The performance of linear receive beamforming in continuous-aperture array (CAPA)-based uplink communications is analyzed. Three continuous beamforming techniques are proposed under the criteria of maximum-ratio combining (MRC), zero-forcing (ZF), and minimum mean-squared error (MMSE). i) ForMRC beamforming, a closed-form expression for the beamformer is derived to maximize per-user signal power. The achieved uplink rate and mean-squared error (MSE) in detecting received data symbols are analyzed. ii) ForZF beamforming, a closed-form beamformer is derived based on channel correlation to eliminate interference. As a further advance, its optimality in maximizing effective channel gain while ensuring zero inter-user interference is proven. iii)MMSE beamformingis established as the optimal linear receive approach for CAPAs in terms of maximizing per-user rate and minimizing MSE. Closed-form expressions are derived for the MMSE beamformer and the achievable sum-rate and sum-MSE. It is mathematically proven that all proposed beamformers lie within the signal subspace spanned by users’ spatial responses. Numerical results demonstrate that CAPAs outperform conventional spatially-discrete arrays (SPDAs) by achieving higher sum-rates and lower sum- MSEs under the proposed linear beamforming techniques.

A continuous-aperture array (CAPA)-based secure transmission framework is proposed to enhance physical layer security. Continuous current distributions, or beamformers, are designed to maximize the secrecy transmission rate under a power constraint and to minimize the required transmission power for achieving a specific target secrecy rate. On this basis, the fundamental secrecy performance limits achieved by CAPAs are analyzed by deriving closed-form expressions for the maximum secrecy rate (MSR) and minimum required power (MRP), along with the corresponding optimal current distributions. To provide further insights, asymptotic analyses are performed for the MSR and MRP, which reveals that i) for the MSR, the optimal current distribution simplifies to maximal ratio transmission (MRT) beamforming in the low-SNR regime and to zero-forcing (ZF) beamforming in the high-SNR regime; ii) for the MRP, the optimal current distribution simplifies to ZF beamforming in the high-SNR regime. The derived results are specialized to the typical array structures, e.g., planar CAPAs and planar spatially discrete arrays (SPDAs). The rate and power scaling laws are further analyzed by assuming an infinitely large CAPA. Numerical results demonstrate that: i) the proposed secure continuous beamforming design outperforms MRT and ZF beamforming in terms of both achievable secrecy rate and power efficiency; ii) CAPAs achieve superior secrecy performance compared to conventional SPDAs.

A continuous-aperture array (CAPA)-based integrated sensing and communications (ISAC) framework is proposed for both downlink and uplink scenarios. Within this framework, continuous operator-based signal models are employed to describe the sensing and communication processes. The performance of communication and sensing is analyzed using two information-theoretic metrics: the communication rate (CR) and the sensing rate (SR). 1) For downlink ISAC, three continuous beamforming designs are proposed: i) the communications-centric (C-C) design that maximizes the CR, ii) the sensing-centric (S-C) design that maximizes the SR, and iii) the Pareto-optimal design that characterizes the Pareto boundary of the CR-SR region. A low-complexity signal subspace-based approach is proposed to derive the closed-form optimal beamformers for the considered designs. On this basis, closed-form expressions are derived for the achievable CRs and SRs, and the downlink rate region achieved by CAPAs is characterized. 2) For uplink ISAC, the C-C and S-C successive interference cancellation-based methods are proposed to manage inter-functionality interference. Using the subspace approach closed-form expressions for the optimal detectors as well as the achievable CRs and SRs are derived. The uplink SR-CR region is characterized based on the time-sharing technique. Numerical results demonstrate that, for both downlink and uplink, CAPA-based ISAC achieves higher CRs and SRs as well as larger CR-SR regions compared to conventional spatially discrete array-based ISAC.

This article investigates the integration of movable antennas (MAs) into multicast communication systems. By discretizing the motion of the MAs, a novel MA-assisted multicast transmission architecture is formulated. An alternating optimization (AO) algorithm based on successive convex approximation is proposed to optimize the transmit beamforming and antenna positions. To gain further insights, the two-user case is examined, and a closed-form expression for the optimal beamformer is derived. On this basis, a low-complexity greedy search algorithm is developed to optimize the placement of the MAs. Furthermore, under the assumption of a line-of-sight propagation environment, a branch-and-bound algorithm is designed to determine the globally optimal antenna configuration with reduced complexity compared to exhaustive search. Numerical simulations confirm that the proposed methods effectively enhance the achievable multicast rate.

The performance of linear receive beamforming in continuous-aperture array (CAPA)-based uplink communications is investigated. Three continuous beamforming strategies are proposed based on the principles of maximum-ratio combining (MRC), zero-forcing (ZF), and maximum signal-to-interference-plus-noise ratio (SINR) (i.e., optimal beamforming). For MRC beamforming, closed-form expressions for both the beamformer and the achievable sum-rate are derived. For ZF beamforming, a closed-form solution is developed using channel correlation to effectively eliminate inter-user interference. For optimal beamforming, a closed-form beamformer is obtained by solving an operator-based Rayleigh quotient maximization problem, and the associated achievable sum-rate is characterized. Numerical results confirm that CAPAs outperform traditional spatially-discrete arrays (SPDAs), achieving superior sum-rate performance under all three beamforming schemes.

A novel movable antenna (MA)-aided secure transmission framework is proposed to enhance the secrecy transmission rate without relying on the eavesdropper’s channel state information. Within this framework, a joint beamforming and jamming scheme is proposed, where the power of the confidential signal is minimized by optimizing the positions of the MAs, and the residual power is used to jam the eavesdropper. An efficient gradient-based method is employed to solve this non-convex problem. Numerical results are provided to demonstrate the superiority of the MA-based framework over systems using traditional fixed-position antennas in secure transmission.

The diversity and multiplexing performance of continuous aperture array (CAPA)-based multiple-input multiple-output (MIMO) channels is analyzed. Angular-domain fading models are derived, and an angular-domain transmission framework is proposed to support CAPA-based MIMO communications. Asymptotic expressions are derived for the achievable outage probability (OP) and average data rate (ADR), and insights into the diversity-multiplexing trade-off (DMT) and associated array gain are provided. Further, the performance of CAPAs is compared with that of conventional spatially discrete arrays (SPDAs) to highlight the advantages of CAPAs. Analytical and numerical results demonstrate that: i) CAPAs achieve lower OP and higher ADR than SPDAs; ii) CAPAs attain the same DMT as SPDAs with half-wavelength antenna spacing but with a higher array gain; and iii) CAPAs outperform SPDAs in DMT when the antenna spacing exceeds half a wavelength.

A framework of holographic MIMO (HMIMO) based integrated sensing and communications (ISAC), i.e., holographic ISAC (HISAC), is proposed. An accurate spherical wave-based model is utilized to characterize sensing link. The spacial correlation introduced by the densely spaced antennas of the HMIMO is incorporated when modeling the communication channel. Based on the proposed framework, closed-form expressions are derived for sensing rates (SRs), communication rates (CRs), and outage probabilities under different beamforming strategies to investigate fundamental information theoretical limits for HISAC. Further insights are gained by examining high signal-to-noise ratio slopes and diversity orders. A Pareto optimal design is proposed to characterize the attainable SR-CR region. Numerical results reveal that HISAC outperforms the conventional MIMO based ISAC and the HMIMO based frequency-division sensing and communications system in terms of both sensing and communications.

A closed-form expression for the secrecy capacity under near-field communications is derived and compared with its far-field counterpart. To gain further insights, the capacity scaling law is revealed by assuming an infinitely large transmit array and an infinitely high power. Both analytical and numerical results demonstrate that, different from the far-field scenario, i) nearfield communications expand the areas where secure transmission is feasible, specifically when the eavesdropper is located in the same direction as the intended receiver; ii) as the number of transmit antennas increases, the near-field secrecy capacity is capped at a finite value, adhering to the principle of energy conservation.

Accurate modeling of radio wave propagation is essential for the design and deployment of wireless communication systems in tunnels. Among various numerical deterministic methods, the finite-difference (FDPE) parabolic equation and split-step (SSPE) parabolic equation approaches have been extensively adopted due to their favorable trade-offs between accuracy and computational efficiency. However, a rigorous comparative evaluation of these two methods remains insufficiently addressed in the literature. This paper presents a systematic investigation into the numerical performance of FDPE and SSPE techniques for tunnel propagation modeling. Both error behavior and computational complexity are analyzed under various configurations.

A novel frequency diverse array (FDA)-assisted secure transmission framework is proposed, which leverages additional frequency offsets to enhance physical layer security. Specifically, an FDA-assisted wiretap channel is considered, where the transmit beamforming and frequency offsets at each antenna are jointly optimized. A novel alternating optimization-based method is introduced to address the non-convex problem of secure transmission, focusing on minimizing transmit power and maximizing the secrecy rate. Numerical results are provided to demonstrate the superiority of the FDA-based framework compared to systems employing traditional phased array antennas in secure transmission.

A holographic multiple-input multiple-output (MIMO)-based integrated sensing and communications (ISAC) framework is proposed for both downlink and uplink scenarios. The spatial correlation is incorporated into the communication channel modeling, while a spherical wave-based model is used to characterize the sensing link. By considering both instantaneous and statistical channel state information, closed-form expressions are derived for sensing rates (SRs), communication rates (CRs), and outage probabilities under various ISAC designs. This enables an investigation into the theoretical performance limits of the proposed holographic MIMO-based ISAC (HISAC) framework. Further insights are gained by examining the high signal-to-noise ratio (SNR) slopes and diversity orders. Specifically: I) for the downlink case, a sensing-centric (S-C) design and a communications-centric (C-C) design are investigated using different beamforming strategies, and a Pareto optimal design is proposed to characterize the attainable SR-CR region; II) for the uplink case, the S-C design and the C-C design differ in the interference cancellation order between the communication and sensing signals, with the rate region obtained through a time-sharing strategy. Numerical results are provided to demonstrate that HISAC systems outperform both conventional MIMO-based ISAC systems and holographic MIMO-based frequency-division sensing and communications systems, underscoring the superior performance of the HISAC framework.

Cellular-connected uncrewed aerial vehicles (UAVs) have gained increasing attention due to the potential to leverage existing cellular infrastructure for reliable communications between UAVs and base stations. They have been used for various applications, including weather forecasting and search and rescue operations. However, under extreme weather conditions such as rainfall, the trajectory design of cellular UAVs is quite challenging due to weak coverage regions in the sky, limitations of UAV flying time, and signal attenuation caused by raindrops. To this end, this paper proposes a physics-based trajectory design approach for cellular-connected UAVs in rainy environments. A physics-based electromagnetic simulator is utilized to take into account detailed environment information and the impact of rain on radio wave propagation. The trajectory optimization problem is formulated to jointly consider UAV flying time and signal-to-interference ratio, and is solved through a Markov decision process using deep reinforcement learning algorithms based on multi-step learning and double Q-learning. Optimal UAV trajectories are compared in examples with homogeneous atmosphere medium and rain medium. Additionally, a thorough study of varying weather conditions on trajectory design is provided, and the impact of weight coefficients in the UAV trajectory design is discussed. The proposed approach has demonstrated great potential for UAV trajectory design under rainy weather conditions.

A general fading model for multipath channels between two non-parallel continuous-aperture arrays (CAPAs) is proposed. Building on this model, the performance of diversity and multiplexing achieved by CAPAs over fading channels is analyzed. i) For multiple-input single-output (MISO) and singleinput multiple-output (SIMO) channels, Landau’s eigenvalue theorem is applied to analyze the autocorrelation of the spatial response. Closed-form expressions are derived for the outage probability (OP) and ergodic channel capacity (ECC). Asymptotic analyses in the high signal-to-noise ratio (SNR) regime are conducted to reveal the maximal achievable diversity and multiplexing gains. The diversity-multiplexing trade-off (DMT) is characterized, along with the array gain within the DMT framework. ii) For multiple-input multiple-output (MIMO) channels, a wavenumber-domain-based transmission framework is proposed to leverage the spatial degrees of freedom offered by CAPAs. Asymptotic approximations for the OP and ECC are derived, and the DMT is explored. The performance of CAPAs is further compared with that of conventional spatially-discrete arrays (SPDAs). Analytical and numerical results demonstrate that: i) CAPAs achieve a lower OP and higher ECC than SPDAs; ii) CAPAs achieve the same DMT as SPDAs with antenna spacing no larger than half a wavelength while attaining a higher array gain; and iii) CAPAs outperform SPDAs with antenna spacing greater than half a wavelength in terms of DMT.

A hybrid non-orthogonal multiple access (HNOMA) empowered integrated sensing and communications (ISAC) framework is proposed, which adaptively manages the additional sensing-to-communication (S2C) interference to save the transmit power. Two scenarios with different numbers of communication users (CUs) are investigated. For the first scenario where the number of CUs does not exceed the number of transmit antennas, a mixed integer problem is formulated to optimize the beamforming (BF) design and successive interference cancellation (SIC) options. An ideal case is primarily inspected, which unveils an insight into the required number of dedicated sensing beams. Inspired by this insight, the SIC options are determined while the remaining BF design is solved via semidefinite relaxation (SDR). For the second scenario where the number of CUs exceeds the number of transmit antennas, the CUs are further grouped into NOMA clusters to mitigate the communication-to-communication interference. An alternating optimization-based algorithm is developed, where the BF design, SIC options and power allocation are alternatively optimized. Simulation results reveal that: 1) the proposed algorithm achieves power-saving gain compared to the conventional ISAC; 2) the proposed algorithm can further exploit the benefits of NOMA to save transmission power while maintaining the least beampattern mismatch in the second scenario.

The channel capacity of near-field (NF) communications is characterized by considering three types of line-of-sight multiuser channels: I) multiple access channel (MAC), II) broadcast channel (BC), and III) multicast channel (MC). For NF MAC and BC, closed-form expressions are derived for the sum-rate capacity as well as the capacity region under a two-user scenario. These results are further extended to scenarios with an arbitrary number of users. For NF MC, closed-form expressions are derived for the two-user channel capacity and the capacity upper bound with more users. Further insights are gleaned by exploring special cases, including scenarios with infinitely large array apertures, co-directional users, and linear arrays. For comparison, the MAC and BC sum-rates achieved by typical linear combiners and precoders are also analyzed. Theoretical and numerical results are presented and compared with far-field communications to demonstrate that: I) the NF capacity of these three channels converges to finite values rather than growing unboundedly as the number of array elements increases; II) the capacity of the MAC and BC with co-directional users can be improved by using the additional range dimensions in NF channels to reduce inter-user interference (IUI); and III) the MC capacity benefits less from the NF effect compared to the MAC and BC, as multicasting is less sensitive to IUI.

The secrecy performance in both near-field and far-field communications is analyzed using two fundamental metrics: the secrecy capacity under a power constraint and the minimum power requirement to achieve a specified secrecy rate target. 1) For the secrecy capacity, a closed-form expression is derived under a discrete-time memoryless setup. This expression is further analyzed under several far-field and near-field channel models, and the capacity scaling law is revealed by assuming an infinitely large transmit array and an infinitely high power. A novel concept of “depth of insecurity” is proposed to evaluate the secrecy performance achieved by near-field beamfocusing. It is demonstrated that increasing the number of transmit antennas reduces this depth and thus improves the secrecy performance. 2) Regarding the minimum required power, a closed-form expression is derived and analyzed within far-field and near-field scenarios. Asymptotic analyses are performed by setting the number of transmit antennas to infinity to unveil the power scaling law. Numerical results are provided to demonstrate that: i) compared to far-field communications, near-field communications expand the areas where secure transmission is feasible, specifically when the eavesdropper is located in the same direction as the intended receiver; ii) as the number of transmit antennas increases, neither the secrecy capacity nor the minimum required power scales or vanishes unboundedly, adhering to the principle of energy conservation.

The capacity limits of continuous-aperture array (CAPA)-based wireless communications are characterized. To this end, an analytically tractable transmission framework is established for both uplink and downlink CAPA systems. Based on this framework, closed-form expressions for the single-user channel capacity are derived. The results are further extended to a multiuser case by characterizing the capacity limits of a two-user channel and proposing the associated capacity-achieving decoding and encoding schemes. In the uplink case, the capacity-achieving detectors and sum-rate capacity are derived, and the capacity region is characterized. In the downlink case, the uplink-downlink duality is established by deriving the uplink-to-downlink and downlink-to-uplink transformations under the same power constraint, based on which the optimal source current distributions and the achieved sum-rate capacity and capacity region are characterized. For comparison, the uplink and downlink sum-rates achieved by the linear zero-forcing scheme are also analyzed. To gain further insights, several case studies are presented by specializing the derived results into various array structures, including the planar CAPA, linear CAPA, and planar spatially discrete array (SPDA). Numerical results are provided to reveal that the channel capacity achieved by CAPAs converges towards a finite upper bound as the aperture size increases; and CAPAs offer superior capacity over the conventional SPDAs.

The performance of continuous aperture array (CAPA)-based wireless communications is analyzed in an uplink scenario. An analytical framework is proposed to characterize uplink CAPA-based transmission using electromagnetic field theories. On this basis, new expressions are derived for the channel capacity in a single-user scenario and the sum-rate capacity in a multiuser scenario, along with the capacity-achieving decoding schemes. These findings are proved to differ greatly from those established for conventional spatially discrete (SPD) arrays. Numerical results are provided to demonstrate that CAPA offers significant capacity gains compared to the SPD array.

The concept of aperture selection is proposed for continuous aperture array (CAPA)-based communications. The achieved performance is analyzed in an uplink scenario by considering both line-of-sight (LoS) and non-line-of-sight (NLoS) scenarios. In the LoS scenario, the optimal selection strategy is demonstrated to follow the nearest neighbor criterion, and the resulting signal-to-noise ratio (SNR) is analyzed. In the NLoS scenario, the achieved outage probability along with the diversity order is revealed. Numerical results are provided to demonstrate that aperture selection effectively maintains satisfactory performance by leveraging selection diversity while simultaneously reducing the implementation complexity of CAPAs.

Capacity limits of near-field (NF) multiple access channel (MAC) is characterized. Closed-form expressions are derived for the sum-rate capacity and the capacity region under a two-user scenario. These results are further extended to scenarios with an arbitrary number of users. Further insights are gleaned by exploring special cases, including scenarios with infinitely large array apertures and co-directional users. Theoretical and numerical results are presented and compared with far-field communications to demonstrate that: i) the NF capacity of the MAC converges to finite values rather than growing unboundedly as the number of array elements increases; ii) the MAC capacity with co-directional users can be improved by using the additional range dimensions in NF channels to reduce inter-user interference.

This work studies a low-complexity design for re-configurable intelligent surface (RIS)-aided multiuser multiple-input multiple-output systems. The base station (BS) applies receive antenna selection to connect a subset of its antennas to the available radio frequency chains. For this setting, the BS switching network, uplink precoders, and RIS phase-shifts are jointly designed, such that the uplink sum-rate is maximized. The principle design problem reduces to an NP-hard mixed-integer optimization. We hence invoke the weighted minimum mean squared error technique and the penalty dual decomposition method to develop a tractable iterative algorithm that approxi-mates the optimal design effectively. Our numerical investigations verify the efficiency of the proposed algorithm and its superior performance as compared with the benchmark.

In this paper, a near-field ISAC framework is proposed with an accurate channel model, in which the loss caused by effective aperture and polarization mismatch are considered. Based on the proposed model, sensing and communication (S&C) performance are analyzed in terms of three different designs: the communications-centric design, the sensing-centric design, and the Pareto optimal design. Within each design, sensing rates (SRs) and communication rates (CRs) are derived. Moreover, the attainable SR-CR regions of the near-field ISAC are characterized. Numerical results reveal that 1) the adopted channel model is more accurate than the conventional models within near field; 2) ISAC achieves a more extensive rate region than the conventional frequency-division S&C.

This paper proposes a cluster-based Non-orthogonal multiple access framework for integrated sensing and communications (ISAC). Based on the proposed model, we investigate three typical ISAC precoding designs: sensing-centric design, communications-centric design, and Pareto optimal design. Under each scenario, the sensing rate (SR), communications rate (CR), and their asymptotic expressions in high signal-to-noise ratio (SNR) regime are derived. High-SNR slopes are also obtained to gain better insights. Finally, the SR-CR rate regions achieved by ISAC and the conventional frequency-division sensing and communications (FDSAC) are studied. Numerical results reveal that ISAC outperforms FDSAC in terms of both SR and CR, and is able to achieve a more extensive rate region.

By analyzing changes in Channel State Information (CSI) during the propagation of Wi-Fi signals in indoor environ-ments, researchers can achieve contactless perception of human behaviors. Due to the high complexity of the deep models used in CSI-based human activity recognition systems, it's difficult to be employed in edge computing devices. To improve the Wi-Fi perception accuracy and reduce the system complexity, this paper proposes a lightweight human behavior perception system LiteWiHAR. The system converts the filtered CSI signal in time domain into a two-dimensional image to increase its spatial structure information. Using ConvNeXt v2 layered encoder as the backbone feature extraction network, perceptual information containing deep and shallow features in the image is extracted layer by layer. By reducing the number of depthwise separable convolution channels and compressing the number of stacked blocks in the encoder, the degree of network fragmentation is reduced and the number of model parameters is compressed. Finally, the SimAM parameterless attention module is introduced to assist the network in capturing global information. The system is lightweight while maintaining good feature extraction capability. We validated the effectiveness of LiteWiHAR on three open-source datasets and demonstrated its superiority over other state-of-the-art systems.

This paper proposes a framework of multiple-input multiple-output based non-orthogonal multiple access for Integrated sensing and communications (ISAC), which incorporates signal alignment to enhance system performance. Sensing rate (SR) and communication rate (CR) are derived under three different precoding designs: sensing-centric design, communications-centric design, and Pareto optimal design. Moreover, the SR-CR regions achieved by ISAC and frequency-division sensing and communications (FDSAC) are studied. Numerical results reveal that ISAC outperforms FDSAC in terms of both SR and CR and can achieve a broader rate region, clearly showcasing its superiority over the conventional FDSAC.

This paper investigates reconfigurable intelligent surface (RIS) aided multi-cell non-orthogonal multiple access (NOMA) networks with stochastic geometry methods. Under Rayleigh and Nakagami-m fading channels, we provide two types of approximate channel models to depict RIS channels, i.e., the N-fold convolution model and the curve fitting model. The analysis reveals that the N-fold convolution model is accurate and tractable when ignoring inter-cell interference, while the curve fitting model can evaluate the impact of inter-cell interference with a small error. The N-fold convolution model provides accurate diversity orders compared to other existing approaches such as the central limit model. Based on these channel models, we derive the closed-form analytical and asymptotic expressions of coverage probabilities and ergodic rates for two paired NOMA users. The analytical results demonstrate that: i) When we ignore inter-cell interference, the diversity order of the typical user is equal to the number of Rayleigh fading channels; and ii) For Nakagami-m fading channels with coefficientm, the diversity order is equal tomtimes of the channel number. Numerical results show that: i) RISs are capable of enhancing the coverage performance and ergodic rates of the proposed network; and ii) RISs provide extra flexibility for NOMA decoding orders.

Integrated Sensing and Communications (ISAC) surpasses the conventional frequency-division sensing and communications (FDSAC) in terms of spectrum, energy, and hardware efficiency, with potential for greater enhancement through integration of non-orthogonal multiple access (NOMA). Leveraging these advantages, a multiple-input multiple-output NOMA-ISAC framework is proposed in this paper, in which the technique of signal alignment is adopted. The performance of the proposed framework for both downlink and uplink is analyzed. 1) The downlink ISAC is investigated under three different precoding designs: a sensing-centric (S-C) design, a communications-centric (C-C) design, and a Pareto optimal design. 2) For the uplink case, two scenarios are investigated: a S-C design and a C-C design, which vary based on the order of interference cancellation between the communication and sensing signals. In each of these scenarios, key performance metrics including sensing rate (SR), communication rate (CR), and outage probability are investigated. For a deeper understanding, the asymptotic performance of the system in the high signal-to-noise ratio (SNR) region is also explored, with a focus on the high-SNR slope and diversity order. Finally, the SR-CR rate regions achieved by ISAC and FDSAC are studied. Numerical results reveal that in both downlink and uplink cases, ISAC outperforms FDSAC in terms of sensing and communications performance and is capable of achieving a broader rate region, clearly showcasing its superiority.

This paper analyzes the performance of a downlink integrated sensing and communications (ISAC) system, where nonorthogonal multiple access (NOMA) is exploited to mitigate inter-user interference. Closed-form expressions are derived to evaluate the outage probability, ergodic communication rate, and sensing rate. Furthermore, asymptotic analyses are carried out to unveil diversity orders and high signal-to-noise ratio (SNR) slopes of the considered NOMA-ISAC system. As the further advance, the achievable sensing-communication rate region of ISAC is characterized. It is proved that ISAC system is capable of achieving a larger rate region than the conventional frequency-division sensing and communications (FDSAC) system.

A reconfigurable intelligent surface (RIS)-assisted downlink nonorthogonal multiple access (NOMA) Internet of Things (IoT) network is proposed, where a Quality-of-Service (QoS)-based NOMA clustering scheme is conceived to effectively utilize the limited wireless resources among IoT devices. A throughput maximization problem is formulated by jointly optimizing the phase shifts of the RIS and the power allocation of the base station (BS) from the short-term and long-term perspectives. We aim to investigate and compare the performance of deep learning (DL) and deep reinforcement learning (DRL) algorithms for solving the formulated problems. In particular, the DL method utilizes model-agnostic-metalearning (MAML) to enhance the generalization capability of the neural network and to accelerate the convergence rate. For the DRL method, the deep deterministic policy gradient (DDPG) algorithm is employed to incorporate continuous phase-shift variables. It shows that the DL method only focuses on the maximization of the instantaneous throughput, whereas the DRL method can coordinate the power consumption over different time slots to maximize the long-term throughput. Numerical results demonstrate that: 1) the proposed QoS-based NOMA clustering scheme achieves higher IoT throughput than the conventional channel-based scheme; 2) the implementation of RISs induces approximately 5%–25% throughput gain as the number of RIS elements increases from 8 to 64; 3) DL and DRL achieve a similar throughput performance for the short-term optimization, while DRL is superior for the long-term optimization, especially when the total transmit power is limited.

In recent years, there has been significant interest in the development of wireless train control systems. Among those, communication-based train control (CBTC) systems are new generation rail signaling systems, aimed at achieving real-time, automated train control through wireless communication between the train and a network of access points (APs).Radio channel characterization in railway environments is indispensable for the effective design and deployment of CBTC systems. In this paper, our recent work on the development of a physics-based wireless channel model is summarized. The validity of our developed model is verified against experimental data in various practical scenarios including the London Underground subway network in UK. On the application side, the developed physics-based wireless channel can be integrated with network-level performance metrics to optimize the placement of APs for CBTC systems. Network protocol design can benefit by harnessing a deeper understanding of the underlying physics of electromagnetic propagation in railway environments.

Communication-based train-control (CBTC) systems are aimed at replacing conventional rail signaling with train control enabled by wireless communication between the train and a network of access points. The position of the access points has a significant impact on the performance of such a system. This paper presents an efficient optimization framework of access point placement through combining a site-specific electromagnetic simulator and an optimization algorithm. The aim of this approach is to select an optimal distribution of access points in order to maximize the coverage of the system. To that end, radio-wave propagation is modeled with the vector parabolic equation method, while the optimization of the access point location is pursued via the robust and well-convergent Hooke and Jeeves algorithm. Practical constraints and engineering considerations associated with the deployment of CBTC systems are taken into account. Numerical results are compared with experimental measurements in an actual CBTC deployment site, demonstrating the validity and usefulness of the proposed methodology.

This paper presents an efficient 3-D finite-difference time-domain (FDTD) subgridding scheme that is free of the Courant-Friedrichs-Lewy stability condition, for the modeling of ground-penetrating radar (GPR) scenarios in lossy dispersive media. Spatial filtering of FDTD fields within the subgrid is employed to render the time step independent of the cell size in the fine-cell subgrids. This process is applied with minimal modification of the original FDTD code, no implicit operations, and very modest computational overhead. Moreover, multiterm dispersion is included to model practical GPR scenarios involving the detection of realistic scatterers within dispersive soil. Several numerical examples are provided to demonstrate the potential of the proposed method as a powerful GPR modeling tool.

Waveguide-form multi-beam lens antenna has several shortcomings, such like large size and weight of feed source. According to such situation, a lens antenna applied to high altitude platform is designed. The proposed antenna uses printed Yagi-Uda antenna as feed unit and applies CST MICROWAVE STUDIO® electromagnetic simulation software to analyze. The proposed antenna is manufactured and tested in microwave anechoic chamber. And the simulated and experimental results show that frequency range of the proposed antenna is from 1.77GHz to 2.44GHz with reflection coefficient less than -10dB, relative bandwidth is 31.8%. Antenna gain at 2.1GHz is 9.3dB, which basically accords with the simulated result. Finally, a multi-beam lens antenna fed independently with 6 printed Yagi-Uda antenna units is designed. The proposed antenna has characteristics of wide band, high gain, small volume and light weight. Thus it can be applied in the future high altitude platform communication system.

Because of its parity check matrix has good systematicness, the minimum distance between codes has linear relationship with code length, AR4JA (accumulate-repeat-4-jagged-accumulate) codes is thought to be one of the most suitable error control channel codes for deep space reliable communication in the future. In order to reduce the modified min-sum algorithm decoder hardware implementation complexity of AR4JA codes, a method of constraint about clipping threshold is proposed in the paper, based on the analysis of the effects of modify factor, clipping threshold and input quantization on the performance. The simulation results show that when the modify factor A is 0.75, received signal clipping threshold cth is 4, and use 8Q5 quantization, the decoding performance of the modified min-sum algorithm for AR4JA codes is close to the theoretical value. Meanwhile, in this condition it can reduce the hardware implementation complexity for just need addition, comparison and shift operation, which is beneficial to realize miniaturization of deep space communication receiver.