Unmanned aerial vehicles (UAVs) enable flexible network deployment but are vulnerable to detection due to the open-access nature of wireless signals. Visible light communication (VLC) emerges as a compelling technology for this context, offering inherent covertness through its reliance on line-of-sight links, while its wide spectrum supports high covert transmission rates. However, the high mobility of UAVs creates dynamic channel conditions that challenge traditional multiple access schemes. This motivates the utilization of rate-splitting multiple access (RSMA), a more robust and flexible framework for managing multi-user interference. Therefore, we investigate a cooperative, RSMA-based VLC system where a source UAV provides covert data transmission, assisted by a jamming UAV that creates power randomness to confuse wardens. By jointly optimizing the three-dimensional (3D) trajectory design and resource allocation of UAVs, we aim to maximize the minimum average covert transmission rate of users. To achieve this goal, the original problem is decomposed into three subproblems, namely horizontal coordinate arrangement, altitude adjustment, along with joint power assignment and rate-splitting, which are solved by the successive convex approximation method, geometric programming-based approach, and majorization-minimization algorithm, respectively. Numerical results validate the effectiveness of the proposed approach through extensive simulations under various parameters and comparative analyses against baselines, highlighting the potential of UAV-assisted visible light covert communications.

Radio frequency fingerprint identification (RFFI) aims to identify subtle impairments in hardware devices, which play an important role in the mobile environment security community. To identify various mobile devices in the complex electromagnetic environment, deep learning methods such as convolutional neural networks (CNN) and recurrent neural networks (RNN) have been adopted to extract device hardware-related features. However, the single network structure has difficulty in comprehensive feature extraction, as many factors can introduce hardware impairments. In this paper, we propose a hybrid model termed switching dynamical deep network (SDDN) for RFFI tasks, which can jointly extract both coarse-grained radio frequency fingerprints (RFFs) and fine-grained RFFs. Additionally, the proposed hybrid model consists of a probabilistic part and a deterministic part. Specifically, in the probabilistic part, the switching linear dynamical systems (SLDS) are incorporated to establish the correspondence between the signal slice and the feature extraction network (FEN). In the deterministic part, multiple independent FENs are established to extract the RFFs. Moreover, to automatically determine the suitable number of FENs, a Bayesian nonparametric prior distribution is placed over the probabilistic part. Finally, an end-to-end parameter optimization method that is based on variational inference and stochastic gradient descent is proposed. Experiments on a real-life Wi-Fi dataset demonstrate the superiority of the proposed method over existing methods.

Vehicular fog computing (VFC) offers a promising paradigm to alleviate vehicular computing burdens and ensure timely processing of computing tasks. In this paper, a heterogeneous VFC system leveraging hybrid visible light communication (VLC) and radio frequency (RF) communications is investigated, exploiting the interference resilience of VLC and the extended coverage of RF for efficient task offloading to multiple idle vehicles while harnessing their computing resources for parallel task computing. On this basis, an average task processing delay (TPD) minimization problem is formulated, thereby encompassing task offloading, computing and communication resource allocation for rapid processing of computing tasks. Then, the non-convex problem is decomposed into three subproblems and iteratively solved within a block coordinate descent (BCD) framework. Within this framework, the residual additive majorization-minimization algorithm is employed for task offloading and computing resource allocation, the transformed majorization-minimization method is applied for joint power adjustment of both VLC and RF, and the relaxed optimization and reconstruction approach is developed for subchannel assignment. Comprehensive simulations validate the superiority of the heterogeneous VFC system over local computing and VFC systems relying on VLC or RF, and demonstrate the convergence of the proposed BCD-based algorithm and its superiority over baselines. Additionally, the influence of key parameters on the average TPD is also characterized, providing essential design guidelines for practical implementations.

Covert communications play a crucial role in modern communication systems, ensuring privacy and security in urban environments. Visible light communication (VLC) emerges as a promising technology due to its potential for covert operations within established infrastructures. In this paper, the covert communication for non-orthogonal multiple access (NOMA)-based VLC systems is investigated, by leveraging the assistance of optical intelligent reflecting surface (OIRS).We develope a system model that allows covert user information to be hidden in the public user information, and to disrupt the warden by altering the channel gain through OIRS. Moreover, the problem is formulated to maximize the effective covert spectral efficiency (SE) of the visible light covert communication (VLCC) system with the detection error probability (DEP) and connection outage probability (COP) constraints, and then an optimization framework is proposed to solve the non-convex problem for both multiple-input single-output (MISO) and single-input single-output (SISO) scenarios. For MISO, a block coordinate descent-based optimization algorithm is developed, decomposing the problem into two sub-problems, named power allocation and OIRS configuration sub-problems. For SISO, closed-form solutions for the power ratio relative to OIRS configuration are derived, simplifying the optimization process. Moreover, we analyzed two distinct cases where Willie either possesses or lacks the knowledge of OIRS state, thereby revealing the impact of warden capabilities on covert communications. Furthermore, the effect of imperfect acquisition of Willie’s channel state information is also examined on the effective covert SE. Simulation results demonstrate that the proposed algorithm enhances the effective covert SE of VLCC systems, while exploring the impact of OIRS units number and other key factors. These findings highlight the potential of OIRS to improve the covert performance in future optical communications.

The growth of indoor terminals has put higher demands on wireless communications, which not only need to support high-rate communications, but are also required to provide power for energy-limited terminals. However, conventional wireless communication systems face challenges in meeting these demands due to the spectrum congestion and electromagnetic interference. Recently, visible light communication (VLC) has been emerged as a promising technology, which can take advantage of its ability to operate within the unlicensed spectra. Therefore, in this paper, VLC benefits from the facilitation of optical intelligent reflecting surface (OIRS) and non-orthogonal multiple access (NOMA) to support energy-constrained devices through simultaneous lightwave information and power transfer (SLIPT), which is well suited for future VLC systems. Moreover, an optimization framework is proposed for NOMA-based VLC systems with OIRS for SLIPT, and then the problem is formulated to minimize the total energy consumption with several key constraints. To solve this non-convex problem, we decompose it into four sub-problems, including the OIRS configuration, NOMA coefficient assignment, transmit power allocation, and direct current bias arrangement, which are solved iteratively by the block coordinate descent algorithm through relaxed iterative optimization, minorization-maximization algorithm, and successive convex approximation. Simulation results validate the convergence and effectiveness of the proposed algorithm, demonstrating the influence of OIRS unit number and other key factors on the system performance. These findings highlight the potential of OIRS to enhance the power transfer capabilities of future optical communications.

Low Earth orbit (LEO) satellite communications have received significant attention due to the global coverage and low-latency characteristics. Due to the limited size, weight, and power of LEO satellites, meeting the demand of satellite-terrestrial communications with minimal energy consumption while suppressing interference to co-existing systems remains a significant challenge. In this paper, a LEO satellite architecture with beam hopping (BH) is proposed, where the dynamic resource management and real-time load balancing are jointly implemented. Specifically, an optimization problem for the BH pattern, resource management, and load balancing with multi-satellite collaboration is formulated to achieve the long-term average energy minimization, while suppressing the interference to the co-existing system. Subsequently, by introducing the Lyapunov optimization method, the long-term energy minimization is transformed into a series of dynamic optimization problems for each time slot, thereby ensuring both the energy minimization and queue stability, where the block coordinate descent algorithm is employed to alternately address these issues. In particular, the BH pattern is determined by the multiplier penalty method combined with the majorization-minimization algorithm. Additionally, the resource management is addressed through the successive convex approximation technique, while real-time load balancing is achieved via quadratic programming. Overall, the proposed method, which can be effectively implemented within polynomial time, outperforms other benchmarks in simulations by achieving interference suppression in co-existing systems and reducing the energy consumption, while satisfying the communication demands.

The mega low-Earth-orbit (LEO) satellite constellation can achieve high throughput and low latency satellite communications, which is highlighted for next-generation communications. In this paper, the LEO satellite communications with coordinated beam hopping (BH) are investigated for throughput maximization and load balancing. Generally, the geographically non-uniform and time-varying packet arriving, along with the interference caused by dense beams, can present significant challenges. Hence, the proper BH pattern selection and dynamic power allocation are necessitated to enhance the throughput of satellite-terrestrial communications. Additionally, load balancing via inter-satellite links (ISLs) adjusts the queue length among satellites, thus indirectly altering the throughput by mitigating congestion. Therefore, an optimization problem is formulated to maximize long-term throughput by determining the BH pattern and dynamic power, while the problem for load balancing via ISLs is also proposed for stabilizing queues in a low congestion state to enhance the throughput. As both problems are inherently associated with each other through the queue length, they are solved in cycles. Specifically, the problem for long-term throughput is converted into decisions for each time slot with the Lyapunov drift-plus-penalty method, and then the BH pattern and power allocation are optimized alternately through successive convex approximation. Moreover, load balancing via ISLs is determined according to the queue length by minimizing the upper bound of Lyapunov drift, thereby decreasing the congestion of queues. Simulation results indicate that the proposed method can effectively improve the throughput and reduce the packet loss compared with the existing baselines, demonstrating the effectiveness of the Lyapunov optimization based method.

Beamforming and waveform design are key essentials for integrated sensing and communication (ISAC) in future wireless networks, which also inspires the emerging research of optical wireless ISAC (OW-ISAC). In this paper, we investigate the joint design of optical phased array (OPA) beamforming and orthogonal frequency division multiplexing (OFDM) waveform, thus extending the radio-frequency (RF)-ISAC paradigm to the optical band. First, the system model for the OPA-based OW-ISAC framework is introduced to facilitate simultaneous communication and sensing. Next, signal processing techniques are tailored for an optical OFDM waveform with precisely separated communication and sensing subcarriers. Then, the joint optimization problem of OPA beamforming and OFDM waveform design is formulated, decomposed, and resolved to reach a flexible compromise between communication and sensing performances. Moreover, numerical simulations validate the effectiveness of the proposed OW-ISAC scheme and reveal the trade-off between communication and sensing functionalities. Consequently, the capabilities of reliable communication and precise sensing will establish OW-ISAC as a powerful complement to RF-ISAC in the near future.

With the rising sophistication of cyber threats and the growing reliance on communication infrastructure, ensuring secure transmission has become a critical challenge. This work investigates the visible light covert communication for unmanned aerial vehicle (UAV) systems employing rate-splitting multiple access, aiming to conceal the very presence of transmission. Besides, the optimal detection threshold and detection error probability are derived to assess the covertness quantitatively. Through jointly optimizing the trajectory design and resource allocation, this work is devoted to maximizing the minimum average covert transmission rate (MACTR) among multiple users. Simulation results verify that the proposed algorithm substantially improves the MACTR compared to the baseline and conventional multiple access schemes, highlighting its effectiveness in enhancing the security for UAV systems.

Optical wireless integrated sensing and communication (OW-ISAC) is rapidly advancing as a compelling alternative to its radio-frequency counterpart. In this paper, an OW-ISAC framework utilizing optical phased array (OPA) is presented, which addresses the critical challenge of angle-domain sensing in OW-ISAC by incorporating OPA beamforming. First, a comprehensive system structure is proposed to enable simultaneous optical wireless communication and profile estimation for extended targets, where the interference among different angle grids arises from the omnidirectional detection of photodiode. Then, an interference-cancellation scheme is developed based on OPA beamforming, which is further transformed into the optimization for the observation matrix and subsequently solved by a perturbation-based method. Moreover, the capabilities of concurrent reliable communication and precise sensing are validated through numerical analysis. Furthermore, the trade-off between communication and sensing performance metrics is also unveiled by tuning the optimization threshold, which enhances the practical viability of OW-ISAC.

In this paper, we investigate the optimization of power allocation and optical intelligent reflecting surface (OIRS) configuration for simultaneous lightwave information and power transfer (SLIPT) in non-orthogonal multiple access (NOMA)based visible light communication (VLC) systems, while both the line-of-sight and OIRS-reflected channels are considered. The problem is formulated to minimize the total power consumption of the whole system, which is solved by the minorizationmaximization method and relaxed iterative algorithm under various key constraints. Moreover, simulation results not only show that the proposed algorithm effectively reduces the system energy consumption while satisfying the constraints, but also demonstrate the enhancement of the system by OIRS, which is especially significant at low signal-to-noise ratio conditions.

In this paper, a multi-satellite cooperative beam hopping (BH) scenario in a low Earth orbit (LEO) satellite constellation is studied for satellite-terrestrial communications. Generally, the geographically non-uniform and time-varying packet arrival process, as well as the interference caused by dense beams, presents significant challenges in throughput maximization. To address these issues, an optimization problem is formulated to maximize long-term throughput in a multi-satellite cooperation scenario by determining the BH pattern and dynamic power allocation, while satisfying both peak and average power constraints. Subsequently, the original long-term problem is converted into decisions for each time slot through the Lyapunov drift-plus-penalty method. Moreover, the non-convex problem is solved with the successive convex approximation algorithm. Simulation results indicate that the proposed method can effectively improve throughput compared with the existing baseline, which demonstrates the effectiveness of the proposed method.

In this paper, an optical intelligent reflecting surface (OIRS)-aided visible light positioning (VLP) system that adopt received signal strength (RSS) fingerprint method is proposed to enhance the positioning accuracy. We employ OIRS to improve the minimal RSS difference between neighboring positions in conventional RSS fingerprint-based VLP systems, involving a two-stage positioning scheme where the OIRS is strategically aligned to refine the positioning accuracy. Subsequently, the considered problem is formulated to maximize the minimum Euclidean distance by optimizing the OIRS configuration, which is then solved by an successive convex approximation (SCA)-based algorithm. Moreover, simulation results demonstrate that the proposed OIRS-assisted VLP system substantially outperforms conventional benchmarks, thereby achieving superior positioning accuracy.

In this paper, a novel integrated control and communication (ICC) framework is proposed for vehicle platoons, ensuring platoon stability while optimizing energy consumption for communications. To address the high signaling overhead and long delays caused by multi-link competition in radio-frequency-based vehicle-to-vehicle communications, visible light communications (VLCs) are employed, allowing adjacent vehicles to establish collision-free links and simultaneously transmit motion status information (MSI) for platoon control. Besides, age of information (AoI) is utilized to quantify the heterogeneous timeliness of the MSI. Building upon this, a distributed linear control strategy is designed for vehicle platoons with a multi-predecessor-leader-multi-following information topology (IT) and heterogeneous AoIs. Afterward, through stability analysis, the maximum allowable AoI threshold is obtained to guarantee both internal stability and input-state string stability under external disturbances. Accordingly, taking the AoI threshold as a constraint, a long-term energy minimization problem is further formulated to optimize the energy consumed by multi-source, multi-hop, and multicast intra-platoon VLC while maintaining platoon stability. To solve this problem, an online distributed information scheduling policy based on Lyapunov optimization is proposed. Finally, simulation results reveal that the proposed ICC framework effectively maintains platoon stability across various ITs, while significantly reducing the energy consumption for communications to no more than 40% of that achieved by multiple baselines, thus highlighting its substantial potential in vehicle platoons.

In multicell downlink vehicular visible light communication (VLC) systems, vehicles at a cell edge experience lower achievable data rates compared with those at a cell center, primarily due to the weaker channel gain and intercell interference, leading to unfairness among vehicles. In this article, a cooperative transmission approach is proposed for a vehicular VLC system with optical intelligent reflecting surface (OIRS) to enhance the max-min fairness of the system by leveraging the additional OIRS-reflected channels and the interference-mitigating capabilities of cooperative transmission. To this end, the system model is established, followed by the formulation of a resource allocation problem aiming at enhancing max-min fairness, in which the minimum achievable data rate among vehicles is optimized. Then, an effective resource algorithm is proposed, transforming the original problem into an equivalent form and subsequently decomposing it into three subproblems, focusing on OIRS assignment, subchannel allocation, and power adjustment, respectively. By employing a block coordinate descent algorithm, the three subproblems are solved iteratively until convergence. In addition, simulation results confirm the improvement in max-min fairness brought by OIRS and the proposed cooperative transmission approach. Moreover, compared with various baselines, the proposed resource allocation algorithm significantly enhances in the max-min fairness for the vehicular VLC system, crucial for this application.

Uncrewed aerial vehicles (UAVs) have gained significant attention due to their low cost and efficient deployment. Specifically, UAV-based communications hold promise to supplement the coverage limitations of terrestrial networks and achieve superior connectivity for the Internet of Things (IoT). Moreover, UAVs with visible light communication (VLC) capability do not interfere with existing radio frequency (RF) communication infrastructure, thereby providing flexible, high-throughput on-demand wireless communications. In this article, considering the limited battery capacity of UAVs, we aim to maximize the energy efficiency (EE) of a multi-UAV downlink VLC system for IoT. To this end, the system model with co-channel interference is first established, followed by the formulation of the joint spatial deployment and resource allocation problem. Besides, the original problem is decomposed into three subproblems, focusing on spatial deployment, subchannel assignment, and power allocation. By employing the block coordinate descent (BCD) method, the three subproblems are solved alternately. Moreover, simulation results demonstrate that the proposed method achieves superior improvements in EE compared to other baselines. In addition, the convergence and computational complexity of the proposed algorithm, as well as the impacts of key parameters on the overall system performance are also investigated.

Optical intelligent reflecting surface (OIRS) is a promising technology in visible light communications (VLCs), which can help VLC overcome the shortcoming of being susceptible to occlusion. It is shown that OIRS has many advantages for nonorthogonal multiple access (NOMA)-based VLC due to its ability to reconfigure optical wireless channels. In this article, we propose an effective OIRS-aided physical layer security (PLS) scheme for NOMA-based VLC networks against multiple eavesdroppers (Eves). By exploiting artificial noise (AN) to jam Eves, the maximization problem of the minimum achievable secrecy data rate is investigated, subject to successive interference cancellation (SIC) decoding conditions and OIRS constraints. Specifically, the original problem is decomposed into the power allocation and OIRS configuration subproblems by a block coordinate descent (BCD) algorithm. Moreover, the semi-definite relaxation and successive convex approximation are employed to solve the subproblems, after which a stochastic probability assignment method is adopted for the integer OIRS constraint. Finally, simulation results demonstrate that AN can enhance the system performance in most scenarios, and the minimum achievable secrecy data rate can be significantly improved by the proposed algorithm, demonstrating the potential of OIRS for enhancing PLS in optical wireless communications.

As one of the six usage scenarios of the sixth-generation (6G) mobile communication system, integrated sensing and communication (ISAC) is regarded as a key enabler for the future Internet of Everything (IoE). While numerous studies have been conducted in radio-frequency (RF)-ISAC, free-space optical (FSO)-ISAC is also laying the foundation for the era of connection and intelligence. In this article, a direct-current (DC)-biased optical orthogonal frequency-division multiplexing (DCO-OFDM) scheme is proposed for FSO-ISAC. To derive the performance metrics for communication and sensing, we model the clipping noise of DCO-OFDM as additive colored Gaussian noise and establish an equivalent frequency-selective channel for FSO-ISAC. In addition, joint power allocation problems are formulated for both communication-centric and sensing-centric scenarios based on the derived performance metrics. Subsequently, these nonconvex joint optimization problems are decomposed into subproblems for DC bias and subcarriers, which can be solved by block coordinate descent algorithms. Furthermore, numerical simulations demonstrate the effectiveness of proposed methods and reveal the tradeoff between communication and sensing functionalities of FSO-ISAC based on DCO-OFDM.

Ultraviolet (UV) communication research has prioritized channel modeling for its critical role in system optimization. Current non-line-of-sight (NLoS) UV modeling mainly addresses obstacle-free scenarios and single-obstacle situations: the former manifests constrained applicability at small transceiver elevation angles with obstacle susceptibility, while the latter suffers from high modeling complexity and can only handle one-obstacle scenarios, which pose critical challenges for Internet of Things applications. To overcome these limitations, we propose a single-collision model for short-range NLoS UV channels incorporating both scattering and reflection effects. Initially, the impact of air scattering on the received pulse energy is presented for diverse obstacle situations, where an obstacle-boundary approximation method (OBAM) is developed to reduce the modeling complexity. Besides, the dimensions, coordinates, shapes, orientation angles, and number of obstacles are considered to emulate practical environments. Subsequently, the impact of obstacle reflection on the received pulse energy is investigated for single, double, and multiple obstacle situations. On this basis, we account for certain scenarios where obstacle surfaces comprise multiple sub-regions, each characterized by distinct reflection coefficients attributed to their varying material compositions. Moreover, we verify the proposed model by comparing it with the Monte-Carlo photon-tracing (MCPT) model and the obstacle-free integral model via simulations. These results demonstrate that the path loss curves obtained by the proposed model exhibit close alignment with those simulated by the MCPT model, while its calculation time is less than 10% that of the MCPT model. Additionally, when obstacle reflection is prominent, the assessment error of the proposed OBAM can be ignored in estimating the path loss of NLoS UV channels containing obstacles.

Non-orthogonal multiple access (NOMA)-based visible light communication (VLC) is considered a promising technique for next generation high-speed wireless communications. The emerging optical intelligent reflecting surface (OIRS) offers significant benefits to the NOMA-based VLC, since it can mitigate signal blockage issues of VLC and improve its performance by manipulating channel qualities of users. This paper investigates the enhancement of OIRS to the NOMA-based multi-cell VLC system and explores the resource allocation problem for the energy efficiency (EE) maximization. To this end, the channel gains of the system are discussed, considering both the line-of-sight and OIRS-reflected paths. Then, the system model of NOMA-based VLC is established and the optimization problem is formulated to maximize the overall EE of the system. Next, the original optimization problem is decomposed into three sub-problems, which are solved by the proposed algorithms iteratively. Moreover, the simulation results demonstrate the convergence of the proposed algorithm and the enhancement in EE achieved by OIRS, as well as the influence of key parameters on the system performance, which can offer insights on resource allocation for NOMA-based VLC systems with OIRS.

Optical intelligent reflecting surface (OIRS) has attracted increasing attention due to its capability of overcoming signal blockages in visible light communication (VLC), an emerging technology for the next-generation advanced transceivers. However, current works on OIRS predominantly assume known channel state information (CSI), while its estimation problem has not been studied yet. To bridge such a gap, this paper proposes a new and customized OIRS channel estimation protocol with joint space-time sampling under the alignment-based OIRS channel model. First, we unveil the spatial and temporal coherence characteristics and derive OIRS coherence distance and coherence time in closed form. Next, to achieve dynamic beam alignment for pilot transmission within the coherence time, we propose to tune the rotation angles of the OIRS reflecting elements following a geometric optics-based non-uniform codebook. Then, given the beam alignment within the considered coherence time, a sequential OIRS channel estimation method is proposed, where the OIRS is divided into multiple subarrays based on the coherence distance. The CSI for each subarray is estimated sequentially, followed by a space-time interpolation to retrieve full CSI for other non-aligned transceiver antennas. Numerical results validate our theoretical analyses and demonstrate the efficacy of the proposed OIRS channel estimation protocol as compared to benchmark schemes.

As transceiver elevation angles increase from small to large, existing ultraviolet (UV) non-line-of-sight (NLoS) models encounter two challenges: 1) cannot estimate the channel characteristics of UV NLoS communication scenarios when there exists an obstacle in the overlap volume between the transmitter beam and the receiver field-of-view (FoV), and 2) cannot evaluate the channel path loss for the wide beam and wide FoV scenarios with existing simplified single-scattering path loss models. To address these challenges, a UV NLoS scattering model incorporating an obstacle was investigated, where the obstacle’s orientation angle, coordinates, and geometric dimensions were taken into account to approach actual application environments. Then, a UV NLoS reflection model was developed combined with specific geometric diagrams. Further, a simplified single-scattering path loss model was proposed with a closed-form expression. Finally, the proposed models were validated by comparing them with the Monte-Carlo photon-tracing model, the exact single-scattering model, and the latest simplified single-scattering model. Numerical results show that the path loss curves obtained by the proposed models agree well with those attained by related NLoS models under identical parameter settings, and avoiding obstacles is not always a good option for UV NLoS communications. Moreover, the accuracy of the proposed simplified model is superior to that of the existing simplified model for all kinds of transceiver FoV angles.

Satellite-terrestrial communications based on mega low-Earth orbit (LEO) constellations enable extensive coverage and high data rates. However, the communication performance is significantly impacted by the non-uniform traffic distribution and the substantial interference caused by dense satellites. Therefore, in this paper, a multi-satellite cooperation architecture for satellite-terrestrial communications is proposed in LEO satellite constellations. Specifically, beam hopping (BH) and resource allocation enable a flexible solution for the non-uniform geographical distribution of communications, and are optimized to improve communication performance and avoid both intra- and inter-satellite interference in satellite-terrestrial communications. Moreover, load balancing via inter-satellite link (ISL) is implemented to further enhance the communication performance. Consequently, the overall problem for maximizing the network throughput and ensuring the latency metric is formulated, and then decomposed into three sub-problems: deep reinforcement learning (DRL) based BH scheduling, resource allocation with multi-satellite cooperation, and load balancing via ISLs. Specifically, DRL is utilized to determine the real-time BH pattern, and the resource allocation among beams is implemented by the majorization-minimization algorithm. Furthermore, for varying input traffic loads, different objectives for load balancing are established and solved by quadratic transformation and hybrid block successive approximation algorithm. Simulation results demonstrate that the proposed method outperforms other existing methods. Meanwhile, it obtains an 18.45% improvement in throughput compared with the benchmark without optimization, while the latency metric for satellite-terrestrial communications is also reduced by the proposed method.

Integrated sensing and communication (ISAC) is regarded as one key enabler in the future sixth-generation (6G) mobile communication network. While considerable attention has been paid to radio-frequency (RF)-ISAC, optical wireless (OW)-ISAC is also rapidly developing as a powerful complement to its RF counterpart. In this paper, an enhanced asymmetrically clipped direct-current-biased optical orthogonal frequency division multiplexing (EADO-OFDM) scheme is proposed for flexible waveform design and resource allocation in OW-ISAC. A generalized OW-ISAC framework is first established to describe the working principles of both communication and sensing (C&S). Then, the signal model is introduced for EADO-OFDM, where the Price theorem is adopted to model the colored clipping noise and elicit a generalized frequency-selective channel. In addition, a joint optimization problem of resource allocation for EADO-OFDM is formulated to adaptively balance C&S performance metrics, and the solution to the problem is obtained by the block coordinate descent algorithm. Finally, extensive numerical simulations demonstrate the flexibility of the proposed EADO-OFDM scheme, while the C&S trade-off is also revealed during the resource allocation.

Optical wireless integrated sensing and communication (OW-ISAC) is emerging as a crucial technology to complement and augment its radio-frequency counterpart. In this paper, we propose an optical phased array (OPA)-based OW-ISAC framework to enable concurrent multi-user communication and environment imaging. The optical beamforming and atmospheric propagation are first elaborated to introduce the principles of OPA-based OW-ISAC. In addition, the investigation into the multi-beam property, direct detection scheme, and sensing task of imaging for OW-ISAC yields dedicated signal-to-interference-plus-noise ratio and contrast metrics for communication and sensing sub-systems, respectively. Moreover, the precoding matrices and photodiode orientations are jointly optimized to achieve optimal beamforming. Subsequently, numerical simulations illustrate the relationships between communication and sensing performance metrics. Furthermore, the proposed OW-ISAC scheme is substantiated in a realistic scenario with the optimized beamforming. The demonstrated high-precision sensing and reliable communication capabilities of OPA-based OW-ISAC can serve plentiful future applications in the era of connection and intelligence.

Optical intelligent reflecting surface (OIRS) has been considered a promising technology for visible light communication (VLC) by constructing visual line-of-sight propagation paths to address the signal blockage issue. However, the existing works on OIRSs are mostly based on perfect channel state information (CSI), whose acquisition appears to be challenging due to the passive nature of the OIRS. To tackle this challenge, this paper proposes a customized channel estimation algorithm for OIRSs. Specifically, we first unveil the OIRS spatial coherence characteristics and derive the coherence distance in closed form. Based on this property, a spatial sampling-based algorithm is proposed to estimate the OIRS-reflected channel, by dividing the OIRS into multiple subarrays based on the coherence distance and sequentially estimating their associated CSI, followed by an interpolation to retrieve the full CSI. Simulation results validate the derived OIRS spatial coherence and demonstrate the efficacy of the proposed OIRS channel estimation algorithm.

Considering that optical intelligent reflecting surface (OIRS) can change the optical channel, the enhancement performance of OIRS on the energy efficiency (EE) of the non-orthogonal multiple access (NOMA)-based visible light communication (VLC) system is investigated. Specifically, a multi-cell VLC system is modelled with both line-of-sight (LoS) and OIRS-reflected paths, and then the problem is formulated to optimize the OIRS configuration and power allocation for the maximization of the overall EE while adhering to various constraints. Moreover, the original task is decomposed into two sub-problems, and is solved iteratively by the proposed algorithm. In addition, the convergence of the proposed algorithm and enhancement in EE achieved by OIRS are illustrated by simulation results, which offer beneficial insights on resource allocation for the NOMAbased VLC systems with OIRS.

In this paper, a multi-satellite cooperation architecture for satellite-terrestrial communications is studied with the dense constellation of low Earth orbit (LEO) satellites. Moreover, beam hopping (BH) and frequency allocation enable a flexible solution for the non-uniform geographical distribution of communications, which are optimized to improve the performance and avoid interference in satellite-terrestrial communications. The total problem for maximizing the networking throughput and ensuring the delay fairness is decomposed into two sub-problems, in which the deep reinforcement learning is utilized to determine the BH pattern, and the frequency allocation among beams is implemented by the majorization-minimization algorithm. Simulation results demonstrate that the proposed method obtains a 13.0% improvement in throughput compared with the original benchmark, while the delay fairness can be ensured by the iterative solution of the two sub-problems.

Integrated sensing and communication (ISAC) is regarded as a key enabler in the upcoming era of connectivity and intelligence, where the optical spectrum emerges as a promising candidate for ISAC. This paper presents an optical wireless (OW)-ISAC scheme based on asymmetrically clipped direct-current-biased optical orthogonal frequency division multiplexing (ADO-OFDM). The Bussgang theorem is adopted to model the clipped OFDM signal and analyze the clipping noise. In addition, the adaptive resource allocation for ADO-OFDM is formulated as a joint optimization problem, which is decomposed into two sub-problems for DC-biased optical (DCO)asymmetrically clipped optical (ACO) power distribution and subcarrier power allocation. Then, the optimal resource allocation can be achieved by iteratively solving these sub-problems. Consequently, numerical results demonstrate the effectiveness of the proposed ADO-OFDM scheme and reveal the trade-off between communication and sensing functionalities in OW-ISAC.

Existing studies on ultraviolet (UV) non-line-of-sight (NLoS) channel modeling primarily focus on scenarios without any obstacle, which makes them unsuitable for small transceiver elevation angles in most cases. To address this issue, a UV NLoS channel model incorporating an obstacle was investigated in this paper, where the impacts of atmospheric scattering and obstacle reflection on UV signals were both taken into account. To validate the proposed model, we compared it to the related Monte-Carlo photon-tracing (MCPT) model that had been verified by outdoor experiments. Numerical results manifest that the path loss curves obtained by the proposed model agree well with those determined by the MCPT model, while its computation complexity is lower than that of the MCPT model. This work discloses that obstacle reflection can effectively reduce the channel path loss of UV NLoS communication systems.

Motivated by the ability of optical intelligent reflective surface (OIRS) to alter optical channels, the effectiveness of OIRS on aggregated visible light communication (VLC)-radio frequency (RF) systems is explored, and the system model is established in detail. With the aim of improving the energy efficiency (EE) of the aggregated system with OIRS, the EE maximization problem is formulated with diverse constraints, followed by the proposed block coordinate descent (BCD)-based resource allocation algorithm. Particularly, the EE maximization problem is partitioned into two subproblems, which are OIRS configuration and joint power allocation, and then are solved in the iteration process. Additionally, the substantial enhancement in EE brought by OIRS for the aggregated VLC-RF system, as well as the convergence and efficacy of the proposed BCD-based algorithm are demonstrated by comprehensive simulation results.

Optical intelligent reflecting surfaces (OIRS) can be deployed in visible light communication (VLC) systems to provide OIRS-reflected paths for multiple light-emitting diodes (LEDs) and users via adjustable reflective characteristics, thereby significantly mitigating the signal blockage challenges in VLC. To achieve this goal, the effectiveness of OIRS in the non-orthogonal multiple access (NOMA)-based multiple-input single-output (MISO) VLC system is explored, while the system model is established considering both the line-of-sight (LoS) and the OIRS-reflected paths. Subsequently, the problem is formulated with the objective of optimizing the OIRS configuration to maximize the achievable sum data rate with the diverse constraints. To address the highly intractable and non-convex problem, a relaxed iterative optimization algorithm based on the Taylor expansion is proposed in this paper. Moreover, numerical results are provided to show the improvement of the achievable sum data rate and the effects of the proposed relaxed iterative algorithm.

The scheduling of the laser inter-satellite links (LISLs) can effectively improve the network performance but is challenging in mega-constellations due to the large amount of satellites. In this paper, inter-OP LISL scheduling is realized by federated reinforcement learning, which reduces complexity by decomposing global scheduling into independent decisions for each satellite and solved by multi-agent reinforcement learning. Based on the constellations collaboration, federated learning (FL) with partial and global aggregations is utilized to reduce the overhead for the model update, where the geostationary orbit (GEO)-GEO collaboration for global aggregation can be performed infrequently since the indirect associations among the GEO satellites according to the motion of low Earth orbit (LEO) satellite. Meanwhile, simulation results indicate that the proposed method reduces the average hop count by over two hops and decreases the number of LISLs by over 25% compared to the fixed LISLs, and the model update overhead is reduced to 46.6% of that in the centralized method.

Integrated sensing and communication (ISAC) is one of the six usage scenarios of the sixth generation (6G) mobile communication system. Since an optical system can also provide communication and sensing abilities, optical ISAC has become a potential complement to radio-frequency (RF) ISAC. As orthogonal frequency division multiplexing (OFDM) has gained increasing interest in optical systems, we propose a direct-current-biased optical OFDM (DCO-OFDM) scheme for free space optical (FSO) ISAC in this paper. To derive the spectral efficiency for communication and the Fisher information for sensing, we model the clipping noise of DCO-OFDM with the Bussgang theorem to obtain the expression of the signal-to-noise ratio. In addition, based on the derived performance metrics, an optimization problem for power allocation is formulated, and an iterative algorithm is proposed to solve the problem efficiently. Meanwhile, numerical simulations demonstrate the effectiveness of the proposed algorithm and reveal the trade-off between communication and sensing functionalities of the OFDM-based FSO-ISAC system.

The burgeoning technology of optical intelligent reflecting surfaces (OIRS) offers significant potential within the realm of visible light communication (VLC) systems. This is primarily attributed to the capability of OIRS to exploit reflected propagation paths, which in turn mitigates the inherent signal blockage challenges encountered in VLC. In this paper, a non-orthogonal multiple access (NOMA)-based multiple-input single-output (MISO) VLC system with the aid of OIRS is investigated, in which multiple light-emitting diodes (LEDs) serve multiple users equipped with a photodetector (PD) simultaneously. To this end, an analysis of the VLC channel gains is undertaken, encompassing the evaluation of both the line-of-sight (LoS) and the OIRS-reflected paths. Subsequently, the problem is formulated with the objective of jointly optimizing the active beamforming at LEDs and the passive beamforming at the OIRS to maximize the achievable sum data rate, while considering the constraints of OIRS and the successive interference cancellation (SIC) process. However, the formulated problem is non-convex. To address this challenge, a block coordinate descent (BCD) algorithm is introduced to decompose the original joint beamforming problem into two sub-problems. Specifically, relaxed iterative algorithms based on semi-positive definite relaxation and Taylor expansion are employed to solve these sub-problems. Additionally, a permutation-based genetic algorithm is proposed to tackle the decoding order problem. Meanwhile, the simulation results illustrate the improvement in the sum data rate achieved by the proposed algorithm, providing valuable insights for future research on OIRS-aided VLC systems.

The promising visible light communication (VLC) technology, which performs superior for Internet of Things (IoT) networks, can alleviate the spectrum congestion of current radio frequency communications. To overcome the drawbacks of VLC such as blockages and high path loss, we propose a multiple-input single-output (MISO) VLC system equipped with optical intelligent reflecting surface (OIRS), to maximize the asymptotic capacity in the high signal-to-noise-ratio regime. Specifically, the characteristics of the OIRS-reflected channel are discussed for the developed OIRS-assisted MISO VLC system, based on which the OIRS optimization can be transformed into an association problem between the OIRS reflecting elements and the transmitter antennas. Next, considering different emission power on antennas, the capacity lower and upper bounds are derived for three different cases and the asymptotic capacities are obtained accordingly, thus giving rise to the objective function of the capacity maximization problem. To solve this problem, we propose a priori-assisted alternating optimization algorithm to jointly optimize the OIRS element alignment and transmitter emission power, which not only can achieve the globally optimal result but also has a low complexity since the solution to each subproblem is given in closed form. Finally, extensive numerical results are provided to show the performance of the proposed algorithm and offer beneficial insights for the design of the proposed OIRS-assisted MISO VLC.

Laser inter-satellite links (LISLs) have greatly extended communication distance between satellites, allowing for establishment of dynamic links to reduce communication delay. However, a closed-loop control is required for LISL, which causes high energy consumption. Proper scheduling of dynamic LISLs can effectively reduce energy consumption and communication delay. In this study, a satellite link mode with three fixed LISLs and one dynamic LISL is designed, and its feasibility is analyzed. The optimization problem is formulated and transformed into a Markov decision process (MDP) by modeling it as a sequential decision. By decomposing states, actions, and reward functions, the MDP is divided into the proposed multi-agent deep reinforcement learning (MADRL). Moreover, compressed sensing is utilized to cut down state information to reduce communication, storage, and computation overhead. Furthermore, network parameters and experience sharing, and prioritized experience replay have been adopted to improve stability and convergence speed of network training with a large number of agents. Experimental results show that under different routing strategies, the proposed MADRL can reduce energy consumption by over 15% and delay by approximately two hops compared to fixed LISLs scenario within several iterations.

Intelligent reflecting surface (IRS) alters the wireless channel by dynamically adjusting the propagation of wireless signals, thereby having the ability to enhance communication performance. Due to its low power consumption, IRS is expected to play an important role in improving energy efficiency (EE). In this paper, both optical IRS (OIRS) and radio frequency (RF) IRS are employed to assist aggregated visible light communication (VLC)-RF systems, and then a resource allocation algorithm is proposed to improve EE. To this end, a model for the IRS-assisted aggregated VLC-RF system is first established, followed by the formulated EE maximization problem. Furthermore, the EE maximization problem is decomposed into four subproblems, focusing on RF IRS configuration, optical subchannel assignment, OIRS arrangement, and joint power allocation. By employing block coordinate descent (BCD), the four subproblems are solved iteratively. Moreover, simulation results show the significant EE improvement brought by the IRS for aggregated VLC-RF systems. In addition, the convergence and effectiveness of the proposed BCD-based resource allocation algorithm, as well as the influence of key system parameters on EE are also demonstrated.

Although the multi-antenna or so-called multiple-input multiple-output (MIMO) transmission is an enabling technology for past generations of wireless communication systems, its application to visible light communication (VLC) still faces a critical challenge due to the strong spatial correlation of VLC channels, which makes it difficult to achieve sufficient spatial multiplexing gain. This paper proposes to use optical intelligent reflecting surfaces (OIRS) to tackle this challenge. Firstly, we characterize the extremely near-field channel condition in the optical frequency range and reveal a peculiar “inter-element interference (IEI) free” property of the OIRS-reflected channel, where the OIRS reflecting elements can be individually configured to align with one pair of transmitter and receiver antennas without causing interference to each other. Next, we characterize the OIRS-assisted MIMO VLC capacities under different power constraints at the transmitter antennas, and then proceed to maximize them by jointly optimizing the OIRS element alignment and transmitter emission power. In particular, we propose two algorithms for the OIRS optimization, namely, location-aided interior-point algorithm and log-det-based alternating optimization algorithm, to balance the performance versus complexity trade-off; while the optimal transmitter emission power is derived in closed form. Numerical results are provided to validate the capacity improvement of OIRS-assisted MIMO VLC against the VLC without OIRS and demonstrate the superior performance of the proposed algorithms compared to baseline schemes.

The scheduling of the laser inter-satellite links (LISLs) can effectively decrease the energy consumption by deactivating idle LISLs and reduce the network latency by decreasing the average hop count through establishing appropriate dynamic LISLs, but is challenging in mega-constellations due to a large amount of satellites involved. In this paper, a federated multi-agent deep reinforcement learning (MADRL) method for LISL scheduling is proposed, where the global scheduling is decomposed into independent decisions for each satellite. To reduce the substantial communication overhead attributable to MADRL, asynchronous hierarchical federated learning with partial and global aggregations is utilized, transmitting the model parameters rather than status information among low Earth orbit (LEO) satellites and geostationary Earth orbit (GEO) satellites. The movement of LEO satellites maintains the consistency of local sample distribution and the indirect association among different GEO satellites. Therefore, the global aggregation with infrequent occurrence is asynchronous with the partial aggregation. Moreover, during the partial aggregation, the utility of each layer in the local model of the LEO satellite is also evaluated to minimize the uncertainty, allowing the adaptive upload to ensure efficiency and fairness within a limited power budget. The simulation results show that the proposed method reduces the average hop by about two hops and decreases the LISLs number by over 25%. Meanwhile, the communication overhead of LEO satellites is 46.6% of that in the centralized approach, with the training performance ensured.

The existing works on ultraviolet (UV) channel modeling primarily focus on non-line-of-sight (NLoS) communication scenarios, where the UV transceiver does not need to be aligned and can communicate around obstacles. However, NLoS scenarios also face problems such as long channel delay spread and severe path loss, and consequently, these phenomena will be exacerbated as the amount and dimension of obstacles increase. To tackle these problems, we investigate the channel models for UV diffused line-of-sight (LoS) communication scenarios comprehensively. First, a UV diffused-LoS channel model with an obstacle is put forward, where the radiation intensity distributions of UV light sources, the height difference between UV transceivers, as well as the obstacle dimension and orientation are incorporated to approach practical application scenarios. Besides, the channel modeling framework for diffused-LoS scenarios incorporating obstacles is investigated, where we take two obstacles as an example to illustrate the entire modeling process. Further, we validate the proposed models by comparing them with associated LoS and Monte-Carlo photon-tracing (MCPT) models via numerical calculations. The path loss results manifest that the proposed integration models agree well with the existing channel models, while their calculation time is much shorter than that of the MCPT model. Apart from that, the channel path loss and bit-error rate performance of diffused-LoS scenarios are superior to those of NLoS scenarios when obstacle reflection is apparent, and channel delay spreads of diffused-LoS scenarios are shorter than those of NLoS scenarios regardless of circumstances with one or two obstacles.

Laser inter-satellite links (LISLs) enable longer-range communication and cross-satellite dynamic links that bypass intermediate satellites. However, the utilization of narrow laser beams necessitates closed-loop control for alignment and consumes substantial energy even during idle periods. Therefore, we propose a dynamic LISL scheduling algorithm and a satellite link pattern with one dynamic LISL and three fixed LISLs to optimize energy consumption and reduce communication delay. To simplify the computation complexity of the optimization problem, a Markov decision process (MDP) is constructed, and the problem is divided into the independent decision process of each agent by breaking down the state space, action space, and reward function. Experimental results indicate that the proposed method reduces communication delay by approximately 2 hops and saves over 15% of energy consumption compared to fixed link patterns.

The non-orthogonal multiple access (NOMA) method is seen as one of the advantageous strategies for radio access that promises improved spectral efficiency in the fifth generation mobile networks (5G). This paper proposes an integrated broadcast and communication networks architecture based on NOMA, in which the physical channels of the cellular base stations are divided into two layers: one layer brings reinforced broadcast signals to the weakest areas of the broadcast tower and forms a single-frequency network transmission with it; the other layer provides diverse unicast services to users. In order to evaluate the spectral efficiency and coverage performance of the above system, an optimization problem based on the integrated spectrum revenue of the system is proposed. To maximize the objective function, the power allocation factors of the cellular base stations are optimized using the genetic algorithm. The simulation results validated that the system architecture is capable of integrating broadcast towers and cellular base stations to provide more reliable coverage of broadcast service and improve spectrum efficiency.

In air-water wireless optical communication, the optical signal may be completely reflected at the sea surface, which will cause signal interruption and seriously affect communication quality. Therefore, this paper analyzes the signal interruption probability and duration caused by total reflection at different wind speeds and transmitter inclination angles. The bit error rate (BER) of L-ary pulse position modulation (L-PPM) across sea surface under different L values is studied in an attempt to find a suitable modulation method to optimize the BER of the system. The BER optimization effect is apparent when the wind speed is low and L=6. However, the optimization effect of L-PPM on BER decreases with the increase in wind speed.

Due to the wide and license-free bandwidth, visible light communication (VLC) functions as a potential technology to meet the exponentially expanding traffic demands in wireless communications. However, the sensitivity to obstacles and high-path loss are the key issues that practical VLC systems must carefully deal with. In this article, the utilization of optical intelligent reflecting surface (OIRS) array in VLC is considered to create additional light propagation paths, thereby achieving a remarkable performance gain. In the OIRS-assisted VLC system, though the power of the signal at receiver can be increased, the resource allocation is relatively complex. Besides, the OIRS also causes time delays among signals received via various propagation paths, which is usually overlooked in existing works. To overcome these issues, the OIRS-assisted VLC system is interpreted as an autoencoder (AE), named OIRS-AE, whose architecture is enhanced according to both the model-driven and data-driven perspectives. By this way, the processing modules at the transmitter, OIRS, and receiver, including the corresponding encoding, resource management, and decoding schemes, can be simultaneously optimized, which is expected to achieve more reliable communication. Moreover, the impact of the OIRS-induced time delay spread on system performance is explored under various situations. The simulation results show that the proposed OIRS-AE can outperform the traditional OIRS-assisted VLC systems in terms of bit error rate performance.

With the capability of reconfiguring the wireless electromagnetic environment, intelligent reflecting surface (IRS) becomes a new paradigm for designing future wireless communication systems. In this paper, we consider optical IRS for improving the performance of visible light communication (VLC) under a multiple-input and multiple-output (MIMO) setting, where the mean square error (MSE) of the IRS-aided MIMO VLC is minimized by jointly designing the IRS and transceiver signal processing. To this end, the MIMO channel gains of the IRS-aided VLC are first derived under the point source assumption, based on which the MSE minimization problem is formulated subject to the emission power constraints and the IRS configuration constraints. Next, we propose an alternating optimization algorithm, which decomposes the original problem into three subproblems, to iteratively optimize the IRS configuration, the precoding and detection matrices for minimizing the MSE. Moreover, theoretical analysis on the performance of the proposed algorithm in high and low signal-to-noise ratio (SNR) regimes is investigated, revealing that the joint optimization process can be simplified in such special cases, and the algorithm’s convergence property and computational complexity are also discussed. Finally, numerical results show that IRS-aided schemes significantly reduce the MSE as compared to their counterparts without IRS, and the proposed algorithm outperforms other baseline schemes.

With the explosive growth of the data traffic and the access number of intelligent devices, the wireless communication systems based on the radio frequency (RF) is suffering from the pressure of spectrum shortage and access congestion constantly, which can be alleviated with the help of visible light communication (VLC). However, due to the limitations of VLC such as finite coverage and inconvenient uplinks, it is imperative to form the hybrid systems and realize the complementary advantages of VLC and RF. In this paper, the hybrid VLC-RF system with multi-users is investigated, where the sum achievable rate and energy efficiency (EE) are maximized via the alternate optimization of transceiver association and power allocation. In addition, based on various types of multiple access points, EE is optimized under different QoS requirements for green communications. With the assistance of proper approximations, the overall problem is decomposed into several convex sub-problems, which can be solved analytically and avoid traversal permutation. The numerical simulations show the effectiveness and scalability of the proposed algorithm in the hybrid VLC-RF system, which can achieve superior performances than the conventional methods and single systems in multifarious scenarios.

Compared with underwater acoustic communication, underwater wireless optical communication (UWOC) has the advantages of wide communication bandwidth, high transmission speed and strong directional transmission, which make it have broad application prospects. However, the absorption and scattering effects in underwater environments cause a UWOC system to suffer from severe channel fading. To reduce the system complexity and power loss, the on- -off-keying (OOK) modulation scheme and one-bit analog-to-digital converter are considered in this work. Besides, to deal with the complex underwater optical channels and the nonlinearity of the one-bit quantization, a novel deep learning based architecture integrating the autoencoder (AE) and generative adversarial network (GAN), named hybrid AE-GAN, is developed. In the proposed hybrid AE-GAN, the generator in GAN is responsible for a generalized channel equalization, which aims to equalize both the impairments from underwater optical channels and the distortion from one-bit quantization. While the decoder in AE and the discriminator in GAN share the same network to distinguish true and fake as well as reconstruct the sent messages simultaneously. Meanwhile, the one-bit quantized signal is regarded as conditional information for GAN to assist in targeted channel equalization for various signals. Moreover, a specialized loss function and training strategy for the hybrid AE-GAN are also presented, which can optimize AE and GAN at the same time, and deal with the problem that the binarization of OOK stymies the gradient backpropagation. The simulation results indicate that the proposed hybrid AE-GAN can achieve superior performance.

Visible light communication (VLC) is one of the candidates to realize data rates of up to tera-bps in indoor scenarios, and is a popular topic in Internet of Things (IoT) applications. However, the receiving performance of the VLC channel is affected by relative locations of transceivers directly, while the uniform illumination is also required when the IoT devices can appear anywhere with strong mobility. Consequently, both the illumination uniformity and the average achievable rate are optimized by joint lamp arrangement and power allocation in this article. Moreover, the achievable rate maximization under diverse uniformity constraints is also obtained based on different room sizes and various numbers of lamps. The feasibility and superiority of the proposed algorithms are demonstrated by simulation validations, while the lower and upper bounds of uniformity constraints are explored. Numerical results also show the changing tendency of average achievable rates in multifarious situations, and the proposed schemes realize the tradeoff between uniform illumination and communication performance.

Though visible light communication (VLC) is a significant supplement to current communication technologies, disadvantages such as the sensitivity to obstacles limit its development and commercialization. As a revolutionizing technology, intelligent reflecting surface (IRS) offers an ability to reconfigure the wireless environment dynamically and passively, which is considered beneficial to improve the performance of VLC. This paper devotes to investigating the effect of VLC IRS and putting forward a joint resource management method for an instantaneous IRS-aided VLC system. To this end, the line-of-sight (LoS) and non-LoS channel gains are first discussed under the point source assumption, after which the system model is established and the optimization problem is formulated. Then, the frozen variable algorithm and minorization-maximization algorithm are proposed to iteratively maximize the overall spectral efficiency (SE), and detailed discussions on the weak/severe interference cases and computational complexity analysis are carried out. Moreover, numerical results are provided to show the improvement of SE and the effects of the proposed algorithms, which offers beneficial insights on joint resource management of IRS-aided VLC.

As a high-speed, large-capacity underwater communication technology, underwater wireless optical communication (UWOC) has broad development prospects. However, accurately characterizing the underwater optical channel for various underwater conditions is still a challenging task due to light absorption and scattering, which may limit further research on UWOC. To overcome these issues, this paper proposes a novel framework of the underwater optical channel impulse response (CIR) generator, named the UCIRG framework, based on the generative adversarial network. Unlike the classical Monte Carlo approach, which is a numerical simulation method taking a long time to calculate, the UCIRG framework can generate a large number of CIRs extremely close to the actual underwater optical CIRs in a short time based on limited underwater optical CIRs as training data. Besides, traditional approximation methods for underwater optical channels usually have limitations on underwater conditions, lacking generality and flexibility, hence a generalized algorithm for UCIRG is also investigated, which is valid for various underwater conditions and can further reduce training time. Moreover, the multi-carrier autoencoder based UWOC system is adopted to evaluate the performance of the trained UCIRG, and the simulation results prove that the CIRs generated by the UCIRG are extremely similar to the actual CIRs.

Facing the worldwide explosive growth of the wireless devices, the future wireless network is required to provide seamless access for the users with diverse Quality-of-Service (QoS) requirements. In this article, a novel multiple access scheme based on the principle of multidomain index modulation is proposed to address the downlink multiple access problem for users with diverse QoS requirements, including the Internet-of-Things (IoT) devices and the smart electronic devices. Unlike the conventional nonorthogonal multiple access (NOMA) schemes which utilize power-domain diversities to realize multiple access, in the proposed scheme, information for different users is conveyed by different domains of the transmitted signals, including the constellation domain, frequency domain, time domain, and spatial domain. As a result, the intracluster interference among users is alleviated and the successive interference cancellation is avoided to reduce the computational complexity of signal detection at the receiver side, which is well suited for the IoT devices. The closed form lower bounds and approximations of the achievable rate of the proposed scheme are further derived to provide accurate estimation of the achievable rate of the communication system. Simulation results validate the superior performance of the proposed scheme over the conventional orthogonal and NOMA schemes.

Visible light communication (VLC) has gradually gained increasing attention in recent years, but new researches are still needed for conventional technologies in the VLC system, as the visible light signal must be real-valued and non-negative, and it is transmitted over the specific ergodic channel. In this paper, the definition of ergodic optical channel is firstly proposed, and the coded modulation average mutual information (CMAMI) of the VLC system is investigated under both fixed and ergodic optical channels. The gradient descent (GD) algorithm for constellation optimization of amplitude-phase modulation (APM) symbols is adopted, while the improved method for GD based on central symmetry is also proposed to accelerate the convergence for higher order constellations. The numerical simulation proves that the VLC system with optimized constellations can reach larger CM-AMI based on asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) compared with quadrature amplitude modulation (QAM) systems, and the influence of the ergodic optical channel is also evaluated.

In this paper, a novel index modulation aided non-orthogonal multiple access (NOMA) scheme is proposed for visible light communication (VLC). Unlike the conventional NOMA schemes, the proposed scheme conveys information for different users through both the index-domain and constellation-domain symbols with the aid of index modulation, which is able to cancel the intra-cluster interference completely and avoid the use of successive interference cancellation to decrease computational complexity. The achievable multi-user sum rate of the proposed scheme is analyzed and a closed-form expression of the lower bound is derived. Then, an approximation is further obtained to realize accurate prediction of the achievable multi-user sum rate. Simulation results validate the accuracy of the approximation of the achievable sum rate and the superior performance of the proposed scheme.

In this paper, an enhanced asymmetrically clipped DC biased optical OFDM (ADO-OFDM) with adaptive subcarrier allocation is proposed to accommodate the requirements of multi-users in downlink multiple access. The optimal optical power allocation is investigated to minimize the overall bit error rate (BER). Moreover, to meet the dimming demands for illumination, enhanced negative ADO-OFDM is investigated and combined with enhanced ADO-OFDM for multiplexing transmission. Furthermore, a dimming control scheme is proposed by changing the proportion of these two signals to a proper value, with full using of the entire dynamic range of light-emitting diodes. Simulation results show that the proposed scheme can achieve better BER performance at the same signal to noise ratio, while wide dimming range for illumination can be ensured compared to the conventional counterparts.

Recently, the index modulation technique is introduced into the visible light communication (VLC) system to convey information bits in a more energy-efficient and spectral-efficient way. However, in practice, the index modulation aided VLC system should be carefully designed to be compatible with dimming control. In this paper, a novel hybrid dimming scheme is proposed for the index modulation aided VLC system, which combines the frequency-domain and time-domain dimming strategies to maximize the channel capacity and maintain the desired illumination level. Simulation results validate the superior performance of the proposed hybrid dimming scheme.

Several recent studies have been conducted on solving the compressive sensing problem with deep learning framework , which enhance the signal recovery performance and greatly shorten the running time compared with traditional algorithms. However, as the size of signals increases, so does the neural network, which will impose large memory space and high computational complexity, making it hard to use this method on mobile devices. To address this issue, in this paper, the neural network is decomposed by Tensor-Train (TT) format, which reduces the number of parameters to a great extent. In particular, the neural network decomposed by TT format is a stacked denoising autoencoder (SDA) network, which called TT-SDA. The experiments demonstrate that, especially with low measurement rates, the proposed TT-SDA network can improve the reconstruction results, reduce the computational complexity and save the memory space.

Utilizing the illuminating light-emitting diode (LED) for signal transmission, the visible light communication (VLC) offloads the congested traffic in licensed spectrum while providing users with high quality of service. However, in shaded areas, the performance of VLC is affected. In this paper, we apply Device-to-Device (D2D) technology on the VLC network, where some mobile users are able to relay the data transmission to nearby end mobile users. Considering the autonomous behaviors of mobile users as relays (RUs), cellular service provider (CSP) and VLC service provider (VLCSP), we propose a hierarchical game framework and analyze the distributive strategies for each individual. In the game, the data packet size, the price of licensed spectrum and data rates in possible data transmission routes are sequentially determined with equilibrium solutions, and each VLC transmitter (VLCT) determines the optimal data transmission route with stable matching. Simulations depict the high performance when combining VLC and D2D with the proposed strategies.

The radio frequency spectrum crunch has triggered the harnessing of other sources of bandwidth, for which visible light is a promising candidate. Even though visible light communication (VLC) ensures high capacity, coverage is limited. This necessitates the integration of VLC and device-to-device (D2D) technologies into heterogeneous networks. In particular, mobile users which are accessible by the VLC transmitters can relay data to mobile users which are not, by means of D2D communication. However, due to the distributed behaviors of mobile users, determining optimal data transmission routes from VLC transmitters to end mobile devices is a major challenge. In this paper, we propose a reinforcement learning (RL)-based approach to determine multi-hop data transmission routes in an indoor VLC-D2D heterogeneous network. We obtain the rewards for the RL-based method dynamically, by formulating the interactions between the mobile users relaying the data as an equilibrium problem with equilibrium constraints and using alternating direction method of multipliers to solve it. The proposed technique can achieve optimal data transmission routes in a distributed manner. The simulation results demonstrate the effectiveness of the proposed approach, showing that transmission routes with low delays and high capacities can be achieved through the learning algorithm.

Visible light communication (VLC) is regarded as one of the promising candidate to complement the conventional radio frequency communication as it can potentially perform communication and illumination simultaneously. Recently, VLC is combined with generalized spatial modulation (GenSM) technology to improve spectral and energy efficiencies. In order to provide high speed communication and flexible dimming control simultaneously, in this paper, a spectral-efficient GenSM based hybrid dimming scheme, which combines the spatial-domain and time- domain dimming strategies, is proposed for VLC. The channel capacity of the proposed scheme is analyzed and a closed-form expression of the upper bound of the channel capacity is derived. According to the required illumination level, the spatial-domain and time-domain strategies are realized based on the maximization of the channel capacity. Simulation results substantiate the superior performance of the proposed dimming scheme over state-of-art dimming schemes.

As the underwater applications require reliable, fast and efficient communications, the underwater visible light communication (VLC) is attracting more and more attention. Due to the complicated channel condition of the underwater environment, accurate channel estimation is still challenging for underwater VLC systems. This paper investigates the underwater VLC channel estimation problem by following two main assumptions. Firstly, the number of the channel paths is assumed to be much smaller than the channel length, which will obtain the sparsity property in the distance domain. Secondly, the attenuation coefficient is assumed to be approximately linear with the frequency, which is true when the modulation bandwidth is much more narrow compared with the carrier frequency. The compressive sensing (CS) framework is formulated based on the two assumptions, whose sensing matrix has a large coherence. In this condition, the Bayesian CS algorithm is adopted instead of the conventional schemes, and the subspace scheme is also investigated for comparison. The simulation results demonstrate that the proposed scheme outperforms the conventional ones in terms of mean square error (MSE), hence better system performance can be expected.

In this paper, a dimming control scheme is proposed for visible light communication (VLC) based on layered asymmetrically clipped optical OFDM (LACO-OFDM) to satisfy different illumination requirements. The proposed scheme combines LACO-OFDM and negative LACO- OFDM (NLACO-OFDM), which is firstly introduced to the best of our knowledge, where the proportion of the two signals is variable to achieve the desired luminance. Moreover, the dynamic range is fully exploited by both LACO-OFDM and NLACO-OFDM, resulting in high channel capacity. Simulation results show that the proposed scheme has superior performance than the previous scheme based on LACO-OFDM in terms of power and spectral efficiencies.

Recently, mobile social networks (MSNs) has been playing an increasingly large proportion in people's daily life, and consequently attracted enormous amount of researches in this area, including network data collection, user behavior analysis and so on. Many of them are based on the community structure of the MSNs, the detection of which has attracted academic attention. In this paper, we propose an inter-community detection scheme under the framework of the emerging compressive sensing (CS) over graphs. Firstly, we extract the social structure among users by calculating the probability of two users encountering with each other. Then, the proposed scheme utilizes the encounter probability and the edge-clustering coefficient to define a novel additive property to make the CS algorithm applicable. Simulation results demonstrate that the proposed detection scheme can detect inter- community links more accurately than the conventional random walk based method.

Recently, the technique of multiple input multiple output (MIMO) is becoming more and more widespread in the communication systems in order to significantly improve the system capacity. The channel estimation is still one of the most tricky problems because of the large amount of coefficients to be estimated for one receive antenna. This paper focuses on designing and optimizing the time-domain training sequences for MIMO systems and proposes a novel sparse channel estimation scheme taking advantage of the spatial correlation among both the transmit antennas and the receive antennas. The structured compressive sensing (SCS) framework is set up, which is the main approach to recover the sparse channel for different antennas. It is illustrated in the simulation results that the proposed scheme has a higher probability to recovery the nonzero support of the channel than that of the traditional schemes, while the mean square error is also smaller, which means our scheme is expected to have a superior performance.

As a cluster between Internet of Things (IoT) and mobile social networks (MSNs), social IoT allows close interaction between humans and things. Many applications of IoT and MSN are based on the community structure to realize efficient services, and thus the detection of the community structure has become a key problem and attracted much academic attention. In this paper, a compressive sensing (CS) over graphs-based intercommunity detection scheme is proposed for the social IoT. By exploiting the probability of two nodes encountering each other, the encounter probability and the edge-clustering coefficient are utilized to define a novel metric for each connection and construct the measurement matrix. Then a CS-based detection algorithm is proposed to detect the intercommunity links. Moreover, the edge-clustering coefficient is exploited as the prior information to further improve accuracy and reduce complexity. Simulations show that the proposed detection scheme outperforms the conventional random walk-based scheme in the social IoT.

In this paper, near-optimal optical power allocation and layer assignment for layered asymmetrically clipped optical orthogonal frequency division multiplexing (LACO-OFDM) are investigated. The average electrical power of each subcarrier should be equally allocated via convex optimization in order to obtain the optimal bit error rate performance. The channel capacity of LACO-OFDM with different layers under additive white Gaussian noise serves as the standard to determine the optimal layer number under different signal-to-noise ratio scenarios. Computer simulations have been conducted to verify the validity of the theoretical analysis for the proposed power allocation and layer assignment schemes.

Visible light communication (VLC), as a promising alternative to the next generation wireless communication technologies, has drawn extensive research interests. In this paper, a novel hybrid intensity modulated direct detection (IM/DD) communication system is proposed, which integrates the multi-carrier and single-carrier modulation to enhance spectrum efficiency and support different qualities of services (QoS). In the proposed method, the negative hybrid asymmetrically clipped optical orthogonal frequency division multiplexing (NHACO-OFDM) is proposed based on the conventional HACO-OFDM scheme, and then HACO-OFDM and NHACO-OFDM signal are combined with on-off keying (OOK) for simultaneous transmission. Simulation results demonstrate that the hybrid transmitted signals can be recovered completely at the receiver with higher spectrum efficiency, meanwhile the proposed system can support multi-service requirements and adapt to the different receivers with various complexities.

Visible light communication (VLC), as a promising future wireless communication technology, has been considered as an attractive solution for indoor positioning systems. In this paper, a novel indoor visible light positioning system is proposed, where the Gray code is utilized for the positioning identification (ID). Compared with the existing light emitting diode (LED)-ID systems, the proposed scheme can deal with the overlapping area problem where the target receiver detects multiple positioning IDs from neighboring LED lamps. Furthermore, the alternating current in the power line is used for time synchronization to facilitate the indoor localization. Experimental demonstration are carried out to verify the feasibility of the proposed scheme, which shows that the proposed system can provide superior performance with large positioning range and low implementation complexity.

This paper proposes a novel doubly selective channel estimation scheme for MIMO-OFDM systems with both time- and frequency-domain training (TFDT) based on structured compressive sensing (SCS). The characteristics of the doubly selective channel is considered in three dimensions, i.e., sample-domain, tap-domain, and antenna-domain. The tap-domain channel impulse responses (CIRs) are jointly sparse, while the sample-domain CIRs can be expanded by specific bases. We utilize the received pseudo-random noise (PN) sequence to acquire the common support of the channel. After a cyclic reconstruction process, the channel estimation can be performed under an SCS model by exploiting the proposed pilot pattern and the spatial correlation among antennas. Simulation results demonstrate that the proposed scheme has a superior performance than that of conventional counterparts.

The non-orthogonal multiple access (NOMA) technology has been proposed and regarded as one of the potential promising technologies for the future 5G network. The extension of generalized spatial modulation multiple-input multiple-output (MIMO) to NOMA system improves both the spectral and energy efficiencies of the system, while maintaining the massive connectivity and low latency advantages, but it puts forward challenges for the multi-user and signal detection as well. In this paper, we propose a joint user activity and signal detection scheme based on the block-sparse compressive sensing (BS-CS) method in the uplink NOMA system, in which the generalized spatial modulation MIMO technology is used. By exploiting the structure and sparsity of the multi-user generalized spatial modulation signals, we formulate the detection problem into a block-sparse recovery problem. Then a BS-CS based detection algorithm, enhanced structured block-sparse compressive sampling matching pursuit (ESB-CoSaMP), is proposed to detect the active users and transmitted data efficiently. Moreover, the information of active antennas at each user is exploited in ESB-CoSaMP to further improve the accuracy. Simulations show that the proposed detection scheme outperforms the conventional CS and BS-CS based schemes.

As the shortage of spectrum is becoming a serious problem to the wireless communication, visible light communication (VLC) is attracting widespread attention. However, the access to the backbone network is likely to completely modify the communication network, thus leading to a great cost. Fortunately, the technology of power line communication (PLC) is a perfect match to VLC, which provides power supply and connection for VLC to the backbone network. In this study, the authors take an integration of PLC and VLC into consideration and mainly focus on a communication framework with multi‐service. In the case of not making a big modification to the origin network, a direct re‐transmission concept is considered and three implementation schemes which differ in frequency domain, time domain, and bit division multiplexing (BDM) are proposed. The demonstration platform and the simulation results suggest that the proposed schemes have the ability to support multi‐service transmission with no big modification of current power line network. Moreover, the BDM scheme can accommodate different requirements of quality of service with better performance than conventional multi‐service schemes.

In the next generation of cellular networks, millimeter wave (mmWave) communications will play an important role. With the utilization of mmWave communications, the massive multiple-input multiple-output (MIMO) technique can be effectively employed, which will significantly improve system capacity. However, an effective channel estimation scheme is the prerequisite of system stability and in great need for improvement in massive MIMO systems. In this paper, a channel estimation scheme based on training sequence (TS) design and optimization with high accuracy and spectral efficiency is investigated in the framework of structured compressive sensing. As a new perspective to optimize the block coherence of the sensing matrix, the auto-coherence and cross-coherence of the blocks are proposed and specified as two kinds of key merit factors. In order to optimize the two factors, specific TS is designed and obtained from the inverse discrete Fourier transform of a frequency domain binary training sequence, and a genetic algorithm is adopted afterwards to optimize the merit factors of the TS. It is demonstrated by the simulation results that the block coherence of the sensing matrix can be significantly reduced by the proposed TS design and optimization method. Moreover, by using the proposed optimized TS's, the channel estimation outperforms the conventional TS design obtained by the brute force search in terms of the correct recovery probability, mean square error, and bit error rate, and can also approach the Cramer-Rao lower bound.

Narrowband Internet-of-Things (NB-IoT) is one of the emerging 5G technologies, but might introduce narrowband interference (NBI) to existing broadband systems, such as long-term evolution advanced (LTE-A) systems. Thus, the mitigation of the NB-IoT interference to LTE-A is an important issue for the harmonic coexistence and compatibility between 4G and 5G. In this paper, a newly emerged sparse approximation technique, block sparse Bayesian learning (BSBL), is utilized to estimate the NB-IoT interference in LTE-A systems. The block sparse representation of the NBI is constituted through the proposed temporal differential measuring approach, and the BSBL theory is utilized to recover the practical block sparse NBI. A BSBL-based method, partition estimated BSBL, is proposed. With the aid of the estimated block partition beforehand, the Bayesian parameters are obtained to yield the NBI estimation. The intra-block correlation (IBC) is considered to facilitate the recovery. Moreover, exploiting the inherent structure of the identical IBC matrix, another method of informative BSBL is proposed to further improve the accuracy, which does not require prior estimation of the block partition. Reported simulation results demonstrate that the proposed methods are effective in canceling the NB-IoT interference in LTE-A systems, and significantly outperform other conventional methods.

In this paper, a novel impulsive noise (IN) cancel- lation scheme based on structured compressed sensing (SCS) for multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) power line communication systems is proposed. The SCS theory is introduced to IN recovery for the first time in this paper to the best of the authors' knowledge, and the gap of lack of research on the IN mitigation for MIMO PLC systems is filled. First, the measurements matrix of the IN is obtained, and the SCS optimization framework is formulated through the proposed spatially multiple measuring method, by fully exploiting the spatial correlation of the IN signals at different receive antennas. To efficiently reconstruct the IN signal, an enhanced SCS-based greedy algorithm, structured a priori aided sparsity adaptive matching pursuit (SPA-SAMP), is proposed, which significantly improves the accuracy and robustness compared with the state-of-art methods. Theoretical analysis and computer simulations validate that the proposed scheme outperforms conventional methods in the typical MIMO PLC system.

A block sparse Bayesian learning (BSBL) based approach of narrowband interference (NBI) cancellation for cyclic prefixed orthogonal frequency division multiplexing based smart grid communications is proposed in this paper. The BSBL theory is firstly introduced to recover the practical block sparse NBI with a frequency offset compared with the sub-carriers. The block sparse representation of the NBI is constituted through the proposed temporal differential measuring approach. A BSBL based method, estimated partitioned BSBL, is proposed for NBI recovery. The intra-block correlation is firstly considered to facilitate the recovery of block sparse NBI. Reported simulation results demonstrate that the proposed methods are effective and significantly outperform conventional counterparts.

Visible light communication (VLC) using the light emitting diode (LED) will become an appealing alternative to the radio frequency communication technology for indoor wireless broadband access. However, VLC needs a ubiquitous network as its backbone to avoid becoming an information isolated island. Power line communication (PLC) systems could easily solve the informative problem of VLC while powering the LED lamps at the same time, which is considered as a good partner of VLC for the cost-effective implementation. In this paper, a novel and cost-effective framework of ubiquitous indoor broadband access based on deeply integrated VLC and PLC technology with only low-cost modification to the current infrastructure is therefore proposed. The broadband access network supports duplex transmission through each LED using the decode-and-forward (DF) working mode. This paper will present our recent research progress in this area, including a prototyping of duplex voice communications network based on hybrid PLC and VLC in our lab. Our research and development plan in this area for the near future will also be covered.

In practical multiple input multiple output (MIMO) systems, accurate knowledge of the channel state information (CSI) is a prerequisite to guarantee the system performance. The conventional CSI acquisition methods for MIMO system usually rely on the orthogonal (either time‐ or frequency‐domain) training sequences (TSs) to estimate the channel associated with each transmit–receive antenna pair, which is not spectrally efficient. This study proposes a non‐orthogonal time‐domain training‐based CSI acquisition approach for MIMO systems under the framework of structured compressive sensing. By exploiting the spatial–temporal correlations of the sparse MIMO channels, a spatially–temporally spARsity‐adaptivE‐simultaneous orthogonal matching pursuit algorithm is proposed, which could use the inter‐block interference free region of very small dimension within the received TS to recover the multiple channels. Furthermore, the proposed algorithm could utilise the priori channel partial common support to improve the recovery probability and reduce the complexity. Simulation results show that the proposed scheme has better performance and higher spectral efficiency than the conventional MIMO schemes, which might be an appealing solution for the future wireless communications.

Power line communication (PLC) techniques present a no extra wire solution for the communication purpose in a smart grid due to the ubiquity and low cost. Moreover, the through-the-grid property of PLC has naturally extended its possible applications, including but not limited to the automatic meter reading, line quality monitoring, online diagnostics, and network tomography. To guarantee the performance of communications as well as other applications in PLC systems, accurate channel state information (CSI) acquisition should be performed regularly. However, the conventional pilot-based CSI acquisition approaches in PLC systems have not made full use of the channel characteristics and hence suffer from a low spectral efficiency. In this paper, by exploiting the parametric sparsity and discretizing the electrical length in the well-known PLC channel model, we formulate the non-sparse (either time domain or frequency domain) PLC channel into a compressive sensing (CS) applicable problem. Furthermore, we propose a spectrally efficient CSI acquisition scheme under the framework of Bayesian CS and extend it to the multiple-input multiple-output PLC by investigating the channel spatial correlation. Compared with the existing sparse CSI acquisition schemes for PLC, such as the annihilating filter-based and the estimating signal parameters via rotational invariance technique-based ones, the proposed scheme has better mean square error performance and noise robustness.

Power line communication (PLC) systems present a “no new wires” solution for the telecommunication access with the additional advantages of ubiquitous availability, easy installation and cost effectiveness. In this paper, by exploiting the parametric sparsity of the PLC channels, we propose a robust sparse channel state information (CSI) acquisition scheme under the framework of Bayesian compressive sensing (CS), which could significantly reduce the pilot overhead and improve the spectral efficiency. Compared to the current sparse CSI acquisition schemes for PLC, including those based on annihilating filter and estimating signal parameters via rotational invariance techniques (ESPRIT) algorithm, the proposed scheme is numerically demonstrated to have better mean squared error (MSE) performance. Furthermore, the proposed method is an appealing solution for practical PLC system, since the performance degradation due to the parameter discretization is not significant.

Bit-interleaved coded modulation (BICM) systems with high order constellations and signal space diversity (SSD) are deployed in DVB-T2 and recommended for potential use in 3GPP-LTE standards for its high spectral efficiency and diversity gain. However, in such systems, previous soft demapping algorithms show either extremely high computational complexity or poor performance under imbalanced In-phase/Quadrature (IQ) fading channel due to SSD. In this paper, a simplified universal soft demapping algorithm for Gray-mapped Mary constellation with O(logM) computational complexity is proposed. According to the average mutual information analysis and bit error rate (BER) simulation, the proposed algorithm shows almost the same performance as the Max-Log-MAP algorithm under conventional channel and a little SNR loss under imbalanced IQ fading channel.

Visible light communication (VLC), as an appealing alternative to the classical radio frequency communication technologies, has a bright application prospect for future wireless communications. In this paper, we propose an integrated power line communication (PLC) and VLC system with bit division multiplexing (BDM). By the integration of VLC with PLC, the lamp can work as light source as well as access point, and the architecture of VLC network could be significantly simplified. Meanwhile, the BDM scheme could simultaneously support multi-service, e.g., data transmission and navigation services as global and local services, respectively, in a natural single frequency network (SFN) structure with low complexity, high spectral efficiency, and easy switching protocol as well. Simulation results demonstrate that this proposed scheme can accommodate different requirements of quality of service (QoS) and outperform conventional multi-service schemes with time-frequency channel resource allocation approaches.

In this paper, a novel impulsive noise (IN) cancellation scheme based on priori aided compressive sensing (CS) for OFDM-based communications systems is proposed. The IN is reconstructed from the frequency-domain measurements at the null sub-carriers based on the CS theory using greedy algorithms. With the aid of the a priori partial support obtained from the proposed time-domain thresholding method, we propose the enhanced greedy algorithm of priori aided sparsity adaptive matching pursuit (PA-SAMP) to improve the accuracy and robustness of the IN recovery. Theoretical analysis and computer simulations validate that the proposed method outperforms conventional CS-based and other classical IN mitigation methods for OFDM-based communications systems.

As the shortage of spectrum is becoming a serious problem to the wireless communication, visible light communication (VLC) is attracting widespread attention. However, the accession to the backbone network is likely to completely modify the communication network, thus leading to a great cost. Fortunately, the technology of power line communication (PLC) is a perfect match to VLC, which provides power supply and connection for VLC to the backbone network. In this paper, we take an integration of VLC and PLC into consideration and mainly focus on a communication framework with multifunction. In the case of not making a big modification to the origin network, a direct re-transmission concept is considered and two implementation schemes which differ in frequency and time domain are proposed. A demonstration platform is built which suggests that both schemes have the ability to support positioning and multi-service transmission in a high data rate with no big modification of current power line network.

Multiple-input multiple-output (MIMO) is one of the key technologies for the next generation digital terrestrial television broadcasting (DTTB). This paper proposes a near-capacity MIMO bit-interleaved coded modulation (BICM) scheme for DTTB systems. The amplitude phase shift keying (APSK) constellation with Gray mapping is applied to the BICM scheme. From the perspective of average mutual information, APSK has the advantage of shaping gain compared to its quadrature amplitude modulation (QAM) counterpart. Moreover, a new kind of bit interleaver named bit mapping, which takes into account the unequal error protection of both APSK and low-density parity-check (LDPC) codes, is proposed to further improve the system performance. The tool of extrinsic information transfer chart is utilized to help analyze and design the optimal bit mapping. Bit error rate simulations are carried out to verify the superiority of the proposed MIMO system.

The dual pseudo noise padded (DPNP) time‐domain synchronous‐orthogonal frequency division multiplexing (TDS‐OFDM) which utilises the second pseudo noise (PN) sequence for channel estimation is able to reduce the complexity and improve the accuracy of channel estimation compared to the classical TDS‐OFDM. However, because of the duplicate PN sequence, DPNP TDS‐OFDM will suffer from severer out‐of‐band emission, which is a headache issue for the conventional TDS‐OFDM. In this study, a novel out‐of‐band suppression approach based on a new PN design criterion as well as a windowing operation is proposed for the DPNP TDS‐OFDM systems. The frame structure and system model are also modified to accommodate to the approach, while the overlap‐and‐add approach is adopted to guarantee the spectral efficiency. Both simulation and experimental results show that this approach could achieve satisfactory performance with much less complexity and no spectral efficiency loss compared to the classical DPNP TDS‐OFDM system. In addition, an iterative channel estimation method is also proposed for the modified frame structure to combat against the long channel delay spread.

Conventional time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) systems have the difficulty to support 256QAM or higher-order modulations and suffer from performance loss, especially under the severe fading channels with long delays. In this letter, a simultaneous time-frequency channel estimation method based on compressive sensing (CS) is proposed to solve this problem. First, the auxiliary channel information is obtained by exploiting the signal structure of TDS-OFDM. Then, a very few frequency-domain pilots in the OFDM block are used to acquire the accurate channel impulse response under the framework of CS. Besides, the auxiliary channel information is utilized to further reduce the complexity of the classical CS algorithm. Simulation results show that the proposed scheme can well support 256QAM under fading channels with long delays and have better performance than the conventional schemes.

A novel compressive sensing (CS) based narrowband interference (NBI) cancellation approach for power line communication (PLC) systems is proposed in this paper. The repeated training sequences of the preamble in PLC systems are utilized for differential measuring to acquire the measuring vector. Under the CS framework, the sparse high-dimensional NBI signal can be reconstructed from the measuring vector of much smaller size obtained through the proposed CS-based differential measuring (CSDM) method. It is verified by theoretical analysis and simulations that the proposed method outperforms conventional anti-NBI methods under the PLC channel.

In this paper, an optimized time-frequency interleaving scheme is proposed to combat against the narrowband interference (NBI) and time-domain impulsive noise (TIN) for orthogonal frequency division multiplexing (OFDM) systems in power line communications (PLC). To improve both the anti-NBI and anti-TIN performance, we propose two criteria based on which the optimized interleaving scheme is designed: (i) to increase the number of different OFDM blocks for one forward error correction (FEC) codeword, which is aimed at TIN mitigation; and (ii) to increase the number of different sub-carriers mapped to the data cells in one FEC codeword, which is aimed at NBI mitigation. Simulations show that the proposed interleaving scheme can effectively reduce the impairments caused by NBI and/or TIN in OFDM systems under PLC environments, and hence achieve better performance than the conventional block interleaving scheme.

In this paper, the framework of amplitude phase shift keying (APSK) constellation labeling design for satellite transmission is proposed. It consists of two steps, the constellation design and the joint phase-labeling optimization. Both iterative and non-iterative demapping scenarios are considered in the design framework. The proposed APSK constellation labeling exhibits a low peak-to-average power ratio and achieves a considerable performance gain compared with its counterpart approved by the consultative committee for space data systems, as verified by both the mutual information analysis and bit error rate simulation.

Digital video broadcasting-next generation handheld (DVB-NGH) is the first broadcasting standard that incorporates multiple-input multiple-output (MIMO) techniques to overcome the Shannon limit of single antenna systems. This paper contributes to analyze the performance of the DVB-NGH MIMO coded modulation system. The detailed performance degradation from information-theoretic limit to implementation by average mutual information and extrinsic information transfer analysis is presented, which provides an insight guideline for future system improvement. Finally, bit error rate simulations are carried out to verify the analysis.

Time‐domain synchronous orthogonal frequency division multiplexing (TDS‐OFDM) enjoys the higher spectrum efficiency and faster synchronisation than the classical cyclic prefix OFDM (CP‐OFDM). However, TDS‐OFDM suffers from performance degradation especially under severely fading channels with long delays. To solve these problems, the authors propose an energy‐efficient OFDM scheme called time–frequency‐training orthogonal frequency division multiplexing (TFT‐OFDM) based on the time–frequency joint channel estimation under the framework of compressive sensing (CS). The power of the guard interval (GI) in the proposed scheme can be reduced to achieve higher energy efficiency, which is infeasible for CP‐OFDM. This method first utilises the time‐domain pseudo noise sequence to acquire partial support information of the channel, and then some frequency‐domain pilots are used for the exact channel estimation. Simulation results show that TFT‐OFDM with CS can achieve much higher energy efficiency than the classical CP‐OFDM, and outperforms the conventional OFDM schemes in both static and mobile environments. Moreover, for the channel with long delay spread, the TFT‐OFDM scheme with CS can demonstrate robustness and much better performance than the conventional OFDM schemes. In this way, the TFT‐OFDM scheme can use the same GI length for larger broadcasting coverage and hence further achieve higher energy efficiency.

This paper proposes a novel coded-modulation scheme using amplitude phase shift keying (APSK) constellations with Gray mapping for the broadband power line communication systems for the first time. In this scheme, three key techniques including the Gray-APSK constellation design, the bit mapping technique, and the method of simplified soft APSK demapper are jointly employed to enhance the error-control performance while ensuring low complexity. Simulation results over AWGN and power line channels show that the proposed scheme provides a remarkable receiving performance gain, compared to its counterpart specified in the G.hn standard.

In this paper, the spectrum notch technique which combines the time-domain windowing and training sequence (TS) redesigning for the time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) system is proposed. An improved frame structure with overlapping between adjacent frames for the dual pseudo noise padded (DPNP) TDS-OFDM system is put forward to make the spectral efficiency undiminished. The simulation results show that this method can deepen the notches in the power spectrum density (PSD) compared to the conventional TDS-OFDM system by about 7 to 8 dB without any spectrum efficiency cost, which could be in accordance with the -30dB spectrum notch requirements in the spectral mask defined in HomePlugAV 1.1.

The amplitude phase shift keying (APSK) constellation with Gray labeling (Gray-APSK) is able to achieve considerable shaping gains in comparison with the quadrature amplitude modulation (QAM) counterpart under both iterative and non-iterative scenarios. Nevertheless, the Gray-APSK constellation with the fixed radius cannot provide the optimal performance for every code rate of practical usage. In this paper, we propose a method based on the genetic algorithm to optimize the parameters of Gray-APSK constellations by maximizing the mutual information for the targeted code rate. Certain performance gains can be achieved via optimizing the radius of the Gray-APSK, as verified by both the average mutual information (AMI) analysis and the error performance evaluation.

In this paper, a signaling-embedded preamble design is proposed for the orthogonal frequency division multiplexing (OFDM) system with transmit diversity. Utilizing the transmit diversity, two identical training sequences (TSs) are embedded in two OFDM symbols separately in discrete Fourier transform (DFT) domain and transmitted by two different antennas simultaneously. The relative distance between the two TSs in DFT domain could be varied in order to indicate several bits of signaling information for the receiver to acquire the transmission parameters signaling (TPS) quickly. Furthermore, the preamble can also be used for frame synchronization, carrier frequency offset (CFO) estimation, and coarse channel estimation. The computational simulations were carried out under both additive white Gaussian noise (AWGN) and multipath channels, and the results demonstrated the design works accurately on the preamble detection, CFO estimation and signaling demodulation under both static and dynamic channels.

Due to the unequal error protection (UEP) property of both the irregular low-density parity-check (LDPC) code and the higher-order modulation, bit mapping is proposed as a joint optimization of the LDPC coded-modulation scheme. In this paper, we discuss the bit mapping optimization performed by employing an additional DEMUX following the given bit interleaver, and then apply it to the second generation digital video broadcasting system for cable (DVB-C2). The extrinsic information transfer (EXIT) chart technique is adopted to analyze the influence of bit mapping on the iterative decoding process. Based on the EXIT-chart analysis, an optimization method is proposed to design the DEMUX for performance improvement. As an example, we re-design the DEMUX for the DVB-C2 system with reduced DEMUX width. The superior performance of the optimized DEMUX is verified by the bit error rate (BER) simulation.

A novel preamble design is proposed for orthogonal frequency division multiplexing systems, which exploits the variable distance between a pair of training sequences for the transmission parameter signalling. Compared to the existing P1-symbol based preamble for the second generation digital terrestrial television broadcasting standard, the proposed design maintains the high performance and robustness in timing and carrier frequency offset estimation while significantly reducing the signalling detection complexity. Simulation results demonstrate that the proposed novel preamble achieves a better signalling detection performance than the P1 symbol design.

Bit-interleaved coded modulation with iterative demapping (BICM-ID) is investigated for multiple-input multiple-output (MIMO) channels. Based on the average mutual information (AMI) analysis, vertical Bell-lab layered space-time (V-BLAST) rather than space-time block code (STBC) is chosen to be combined with BICM-ID. Based on the extrinsic information transfer (EXIT) chart analysis, a novel algorithm in searching for a labeling to well match the outer code is proposed for MIMO channels, which facilitates a near-capacity V-BLAST-BICM-ID scheme. Computer simulation confirmed the near-capacity performance.

In order to accommodate the different applications in wireless transmission environment, communication systems usually provide several configurable transmission modes. Therefore, transmission parameter signalling (TPS) is critical for the receiver to recognize the signal transmission modes. In this paper, the pseudo-noise (PN) training sequence with embedded signalling in the time domain synchronous block transmission (TDS-BT) system is investigated, where the TPS could be conveyed through the transformation of the PN sequences in the frame head. The proposed signalling-embedded PN sequences could provide precise synchronization as well as robust signalling performance without extra transmission resource consumption. Computer simulations are also presented to verify the effectiveness of our proposed methods.

This paper presents a method to measure and predict the reception quality of the digital terrestrial/television multimedia broadcasting (DTMB) system in a single frequency network (SFN) environment. Measurement of the signal-to-noise ratio (SNR) threshold at several market commercial receivers was carried out in the laboratory. After analyzing the channel capacity loss produced by the multiple transmitter reception, a prediction model of SNR threshold is presented. Simulation results are also performed to verify the accuracy of the prediction method. This model and method could be adopted for SFN planning to ensure a good service quality in the SFN environment.

To revive the lack of spectral resources due to the expansion of service requirements and implementation of flexible service transmission, next generation digital television broadcasting system should define frame structures to support efficient and compatible multi-service transmission for different applications, especially terrestrial high definition television (HDTV) and mobile TV services. The approach to support compatible OFDM symbols with different sub-carrier intervals and improve the spectral efficiency is discussed. In this paper, two novel TDS-OFDM composite frame structures are proposed with the concept of physical sub-channel (PSC) to support services with different quality of service (QoS) requirements. Simulation results show that the proposed frame structures can provide multi-service transmission with diverse requirements and high spectral efficiency as well.

In this paper, a new channel coding scheme for the narrowband powerline communication (PLC) system employing quasi-cyclic (QC) low-density parity-check (LDPC) codes of multiple code rate and multiple code length is proposed. Combined with proper constellation mappings, 4 transmission modes can be supported, which provides different error correction capabilities. A comparison with the coding scheme in the G3 specification is performed, confirming that the proposed scheme is superior to G3 in terms of both flexibility and reliability while the efficiency is higher than that of G3. A study on the implementation complexity on FPGA is also conducted to prove the feasibility of using the proposed scheme in future practical narrowband PLC system.

Signal space diversity (SSD) is a well-known power- and bandwidth-efficient diversity technique with constellation rotation and coordinate interleaving. This paper investigates issues of combining SSD with coded modulation systems (CMSs), e.g., bit-interleaved coded modulation (BICM) and its iterative version, BICM-ID. It demonstrates that the average mutual information (AMI) between the signal after rotated constellation mapping and the signal before or after the soft demapper varies with the rotation angle. A new criterion for determining the optimal rotation angle by maximizing such AMI is therefore proposed. Specific considerations of combining SSD with BICM (BICM-SSD) and BICM-ID (BICM-ID-SSD) are addressed. The demapper's extrinsic information transfer (EXIT) curve in traditional BICM-ID systems exhibits different slopes under different channels, which consequently prevents traditional BICM-ID systems from having simultaneously excellent performance under different channels. It is shown that such a different-slope problem can be simply mitigated by a proper use of SSD. Analysis and simulation show that the proposed BICM-ID-SSD systems hold a near-capacity performance under both additive white Gaussian noise (AWGN) and Rayleigh fading channels simultaneously.

Signal space diversity (SSD) is a well-known technique providing excellent performance gain over fading channels. This paper investigates the system design of bit-interleaved coded modulation with iterative demodulation and SSD (BICM-ID-SSD). It demonstrates that within SSD the average mutual information (AMI) between the signal after rotated constellation mapping and that before the soft demapper varies with the rotation angle. Therefore, a new criterion for searching the optimal rotation angle by maximizing such AMI is proposed. Based on this criterion it is shown that the optimal rotation angle is not relevant to the labeling, and 45-degree is found to be the optimal or near optimal rotation angle for square quadrature amplitude modulation (QAM) at low to moderate code rates. Furthermore, the procedure of BICM-ID-SSD system design could be divided into two independent steps: 1) determining the optimal rotation angle based on the above criterion, and 2) choosing well-fitted labeling and outer channel code with the aid of extrinsic information transfer (EXIT) charts. Analysis and simulation results show that the proposed system exhibits a near-capacity performance, meanwhile being robust over both additive white Gaussian noise (AWGN) and Rayleigh fading channels.

This paper summarizes some key features for future Chinese digital television terrestrial broadcasting (DTTB) systems including improved frame structure, transmit diversity, advanced channel coding and modulation, multi-service support, broadcasting return channel solution and etc.

To improve the overall performance of time-domain synchronous (TDS) orthogonal frequency division multiplexing (OFDM) systems, novel iterative decoding and channel estimation algorithm with Nordstrom-Robinson (NR) code is proposed in this paper. Compared to the non-iterative case, the system performance can be significantly improved by the proposed iterative algorithm at the cost of a little complexity and latency increase. Simulation results show that, for example, with maximum Doppler spread of 25 Hz under two typical multipath channels at bit error rate (BER) of 10-4, the signal to noise ratio (SNR) performance of the proposed iterative algorithm is only 0.2 to 0.3 dB away from the ideal case, and about t dB or more better than the non-iterative one.

In order to improve the system performance over wireless fading channel, transmit diversity technique has been proven as an attractive and effective solution especially for broadcasting systems. In this paper, a PN sequence design scheme based on both cyclic-shift m-sequences and space-time block coded (STBC) m-sequences for time domain synchronous orthogonal frequency-division multiplexing (TDS-OFDM) system with transmit diversity is proposed. Based on this novel design, flexible channel estimation which provides a trade-off between maximum delay spread and maximum Doppler spread over double-selective channel is investigated and a radix-2 fast Fourier transform (FFT) approach is adopted for implementation from the viewpoint of computational complexity. Simulations show that the performance of the proposed transmit diversity scheme is better than conventional one and perform well under different propagation conditions.

In order to improve the system performance over both frequency- and time-selective fading channels, orthogonal frequency division multiplexing (OFDM) system with transmit diversity technique is an effective and attractive solution. However, the received signal is the superposition of the signals from different transmit antennas. Hence, to obtain accurate channel state information (CSI) is difficult but very important to recover transmitted OFDM symbols. Conventional channel estimation methods use subcarrier pilots or training sequences as the channel sounding signal to obtain the estimation of channel frequency response (CFR). Actually, decision-directed channel estimation (DDCE) method which takes advantage of the fact that m-QAM constellation subcarriers in OFDM symbol also contain much valuable hidden-information and can be used to perform the channel estimation as well as tracking of time-varying channel. In this paper, a simple and effective partial hard decision method for m-QAM is investigated. Furthermore, a simplified DDCE method based on an accurate initial CFR and partial decision results of OFDM subcarriers for transmit diversity system is proposed. Simulation results demonstrate that the proposed algorithm works well over the slow-varying frequency-selective fading channel.

This study proposes an iterative channel impulse response (CIR) estimation scheme for multicarrier block transmission with known symbol padding, in the context of the time-domain synchronous OFDM (TDS-OFDM) system. It is shown that the TDS-OFDM still fulfils the circular convolution relationship even if pseudo-noise (PN) sequence is used as guard interval. While conventional methods perform the channel estimation based on the cyclic prefix reconstruction or residual intersymbol interference cancellation in the time domain, by processing the data part and the known symbol padding in one TDS-OFDM block separately, the new proposal uses the one- tap frequency-domain equalization to separate the data part and the known symbol padding and the CIR can be estimated in an iterative manner. In a typical example for 3780-point FFT based TDS-OFDM system with 16QAM constellations, the mean square error (MSE) of of the proposed channel estimator can be reduced to about 10-5/2 after two iterations when the channel signal-to-noise ratio (SNR) is larger than 8 dB, without the initial CIR estimation. The BER performance of a QPSK TDS-OFDM system shows that the signal-to-noise-ratio (SNR) degradation based on the proposed channel estimator is less than 0.3 dB compared with the lower bound for both Brazil A and B channels.