel, the model is formulated as a cascade of the transmitting base station (BS)-target link, the target-sensing BS link, and the scattering response from the target UAV. For the background channel, a novel parameter is introduced to separate the influence of the target UAV. Furthermore, key statistical properties, including the space-time-frequency correlation function, coherence distance, Doppler power spectral density, root mean square delay spread, and stationarity interval, are derived and analyzed. The accuracy of the proposed channel model is verified by the close agreement between simulated statistics properties and measured data, and the effectiveness of the cascaded method is validated by the close agreement between the concatenation output and simulation results.

Cellular-connected unmanned aerial vehicles (UAVs) are expected to play an increasingly important role in future wireless networks. To facilitate the reliable navigation for cellular-connected UAVs, channel knowledge map (CKM) is considered a promising approach capable of tackling the non-negligible co-channel interference resulting from the high line-of-sight (LoS) probability of air-ground (AG) channels. Nevertheless, due to measurement constraints and the aging of information, CKM is usually incomplete and needs to be regularly updated to capture the dynamic nature of complex environments. In this paper, we propose a novel trajectory design strategy in which UAV navigation and CKM completion are incorporated into a common framework, enabling mutual benefits for both tasks. Specifically, a cellular-connected UAV deployed in an urban environment measures the radio information during its flight and completes the CKM with Kriging interpolation. Based on the method of grid discretization and spherical approximation, a mixed-integer multi-objective optimization problem is formulated. The problem falls into the category of combinatorial mathematics and is essentially equivalent to determining an optimum sequence of grid points to traverse. Through proper mathematical manipulation, the problem is reformulated as variants of two classic models in graph theory, namely the shortest-path problem (SPP) and the traveling salesman problem (TSP). Two navigation strategies based on the two different models are proposed and thoroughly compared based on numerical results to provide implementable methods for engineering practice and reveal the trade-offs between UAV navigation and CKM completion. Simulation results reveal that the proposed navigation strategies can quickly expand the Pareto boundary of the problem and approach the performance of fully-known CKM.

Prior studies on mixed near-field and far-field communications have focused exclusively on single-cell scenarios, where both near-field and far-field users are served by the same base station (BS), leading to intra-cell mixed-field interference. In this paper, we consider a more general and practical multi-cell mixed-field scenario consisting of multiple cells, each serving multiple users, thus resulting in more complex inter-cell mixed-field interference. To address this new challenge, we propose leveraging rotatable antenna (RA) technology to enhance multi-cell mixed-field communication performance by exploiting the additional spatial degree-of-freedom (DoF) introduced by RA rotation to mitigate interference in an efficient way. Specifically, we study an RA-enabled multi-cell mixed-field communication system in which each BS is equipped with an RA array to serve its associated users. We formulate a network-wide sum-rate maximization problem that jointly optimizes the transmit beamforming and the rotation angles of the RA arrays, subject to per-BS power constraints and admissible array rotation limits. To gain useful insights into the role of RAs in multi-cell mixed-field communications, we first analyze a special case with a single user per cell. For this case, we obtain a closed-form expression for the rotation-aware inter-cell mixed-field interference using the Fresnel integrals and analytically show that RA rotation can effectively mitigate such interference, thereby substantially improving system performance. For the general case with multiple users per cell, we develop an efficient double-layer algorithm: the inner layer optimizes the transmit beamforming at each BS via semidefinite relaxation (SDR) and successive convex approximation (SCA); while the outer layer determines the rotation angles of the RA arrays using particle swarm optimization (PSO). Numerical results demonstrate that RA-enabled multi-cell systems achieve significant performance gains over conventional fixed-antenna systems, and the proposed joint design consistently outperforms various benchmark schemes.

Six-dimensional movable antenna (6DMA) introduces spatial degrees of freedom (DoFs) through joint three-dimensional (3D) position and rotation adjustment, offering great potential for enhancing physical-layer security (PLS). However, when eavesdroppers (Eves) are angularly proximate to legitimate users or occupy dominant propagation paths, existing movable antenna schemes that optimize only position or rotation separately cannot fully exploit spatial DoFs, resulting in limited security performance. To overcome this limitation, this letter investigates a 6DMA-assisted secure communication system where a base station equipped with 6DMA surfaces transmits confidential information to multiple legitimate users in the presence of multiple Eves. We aim to maximize the sum secrecy rate by jointly optimizing the transmit beamforming and artificial noise (AN) vector, along with the 3D positions and 3D rotations of all 6DMA surfaces. Accordingly, we propose an efficient alternating optimization (AO) algorithm to obtain a high-quality suboptimal solution, where the positions and rotations of 6DMA surfaces are optimized via a proximal successive convex approximation (PSCA) technique. Simulation results verify the potential of the 6DMA-assisted wireless system for secure communication, and demonstrate that the incorporation of AN into the 6DMA-assisted design can further improve the secrecy performance.

In this paper, we propose a new rotatable antenna (RA) model to improve the performance of wireless communication systems. Different from conventional fixed antennas, the proposed RA system can flexibly and independently alter the boresight direction of each antenna via mechanical or electronic means to exploit new spatial degrees-of-freedom (DoFs). Specifically, we investigate an RA-enabled uplink communication system, where the receive beamforming and the boresight directions of all RAs at the base station (BS) are jointly optimized to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among all the users. In the special single-user and free-space propagation setup, the optimal boresight directions of RAs are derived in closed form with the maximum-ratio combining (MRC) beamformer applied at the BS. In the general multi-user and multipath channel setup, we first propose an alternating optimization (AO) algorithm to alternately optimize the receive beamforming and the boresight directions of RAs in an iterative manner. Then, a two-stage algorithm that solves the formulated problem without the need for iteration is proposed to further reduce computational complexity. Moreover, we extend the channel model to incorporate polarization effects and frequency-selective fading while catering to antenna boresight rotation. Simulation results are provided to validate our analytical results and demonstrate that the proposed RA system can significantly improve the communication performance as compared to other benchmark schemes.

Unlike conventional fixed-antenna architectures, rotatable antenna (RA) has shown great potential in enhancing wireless communication performance by exploiting additional spatial degrees of freedom (DoFs) in a cost-effective manner. In this letter, we propose a novel RA-enabled covert communication system, where an RA array-based transmitter (Alice) sends covert information to a legitimate user (Bob) in the presence of multiple wardens (Willies). To maximize the covert rate, we optimize the transmit beamforming vector and the rotational angles of individual RAs, subject to the constraints on covertness, transmit power, and antenna rotational range. To address the non-convex formulated problem, we decompose it into two subproblems and propose an efficient alternating optimization (AO) algorithm to solve the two subproblems iteratively, where the second-order cone programming (SOCP) method and successive convex approximation (SCA) approach are applied separately. Simulation results demonstrate that the proposed RA-enabled covert communication system can provide significantly superior covertness performance to other benchmark schemes.

In this paper, we propose a new concept of self-sustainable active metasurface (SAM), which exploits the dual advantages of energy harvesting in terms of self-sustainability and active metasurface in terms of information transmission, to achieve continuous operation and flexible deployment for reconfigurable intelligent surface (RIS) and simultaneously mitigate its multiplicative fading. SAM can enhance incident signals via power amplifiers and achieve self-sustainability by harvesting ambient energy. We propose three operation schemes to implement energy harvesting and information transmission for SAM, namely, time-switching based SAM (TS-SAM), power-splitting based SAM (PS-SAM), and element-splitting based SAM (ES-SAM). Then, we propose three new metrics, namely, energy-information outage probability (EIOP), energy-information intercept probability (EIIP), and secure energy efficiency ratio (SEER). The accurate and asymptotic EIOP and EIIP as well as accurate SEER for the three proposed schemes are analyzed, respectively. The results show that compared to self-sustainable passive RIS, TS-SAM and ES-SAM have better EIOPs, and PS-SAM has a better EIIP. Among the three schemes, PS-SAM achieves the best EIOP at low RF energy, while TS-SAM and ES-SAM perform better in high-energy scenarios. For EIIP, PS-SAM outperforms the other two schemes. In particular, compared to self-sustainable passive RIS, TS-SAM and ES-SAM have better SEERs, verifying the superiority of the proposed TS-SAM and ES-SAM. Among all inter-node distances, the distance between user and SAM dominates the performance. When the harvested energy and the number of reflecting elements are sufficiently large, the EIOP and EIIP of TS-SAM and ES-SAM are unrelated to the amplification factor of SAM.