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Xidong Mu

Publications and source records attributed to Xidong Mu.

At least 37 records · Page 2Linked to original sources

Delay Minimization in Pinching-Antenna-enabled NOMA-MEC Networks

This letter proposes a novel pinching antenna systems (PASS) enabled non-orthogonal multiple access (NOMA) multi-access edge computing (MEC) framework. An optimization problem is formulated to minimize the maximum task delay by optimizing offloading ratios, transmit powers, and pinching antenna (PA) positions, subject to constraints on maximum transmit power, user energy budgets, and minimum PA separation to mitigate coupling effects. To address the non-convex problem, a bisection search-based alternating optimization (AO) algorithm is developed, where each subproblem is iteratively solved for a given task delay. Numerical simulations demonstrate that the proposed framework significantly reduces the task delay compared to benchmark schemes.

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SE-EE Tradeoff in Pinching-Antenna Systems: Waveguide Multiplexing or Waveguide Switching?

The spectral and energy efficiency (SE-EE) trade-off in pinching-antenna systems (PASS) is investigated in this paper. In particular, two practical operating protocols, namely waveguide multiplexing (WM) and waveguide switching (WS), are considered. A multi-objective optimization problem (MOOP) is formulated to jointly optimize the baseband and pinching beamforming for maximizing the achievable SE and EE, which is then converted into a single-objective problem via the ε-constraint method. For WM, the problem is decomposed within the alternating-optimization framework, where the baseband beamforming is optimized using the successive convex approximation, and the pinching beamforming is updated through the particle swarm optimization. For WS, due to the time-division transmission and interference-free nature, the pinching beamforming in each time slot is first adjusted to maximize the served user channel gain, followed by the baseband power allocation. Simulation results demonstrate that 1) PASS outperforms conventional antennas by mitigating large-scale path losses; 2) WS leads to a higher maximum achievable EE by activating a single RF chain, whereas WM yields a higher SE upper bound by serving all users concurrently; and 3) increasing the number of users substantially enhances SE under WM, whereas WS shows more pronounced benefits in low-signal-to-noise ratio regimes.

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User Localization and Channel Estimation for Pinching-Antenna Systems (PASS)

This letter proposes a novel user localization and channel estimation framework for pinching-antenna systems (PASS), where pinching antennas are grouped into subarrays on each waveguide to cooperatively estimate user/scatterer locations, thus reconstructing channels. Both single-waveguide (SW) and multi-waveguide (MW) structures are considered. SW consists of multiple alternatingly activated subarrays, while MW deploys one subarray on each waveguide to enable concurrent subarray measurements. For the 2D scenarios with a fixed user/scatter height, an orthogonal matching pursuit-based geometry-consistent localization (OMP-GCL) algorithm is proposed, which leverages inter-subarray geometric relationships and compressed sensing for precise estimation. Theoretical analysis on Cramér-Rao lower bound (CRLB) demonstrates that: 1) The estimation accuracy can be improved by increasing the geometric diversity through multi-subarray deployment; and 2) SW provides a limited geometric diversity within a $180^\circ$ half space and leads to angle ambiguity, while MW enables full-space observations and reduces overheads. The OMP-GCL algorithm is further extended to 3D scenarios, where user and scatter heights are also estimated. Numerical results validate the theoretical analysis, and verify that MW achieves centimeter- and decimeter-level localization accuracy in 2D and 3D scenarios with only three waveguides.

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Multi-Functional Programmable Metasurfaces for 6G and Beyond

The sixth-generation and beyond (B6G) networks are envisioned to support advanced applications that demand high-speed communication, high-precision sensing, and high-performance computing. To underpin this multi-functional evolution, energy- and cost-efficient programmable metasurfaces (PMs) have emerged as a promising technology for dynamically manipulating electromagnetic waves. This paper provides a comprehensive survey of representative multi-functional PM paradigms, with a specific focus on achieving \emph{full-space communication coverage}, \emph{ubiquitous sensing}, as well as \emph{intelligent signal processing and computing}. i) For simultaneously transmitting and reflecting surfaces (STARS)-enabled full-space communications, we elaborate on their operational protocols and pivotal applications in supporting efficient communications, physical layer security, unmanned aerial vehicle networks, and wireless power transfer. ii) For PM-underpinned ubiquitous sensing, we formulate the signal models for the PM-assisted architecture and systematically characterize its advantages in near-field and cooperative sensing, while transitioning to the PM-enabled transceiver architecture and demonstrating its superior performance in multi-band operations. iii) For advanced signal processing and computing, we explore the novel paradigm of stacked intelligent metasurfaces (SIMs), investigating their implementation in wave-domain analog processing and over-the-air mathematical computing. Finally, we identify key research challenges and envision future directions for multi-functional PMs towards B6G.

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Resource Allocation for Pinching-Antenna Systems (PASS)-enabled NOMA Communications

Pinching-antenna systems (PASS) have emerged as a promising technology due to their ability to dynamically reconfigure wireless propagation environments. A novel PASS-based multi-user non-orthogonal multiple access (NOMA) framework is proposed by exploiting the waveguide-division (WD) transmission characteristic. Specifically, each NOMA user cluster is served by one dedicated waveguide, and the corresponding pinching beamforming is exploited to enhance the intra-cluster performance while mitigating the inter-cluster interference. Based on this framework, a sum-rate maximization problem is formulated for jointly optimizing power allocation, pinching beamforming, and user scheduling. To solve this problem, a two-step algorithm is developed, which decomposes the original problem into two subproblems. For the joint power allocation and pinching beamforming design, a penalty dual decomposition (PDD) algorithm is proposed to obtain the locally optimal solutions. Specifically, the coupling constraints are alleviated through augmented Lagrangian relaxation, and the resulting augmented Lagrangian (AL) problem is decomposed into four subproblems, which are solved by the block coordinate descent (BCD) method. For the user scheduling, a low-complexity matching algorithm is developed to solve the user-to-waveguide assignment problem. Simulation results demonstrate that 1) the proposed PASS-based NOMA framework under the WD transmission structure achieves significant sum-rate gain over conventional fixed-position antenna systems and orthogonal multiple access (OMA) scheme; and 2) the proposed matching-based user scheduling algorithm achieves near-optimal user-waveguide association with low computational complexity.

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Pinching-Antenna Systems-Assisted SWIPT: A Rate-Energy Trade-off Perspective

This paper investigates the rate-energy trade-off for pinching-antenna systems (PASS)-assisted simultaneous wireless information and power transfer (SWIPT) systems. Both the single information user (IU)/energy user (EU) and multiple IUs/EUs scenarios are considered.1) For the single IU/EU scenario, a pinching beamforming optimization problem is formulated for simultaneously maximizing data rate and harvested energy. To tackle this problem, a two-stage algorithm is proposed. Specifically, the successive convex approximation (SCA) method is first invoked for minimizing the large-scale path loss, which is followed by the fine-tuning method for the phase alignment. 2) For the multiple IUs/EUs scenario, three multiple access schemes are considered, i.e., frequency division multiple access (FDMA), time division multiple access (TDMA), and non-orthogonal multiple access (NOMA). The corresponding multi-objective optimization problem (MOOP) that simultaneously maximizes the minimum data rate and minimum harvested energy is formulated for ensuring users' fairness. To address this problem, we adopt the $ε$-constraint method to first convert the intractable MOOPs to single-objective optimization problems (SOOPs). Then, for the SOOP under each multiple access protocol, the particle swarm optimization (PSO) and convex optimization methods are adopted for solving the pinching beamforming and resource allocation problems, respectively. Simulation results unveil that: i) PASS can achieve a significantly superior rate-energy region compared to conventional fixed-position antenna systems for pinching beamforming; and ii) by exploiting the time-switching feature, TDMA can outperform both NOMA and FDMA for the multiple IUs/EUs scenario.

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Pinching-Antenna Systems-Enabled Multi-User Communications: Transmission Structures and Beamforming Optimization

Pinching-antenna systems (PASS) represent an innovative advancement in flexible-antenna technologies, aimed at significantly improving wireless communications by ensuring reliable line-of-sight connections and dynamic antenna array reconfigurations. To employ multi-waveguide PASS in multi-user communications, three practical transmission structures are proposed, namely waveguide multiplexing (WM), waveguide division (WD), and waveguide switching (WS). Based on the proposed structures, the joint baseband signal processing and pinching beamforming design is studied for a general multi-group multicast communication system, with the unicast communication encompassed as a special case. A max-min fairness problem is formulated for each proposed transmission structure, subject to the maximum transmit power constraint. For WM, to solve the highly-coupled and non-convex MMF problem with complex exponential and fractional expressions, a penalty dual decomposition (PDD)-based algorithm is invoked for obtaining locally optimal solutions. Specifically, the augmented Lagrangian relaxation is first applied to alleviate the stringent coupling constraints, which is followed by the block decomposition over the resulting augmented Lagrangian function. Then, the proposed PDD-based algorithm is extended to solve the MMF problem for both WD and WS. Furthermore, a low-complexity algorithm is proposed for the unicast case employing the WS structure, by simultaneously aligning the signal phases and minimizing the large-scale path loss at each user. Finally, numerical results reveal that: 1) the MMF performance is significantly improved by employing the PASS compared to conventional fixed-position antenna systems; 2) WS and WM are suitable for unicast and multicast communications, respectively; 3) the performance gap between WD and WM can be significantly alleviated when the users are geographically isolated.

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Pinching-Antenna System-Assisted Localization: A Stochastic Geometry Perspective

This paper proposes a novel localization framework underpinned by a pinching-antenna (PA) system, in which the target location is estimated using received signal strength (RSS) measurements obtained from downlink signals transmitted by the PAs. To develop a comprehensive analytical framework, we employ stochastic geometry to model the spatial distribution of the PAs, enabling tractable and insightful network-level performance analysis. Closed-form expressions for target localizability and the Cramer-Rao lower bound (CRLB) distribution are analytically derived, enabling the evaluation of the fundamental limits of PA-assisted localization systems without extensive simulations. Furthermore, the proposed framework provides practical guidance for selecting the optimal waveguide number to maximize localization performance. Numerical results also highlight the superiority of the PA-assisted approach over conventional fixed-antenna systems in terms of the CRLB.

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Pinching-Antenna-Enabled Cognitive Radio Networks

This paper investigates a pinching-antenna (PA)-enabled cognitive radio network, where both the primary transmitter (PT) and secondary transmitter (ST) are equipped with a single waveguide and multiple PAs to facilitate simultaneous spectrum sharing. Under a general Ricean fading channel model, a closed-form analytical expression for the average spectral efficiency (SE) achieved by PAs is first derived. Based on this, a sum-SE maximization problem is formulated to jointly optimize the primary and secondary pinching beamforming, subject to system constraints on the transmission power budgets, minimum antenna separation requirements, and feasible PA deployment regions. To address this non-convex problem, a three-stage optimization algorithm is developed to sequentially optimize both the PT and ST pinching beamforming, and the ST power control. For the PT and ST pinching beamforming optimization, the coarse positions of PA are first determined at the waveguide-level. Then, wavelength-level refinements achieve constructive signal combination at the intended user and destructive superposition at the unintended user. For the ST power control, a closed-form solution is derived. Simulation results demonstrate that i) PAs can achieve significant SE improvements over conventional fixed-position antennas; ii) the proposed pinching beamforming design achieves effective interference suppression and superior performance for both even and odd numbers of PAs; and iii) the developed three-stage optimization algorithm enables nearly orthogonal transmission between the primary and secondary networks.

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PASS-Enhanced MEC: Joint Optimization of Task Offloading and Uplink PASS Beamforming

A pinching-antenna system (PASS)-enhanced mobile edge computing (MEC) architecture is investigated to improve the task offloading efficiency and latency performance in dynamic wireless environments. By leveraging dielectric waveguides and flexibly adjustable pinching antennas, PASS establishes short-distance line-of-sight (LoS) links while effectively mitigating the significant path loss and potential signal blockage, making it a promising solution for high-frequency MEC systems. We formulate a network latency minimization problem to joint optimize uplink PASS beamforming and task offloading. The resulting problem is modeled as a Markov decision process (MDP) and solved via the deep reinforcement learning (DRL) method. To address the instability introduced by the $\max$ operator in the objective function, we propose a load balancing-aware proximal policy optimization (LBPPO) algorithm. LBPPO incorporates both node-level and waveguide-level load balancing information into the policy design, maintaining computational and transmission delay equilibrium, respectively. Simulation results demonstrate that the proposed PASS-enhanced MEC with adaptive uplink PASS beamforming exhibit stronger convergence capability than fixed-PA baselines and conventional MIMO-assisted MEC, especially in scenarios with a large number of UEs or high transmit power.

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Pinching-Antenna Systems (PASS): Power Radiation Model and Optimal Beamforming Design

Pinching-antenna systems (PASS) improve wireless links by configuring the locations of activated pinching antennas along dielectric waveguides, namely pinching beamforming. In this paper, a novel adjustable power radiation model is proposed for PASS, where power radiation ratios of pinching antennas can be flexibly controlled by tuning the spacing between pinching antennas and waveguides. A closed-form pinching antenna spacing arrangement strategy is derived to achieve the commonly assumed equal-power radiation. Based on this, a practical PASS framework relying on discrete activation is considered, where pinching antennas can only be activated among a set of predefined locations. A transmit power minimization problem is formulated, which jointly optimizes the transmit beamforming, pinching beamforming, and the numbers of activated pinching antennas, subject to each user's minimum rate requirement. (1) To solve the resulting highly coupled mixed-integer nonlinear programming (MINLP) problem, branch-and-bound (BnB)-based algorithms are proposed for both single-user and multi-user scenarios, which is guaranteed to converge to globally optimal solutions. (2) A low-complexity many-to-many matching algorithm is further developed. Combined with the Karush-Kuhn-Tucker (KKT) theory, locally optimal and pairwise-stable solutions are obtained within polynomial-time complexity. Simulation results demonstrate that: (i) PASS significantly outperforms conventional multi-antenna architectures, particularly when the number of users and the spatial range increase; and (ii) The proposed matching-based algorithm achieves near-optimal performance, resulting in only a slight performance loss while significantly reducing computational overheads. Code is available at https://github.com/xiaoxiaxusummer/PASS_Discrete

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Near-Field Integrated Sensing and Communications

A near-field integrated sensing and communications (ISAC) framework is proposed, which introduces an additional distance dimension for both sensing and communications compared to the conventional far-field system. In particular, the Cramer-Rao bound for the near-field joint distance and angle sensing is derived, which is minimized subject to the minimum communication rate requirement of each user. Both fully digital antennas and hybrid digital and analog antennas are investigated. For fully digital antennas, a globally optimal solution of the ISAC waveform is obtained via semidefinite relaxation. For hybrid antennas, a high-quality solution is obtained through two-stage optimization. Numerical results demonstrate the performance gain introduced by the additional distance dimension of the near-field ISAC over the far-field ISAC.

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Sum Capacity Characterization of Pinching Antennas-assisted Multiple Access Channels

Pinching antenna system (PASS) has recently shown its promising ability to flexibly reconfigure wireless channels via dynamically adjusting the positions of pinching antennas over a dielectric waveguide, termed as pinching beamforming. This paper studies the fundamental limit of the sum rate for a PASS-assisted multiple access channel, where multiple users transmit individual messages to a base station under the average power constraint. To this end, a dynamic pinching beamforming setup is conceived, where multiple pinching beamforming vectors are employed in a transmission period and the capacity-achieving non-orthogonal multiple access (NOMA) based scheme is considered. For the ideal case with an asymptotically large number of pinching beamforming vectors, the optimal transmission scheme is unveiled to carry out alternating transmission among each user whose channel power gain is maximized with the tailored pinching beamforming. This implies that NOMA is not needed for achieving the sum capacity and the required optimal number of pinching beamforming vectors is equal to the number of users. With this insight, the corresponding sum rate is derived in closed-form expression, which serves as the upper bound of the sum rate. Inspired by this result, a lower bound of the sum rate under an arbitrarily finite number of pinching beamforming vectors is obtained. Numerical results validate our theoretical findings and also illustrate the practical significance of using dynamic pinching beamforming to improve the sum rate.

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SE and EE Tradeoff in Active STAR-RIS Assisted Systems With Hardware Impairments

This paper investigates the problem of resource efficiency maximization in an active simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted communication system under practical transceiver hardware impairments (HWIs). We aim to obtain an optimal tradeoff between system spectral efficiency (SE) and energy efficiency (EE), by jointly optimizing the base station (BS) transmit beamforming and the active STAR-RIS beamforming. To tackle the challenges in the fractional objective function, we begin by applying the quadratic transformation method to simplify it into a manageable form. An alternating optimization-based algorithm is then developed to iteratively update the BS and STAR-RIS beamforming coefficients. Simulation results demonstrate that the proposed scheme performs better than other baseline schemes in the presence of HWIs. Moreover, the variation of the achievable SE-EE region with different transmit power budgets is analyzed.

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Multiport Network Modeling and Optimization for Reconfigurable Pinching-Antenna Systems

A reconfigurable pinching-antenna system (PASS) is presented, endowing pinching antennas (PAs) with both amplitude- and phase-controllable radiation beyond conventional implementations. To characterize this feature, a general and physically consistent model is established for PASS via multiport network theory. Within this model, the fundamental constraint of ideal reconfigurability of PAs is identified, allowing the full control of signal amplitudes and phases. A practical directional-coupler (DC)-based PA model is then proposed, enabling both amplitude-only control and amplitude-constrained phase control. Beamforming optimization is investigated for both ideal and practical cases: an optimal solution is obtained for ideal PAs, whereas a high-quality iterative algorithm is developed for DC-based PAs. Numerical results suggest that in single-user scenarios: (i) with optimized PA positions, performance gains arise primarily from amplitude reconfigurability and DC-based PAs approach ideal performance, and (ii) with fixed PA positions, both amplitude and phase reconfigurability are critical and DC-based PAs incur non-negligible loss.

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Near-Field Integrated Sensing and Communications for Secure UAV Networks

A novel near-field integrated sensing and communications framework for secure unmanned aerial vehicle (UAV) networks with high time efficiency is proposed. A ground base station (GBS) with large aperture size communicates with one communication UAV (C-UAV) under the existence of one eavesdropping UAV (E-UAV), where the artificial noise (AN) is employed for both jamming and sensing purpose. Given that the E-UAV's motion model is unknown at the GBS, we first propose a near-field localization and trajectory tracking scheme. Specifically, exploiting the variant Doppler shift observations over the spatial domain in the near field, the E-UAV's three-dimensional (3D) velocities are estimated from echo signals. To provide the timely correction of location prediction errors, the extended Kalman filter (EKF) is adopted to fuse the predicted states and the measured ones. Subsequently, based on the real-time predicated location of the E-UAV, we further propose a joint GBS beamforming and C-UAV trajectory design scheme for maximizing the instantaneous secrecy rate, while guaranteeing the sensing accuracy constraint. To solve the resultant non-convex problem, an alternating optimization approach is developed, where the near-field GBS beamforming and the C-UAV trajectory design subproblems are iteratively solved by exploiting the successive convex approximation method. Finally, our numerical results unveil that: 1) the E-UAV's 3D velocities and location can be accurately estimated in real time with our proposed framework by exploiting the near-field spherical wave propagation; and 2) the proposed framework achieves superior secrecy rate compared to benchmark schemes and closely approaches the performance when the E-UAV trajectory is perfectly known.

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Federated Learning in Active STARS-Aided Uplink Networks

Active simultaneously transmitting and reflecting surfaces (ASTARS) have attracted growing research interest due to its ability to alleviate multiplicative fading and reshape the electromagnetic environment across the entire space. In this paper, we utilise ASTARS to assist the federated learning (FL) uplink model transfer and further reduce the number of uploaded parameter counts through over-the-air (OTA) computing techniques. The impact of model aggregation errors on ASTARS-aided FL uplink networks is characterized. We derive an upper bound on the aggregation error of the OTA-FL model and quantify the training loss due to communication errors. Then, we define the performance of OTA-FL as a joint optimization problem that encompasses both the assignment of received beams and the phase shifting of ASTARS, aiming to achieve the maximum learning efficiency and high-quality signal transmission. Numerical results demonstrate that: i) The FL accuracy in ASTARS uplink networks are enhanced compared to that in state-of-the-art networks; ii) The ASTARS enabled FL system achieves the better learning accuracy using fewer active units than other baseline, especially when the dataset is more discrete; and iii) FL accuracy improves with higher amplification power, but excessive amplification makes thermal noise the dominant source of error.

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Pinching-Antenna Systems (PASS): Architecture Designs, Opportunities, and Outlook

Flexible-antenna systems have recently attracted significant research attention due to their potential to intelligently reconfigure wireless channels. However, the current flexible-antenna systems still suffer from fundamental limitations, such as free-space path loss and line-of-sight blockage. This article introduces a novel flexible-antenna system, termed the Pinching-Antenna SyStem (PASS). PASS adopts the dielectric waveguides as the primary transmission medium and radiates signals into free space by flexibly pinching discrete dielectric particles, referred to as pinching antennas, along the waveguide. By combining the strengths of both wireless and wired communication, PASS effectively mitigates inherent wireless limitations while offering high antenna reconfigurability. This article reviews the key features of PASS in comparison with conventional wireless systems, analyzes its main advantages, and discusses potential designs, transmission architectures, and application scenarios. Finally, it outlines promising research directions and open challenges associated with PASS.

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