The application of power over Ethernet (PoE)-enabled lighting has emerged as a groundbreaking technology with the potential to achieve cooperative control and create an energy-saving lighting network. However, fine-grained user-side lighting environment perception is crucial to improve energy efficiency and user experience. To tackle this issue, a PoE-enabled intelligent lighting network with multi-modal sensing is proposed. Specifically, a multi-modal sensor is designed and installed on the side of the luminaire to provide both fine-grained lighting environment monitor and dimming. Then, a multilayer perceptron (MLP)-based estimation scheme is proposed to estimate the illumination and color temperature information around the user activity area. Moreover, an experimental lighting network is constructed and deployed in a classroom to measure practical lighting dataset. The proposed scheme effectively estimates the lighting quality on the user side based on the measurement data. Furthermore, based on the estimated information and the collaborative control capabilities of PoE, the operating current of the luminaire is updated in real time, and thus the ambient light resource is fully utilized. Finally, the proposed lighting network achieves a 39.99% energy saving.

The majority of research on visible light communications (VLC) neglects the non-line-of-sight (NLoS) channel gains, which cannot be ignored for physical-layer security analysis. Moreover, the commonly used semidefinite relaxation technique for power minimization problems may not always yield an optimal solution due to the removal of the rank-one constraint. In this letter, we investigate a power minimization-based secure beamforming problem for a multiple-input single-output VLC system having both LoS and NLoS components. Assuming perfect channel state information (CSI), we formulate an optimal secure beamforming problem with a worst-case secrecy rate constraint and a per-lamp power constraint. Instead of removing the rank-one constraint, we incorporate such a constraint into the objective function and treat it as a penalty term. Then, we propose a semidefinite programming and penalty function (SDPPF) algorithm to solve the non-convex problem. To enhance practicality, we also consider the case of imperfect CSI and explore a robust beamforming scheme. Numerical results demonstrate that the proposed SDPPF algorithm can achieve a power gain of at least 3 dB compared to existing algorithms. Moreover, the necessity of considering the NLoS channel gains is also verified.

Log-based anomaly detection is crucial for software reliability assurance. System logs are semi-structured data containing constant and variable contents, both of which can provide valuable features for anomaly detection. Due to variables being heterogeneous and discrete, there is a lack of effective approaches that can comprehensively incorporate features of variables into log-based anomaly detection. In this paper, we propose VCRLog, an anomaly detection method that mines the relationships among the heterogeneous and discrete variables and extracts important features contributing to anomaly detection. Firstly, considering parsing methods cannot accurately extract variables from logs, we propose a variable extraction method based on domain knowledge. Secondly, to capture and extract the relationship feature among heterogeneous and discrete variables, we design a conceptual model based on system operation to construct variable attributed graph, which can mine important feature vectors by structural embeddings. Finally, considering constants directly express the meaning of logs, we combine relationship vectors with semantic vectors of constants to achieve transformer-based anomaly detection. Experimental results show that our proposed method can accurately detect anomalies and maintain high accuracy as the training data size decreases, outperforming existing methods. Our source code and experimental data are publicly available at https://github.com/Fridaywjy/VCRLog.

Junlong Li, Jinyuan Wang, Zhuosheng Zhang, Hai Zhao. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2024.

This letter focuses on an unmanned aerial vehicle (UAV)-based covert visible light communication system. We establish a system model, where a UAV secretly transmits a message to a legitimate user, avoiding a warden's detection. In the system, weather-dependent channel gain is considered. We first analyze the mutual information of the communication channel and the covertness constraint of the detection channel. To improve system performance, we jointly optimize the UAV's height and peak optical intensity by maximizing the mutual information subject to the UAV's height constraint and peak optical intensity constraint. The UAV's optimal height and peak optical intensity are derived, and the existence of the solutions is proved. By adding an additional covertness constraint, the optimal solutions are also derived. Numerical results verify the effectiveness of the proposed joint optimization schemes. It is also shown that different weather conditions lead to differences in visibility ranges, which significantly affect the system performance.

The integrated sensing and communication has emerged as a key technology for future wireless systems. This article considers a multislot integrated visible light communication and sensing (IVLCS) system. In the IVLCS system, the primary purpose is sensing, while the second purpose is communication. We formulate a joint slot selection and power allocation problem by minimizing the total transmitted power under the echo-to-noise ratio constraint, communication sum rate constraint, sensing slot number constraint, and power constraint. Such a problem is shown to be nonconvex. After convex relaxation reformulation, the original problem is divided into a sensing subproblem and a communication subproblem. We propose a sensing priority and power minimization-based joint slot selection and power allocation (SPPM-JSSPA) algorithm to solve the two subproblems. To further reduce the complexity, a low-complexity fixed slot selection and power allocation (FSSPA) algorithm is also proposed. The convergence and complexity analysis indicates that both the proposed SPPM-JSSPA algorithm and the FSSPA algorithm are convergent and efficient. Numerical results show that the proposed SPPM-JSSPA algorithm can obtain the best performance compared to the existing algorithms, and the low-complexity FSSPA algorithm can achieve a comparable performance to the SPPM-JSSPA algorithm.

In physical-layer security, secrecy capacity is an important performance metric. This work aims to determine the secrecy capacity for an indoor visible light communication system consisting of a transmitter, a legitimate receiver and an eavesdropping receiver. In such a system, both signal-independent noise and signal-dependent noise are considered. Under nonnegativity and average optical intensity constraints, lower and upper bounds on secrecy capacity are derived by the variational method, the dual expression of the secrecy capacity, and the concept of “the optimal input distribution that escapes to infinity”. By an asymptotic analysis at large optical intensity, there is a small gap between the asymptotic upper and lower bounds. Then, by adding a peak optical intensity constraint, we further analyze the exact and asymptotic secrecy-capacity bounds. For practical considerations, the effects of imperfect channel state information, multi-photodiode eavesdropper, and artificial noise on secrecy performance are also discussed. Finally, the derived secrecy-capacity bounds are verified by numerical results.

Training dense passage representations via contrastive learning has been shown effective for Open-Domain Passage Retrieval (ODPR).Existing studies focus on further optimizing by improving negative sampling strategy or extra pretraining.However, these studies keep unknown in capturing passage with internal representation conflicts from improper modeling granularity.Specifically, under our observation that a passage can be organized by multiple semantically different sentences, modeling such a passage as a unified dense vector is not optimal.This work thus presents a refined model on the basis of a smaller granularity, contextual sentences, to alleviate the concerned conflicts.In detail, we introduce an in-passage negative sampling strategy to encourage a diverse generation of sentence representations within the same passage.Experiments on three benchmark datasets verify the efficacy of our method, especially on datasets where conflicts are severe.Extensive experiments further present good transferability of our method across datasets.

This paper investigates coverage analysis and performance optimization for a high-speed railway (HSR) communication system with carrier aggregation (CA). Initially, the system model is established. By using CA technology, the statistical characteristic of the received signal-to-noise ratio (SNR) is obtained. Then, for the systems with or without CA, unified theoretical expressions for the edge coverage probability (ECP) and the percentage of cell coverage area (CCA) are obtained, respectively. After that, a chance-constrained coverage optimization is proposed to improve the coverage performance, which is effectively solved by using a heuristic algorithm. Numerical results show that the derived expressions of the ECP and the percentage of CCA are accurate and can be directly used to evaluate the coverage performance without time-intensive simulations. Moreover, the impacts of CA, transmit power, cell radius, received SNR threshold, HSR scenario on coverage performance have been discussed. Furthermore, the effectiveness of the proposed coverage optimization scheme is also verified.

In this paper, we investigate a low earth orbit satellite (LEO SAT) and high altitude platform (HAP) integrated edge computing network to provide computing services for ground mobile devices (GMDs). We propose to minimize the weighted sum energy consumption via jointly optimizing the GMD association, precoding design, computation task assignment and computation resource allocation. To solve the nonconvex problem, we propose an algorithm that decomposes the optimization problem into four subproblems and solves each sub-problem iteratively. Specially, the GMD association subproblem is solved by quadratic transform based fractional programming (QTFP) and difference of convex function; the precoding design subproblem is obtained via QTFP and weighted minimum mean square (WMMSE) method; the computation task assignment is solved by the interior point method and the computation resource allocation is derived in closed form. The numerical results show that the proposed algorithms can solve the problems quite well and the energy consumption is maintained at a relative low level.

Relay-assisted free-space optical (FSO) communication systems are exploited as a means to mitigate the limiting effects of the turbulence induced atmospheric scintillation. However, conventional ground relays are stationary, and their optimal placement is not always feasible. Due to their mobility and flexibility, unmanned aerial vehicles (UAVs) provide new opportunities for FSO relaying systems. In this paper, a hovering UAV-based serial FSO decode-and-forward relaying system is investigated. In the channel modelling for such a system, four types of impairments (i.e., atmospheric loss, atmospheric turbulence, pointing error, and link interruption due to angle-of-arrival fluctuation) are considered. Based on the proposed channel model, a tractable expression for the probability density function of the total channel gain is obtained. Closed-form expressions of the link outage probability and end-to-end outage probability are derived. Asymptotic outage performance bounds for each link and the overall system are also presented to reveal insights into the impacts of different impairments. To improve system performance, we optimize the beam width, field-of-view and UAVs' locations. Numerical results show that the derived theoretical expressions are accurate to evaluate the outage performance of the system. Moreover, the proposed optimization schemes are efficient and can improve performance significantly.

Channel capacity bounds are derived for a point-to-point indoor visible light communications (VLC) system with signal-dependent Gaussian noise. Considering both illumination and communication, the non-negative input of VLC is constrained by peak and average optical intensity constraints. Two scenarios are taken into account: one scenario has both average and peak optical intensity constraints, and the other scenario has only average optical intensity constraint. For both two scenarios, we derive closed-from expressions of capacity lower and upper bounds. Specifically, the capacity lower bound is derived by using the variational method and the property that the output entropy is invariably larger than the input entropy. The capacity upper bound is obtained by utilizing the dual expression of capacity and the principle of “capacity-achieving source distributions that escape to infinity”. Moreover, the asymptotic analysis shows that the asymptotic performance gap between the capacity lower and upper bounds approaches zero. Finally, all derived capacity bounds are confirmed using numerical results.

In this paper, a hovering unmanned aerial vehicle (UAV)-based free-space optical (FSO) serial multi-hop decode-and-forward relaying system is investigated. Considering the joint effect of atmospheric loss, atmospheric turbulence, pointing error and angle-of-arrival (AOA) fluctuation, the novel closed-form expressions of the link outage probabilities for ground-to-UAV, UAV-to-UAV, and UAV-to-ground links are derived, and the expression of the end-to-end outage probability for the UAV-based relaying system is also obtained. The asymptotic outage performance bounds for each link and the considered system are presented to reveal insights into the impact of AOA fluctuations. Based on the derived theoretical results, an optimization problem of receiver's field-of-view (FOV) is formulated to alleviate the impairment of AOA fluctuation. Numerical results show that the derived theoretical expressions are accurate to evaluate the outage performance of UAV-based FSO system. Moreover, the derived FOV can improve performance significantly.

Hybrid architecture is a promising candidate precoding scheme to balance the achievable spectral efficiency and power consumption in millimeter wave (mmWave) multiple input multiple output (MIMO) systems. A practical partially dynamic subarray-connected architecture is developed to improve the transmission performance. In this proposed architecture, the set of antennas in each subarray is fixed, but the subarrays connected to each radio frequency chain are dynamic. Moreover, we study how to optimize jointly the partially dynamic subarray structure and the hybrid precoders under the constraints of total transmit power and hardware limitation. This joint optimization problem is divided into two sub-problems. For the first sub-problem, a low complexity algorithm is proposed to determine the partition of subarrays using the long-term spatial channel covariance. Then, the penalty decomposition method is adopted to design the hybrid precoders. Numerical results verify that the partially dynamic subarray design algorithm offers one or two orders of computation time saving compared with the existing algorithms. Moreover, the proposed structure achieves spectral efficiency gain using less hardware, compared with the fully dynamic subarray structure adopted in the existing algorithms.

Hybrid architecture is a promising candidate precoding scheme to balance the achievable spectral efficiency and power consumption in millimeter wave multiple input multiple output systems. A practical partially dynamic subarray-connected architecture is developed to improve the transmission performance. In this proposed architecture, the set of antennas in each subarray is fixed, but the subarrays connected to each radio frequency chain are dynamic. Moreover, we study how to optimize jointly the partially dynamic subarray structure and the hybrid precoders under the constraints of total transmit power and hardware limitation. This joint optimization problem is divided into two sub-problems. For the first sub-problem, a low-complexity algorithm is proposed to determine the partition of subarrays using the long-term spatial channel covariance. Then, the penalty decomposition method is adopted to design the hybrid precoders. Numerical results verify that the partially dynamic subarray design algorithm offers one or two orders of computation time saving compared with the existing algorithms, and the hybrid precoding algorithm outperforms the existing algorithms in terms of spectral efficiency. Moreover, compared with the fully dynamic subarray structure adopted in the existing algorithms, the proposed structure achieves spectral efficiency gain and energy efficiency gain using less hardware.

Mobile edge computing (MEC) is considered as an efficient method to relieve the computation burden of mobile devices. In order to reduce the energy consumption and time delay of mobile devices (MDs) in MEC, multiple users multiple input and multiple output (MU-MIMO) communications is considered to be applied to the MEC system. The purpose of this paper is to minimize the weighted sum of energy consumption and time delay of MDs by jointly considering the offloading decision and MU-MIMO beamforming problems. And the resulting optimization problem is a mixed-integer non- linear programming problem, which is NP-hard. To solve the optimization problem, a semidefinite relaxation based algorithm is proposed to solve the offloading decision problem. Then, the MU-MIMO beamforming design problem is handled with a newly proposed fractional programming method. Simulation results show that the proposed algorithms can effectively reduce the energy consumption and time delay of the computation offloading.

With the development of Internet of Things, the mobile edge computing has become a promising technology for real-time communications. This paper investigates a mobile edge computing system that consists of an access point integrated with a mobile edge computing server, multiple mobile stations, and a malicious eavesdropper. By offloading part of the computing tasks to the mobile edge computing server, the energy consumption of mobile stations can be reduced significantly and the lifetime is prolonged as well. Moreover, the physical layer security is an effective technique to guarantee the secure transmission of the offloading data. Based on the proposed system model, we formulate an optimization problem to minimize the energy consumption of the system by jointly optimizing the allocations of local computing tasks, local central processor's frequency, offloading power, and offloading timeslots. A difference of convex algorithm based scheme is proposed to solve the problem. The performance of the proposed scheme is superior to the benchmark schemes, which is demonstrated by simulation results.

High-speed trains are being widely deployed around the world. To meet the high data rate transmission requirements, millimeter wave high-speed train communication systems with large antenna arrays have drawn increasingly attentions. Since channel conditions vary rapidly in high-speed train communication scenarios, frequent channel estimation is required. Moreover, due to the limit period of each transmission time interval, the key challenge in channel estimation is to design an efficient beam searching scheme to allow more time for data transmission. This paper formulates the beam searching problem into a multi-armed bandit problem, and proposes a bandit inspired beam searching scheme to reduce the number of measurements. The performance of the proposed scheme is evaluated in terms of regret, and simulation results show that the proposed scheme can approach the theocratical limit quickly.

Different from conventional key‐based cryptography schemes, physical‐layer security (PLS) techniques have drawn much attention recently to realise unconditional security from the information theory perspective. As an important performance metric in PLS, the ergodic secrecy rate (ESR) for a multi‐input multi‐output wireless communication network over a Nakagami fading channel is analysed. The network is consisted of a multi‐antenna transmitter (Alice), a multi‐antenna legitimate receiver (Bob), and a multi‐antenna eavesdropper (Eve). By using the selective transmission (ST) at Alice and the maximum ratio combining (MRC) at Bob and Eve, an exact expression of the ESR is derived. However, due to the infinite summation, it is very hard to evaluate the ESR performance. To reduce computational complexity and obtain more insights, a lower bound of the ESR is then obtained, which is in a closed form. As special cases, the lower bounds of the ESR for the signal‐antenna scenario and Rayleigh fading channel are also obtained, respectively. Numerical results show that the derived expressions of the ESR and its lower bound are very accurate to evaluate system performance.

In this paper, we investigate the physical-layer security for a spatial modulation (SM)-based indoor visible light communication (VLC) system, which includes multiple transmitters, a legitimate receiver, and a passive eavesdropper (Eve). At the transmitters, the SM scheme is employed, i.e., only one transmitter is active at each time instant. To choose the active transmitter, a uniform selection (US) scheme is utilized. Two scenarios are considered: one is with non-negativity and average optical intensity constraints and the other is with non-negativity, average optical intensity, and peak optical intensity constraints. Then, lower and upper bounds on the secrecy rate are derived for these two scenarios. Besides, the asymptotic behaviors for the derived secrecy rate bounds at high signal-to-noise ratio (SNR) are analyzed. To further improve the secrecy performance, a channel adaptive selection (CAS) scheme and a greedy selection (GS) scheme are proposed to select the active transmitter. Numerical results show that the lower and upper bounds of the secrecy rate are tight. At high SNR, small asymptotic performance gaps exist between the derived lower and the upper bounds. Moreover, the proposed GS scheme has the best performance, followed by the CAS scheme and the US scheme.

We study the uplink achievable rate of full-duplex (FD) multiuser multi-input multi-output (MIMO) systems with a base station (BS) and users over Rician fading channels, based on maximum ratio combining (MRC) receivers. Contrary to previous related works over Rayleigh fading channels, this paper assumes that the fast fading MIMO channel matrix follows the Rice distribution which will be more common in future 5G wireless communication systems. A lower bound expressions of the uplink achievable rate for perfect channel state information (CSI) can be derived when the number of BS antennas grows large. Based on the theoretical analysis, it is found that when the antennas of the BS are large enough and the power scaling law is applied properly, the impact of multi-user interference (MUI), loop interference (LI) and noise can be suppressed. In addition, the simulation results show that the uplink sum achievable rates increase with the number of BS antennas and they will converge to fixed values with the increasing Rician K-factor.

As a novel statistical model, Málaga distribution is proposed recently, which covers many commonly used fading models as special cases. The secure transmission of information over the Málaga fading channels has not been discussed in literature. In this paper, the secrecy outage probability (SOP) over the Málaga fading channels is investigated. Initially, an exact expression of the SOP is derived, which is with an integral term and can not be easily used in practice. To reduce its computational complexity, a closed-from expression for the lower bound of the SOP is then obtained. Numerical results that illustrate the effect of the Málaga fading on system performance are provided. The accuracy of the performance analysis is verified by simulations.

Exact outage probability analysis for equal-gain combining (EGC) over lognormal fading channels results in multi-fold integrals, and traditional asymptotic analysis techniques cannot work for lognormal fading channels due to the channels' infinite diversity order. In this work, we derive a closed-form asymptotic outage probability expression for dual-branch EGC over correlated lognormal fading channels with different statistics. The new result reveals insights into the long-standing problem of asymptotic analysis for correlated lognormal fading channels, paving the way for analysis on more general channel models. The result also provides an efficient way to evaluate the performance of dual-branch EGC over correlated and nonidentically distributed lognormal channels at high signal-to-noise ratio.

Existing indoor positioning methods for visible-light communication systems require large database, powerful signal processing units, additional sensors, such as gyroscopes, or the receiver placed toward a certain angle. These assumptions limit the applications of the indoor positioning systems in low-cost scenarios. In this paper, we propose a novel positioning framework based on the angle differences of arrival (ADOA) in 3-D coordinate systems, which can be used in receivers with image sensors or photodiodes. The proposed ADOA positioning does not require the receiver to be placed toward a certain angle and no additional sensor is required. Two positioning algorithms are proposed: one is based on the method of exhaustion (MEX), and the other is based on the least squares method (LSM). The MEX algorithm is analytically proved to be the optimal, while the LSM algorithm has much lower complexity. Both the upper and lower bounds are derived for the average discrepancy between the exact position and the estimated position. These performance bounds can facilitate the design of a light-emitting diode array. Experimental results show that the MEX algorithm can achieve an average error of 3.20 cm with a time cost of 0.36 s, and the LSM algorithm can achieve an average error of 14.66 cm with a time cost of 0.001 s.

This paper investigates the physical-layer security for an indoor visible light communication network consisting of a transmitter, a legitimate receiver, and an eavesdropper. Both the main channel and the wiretapping channel have non-negative inputs, which are corrupted by additive white Gaussian noises. Considering the illumination requirement and the physical characteristics of lighting source, the input is also constrained in both its average and peak optical intensities. Two scenarios are investigated: one is only with an average optical intensity constraint and the other is with both average and peak optical intensity constraints. Based on the information theory, closed-form expressions of the upper and lower bounds on secrecy capacity for the two scenarios are derived. Numerical results show that the upper and lower bounds on secrecy capacity are tight, which validates the derived closed-form expressions. Moreover, the asymptotic behaviors in the high signal-to-noise ratio (SNR) regime are analyzed from the theoretical aspects. At high SNR, when only considering the average optical intensity constraint, a small performance gap exists between the asymptotic upper and lower bounds on secrecy capacity. When considering both average and peak optical intensity constraints, the asymptotic upper and lower bounds on secrecy capacity coincide with each other. These conclusions are also confirmed by numerical results.

Prior asymptotic performance analyses are based on the series expansion of the moment-generating function (MGF) or the probability density function (PDF) of channel coefficients. However, these techniques fail for lognormal fading channels because the Taylor series of the PDF of a lognormal random variable is zero at the origin and the MGF does not have an explicit form. Although lognormal fading model has been widely applied in wireless communications and free-space optical communications, few analytical tools are available to provide elegant performance expressions for correlated lognormal channels. In this paper, we propose a novel framework to analyze the asymptotic outage probabilities of selection combining (SC), equal-gain combining (EGC), and maximum-ratio combining (MRC) over equally correlated lognormal fading channels. Based on these closed-form results, we show: 1) the outage probability of EGC or MRC becomes an infinitely small quantity compared to that of SC at high signal-to-noise ratio (SNR); 2) channel correlation can cause an infinite performance loss at high SNR; and 3) negatively correlated lognormal channels can outperform the independent lognormal channels. The analyses reveal insights into the long-standing problem of asymptotic performance analyses over correlated lognormal channels, and circumvent the time-consuming Monte Carlo simulation and numerical integration.

This paper considers the problem of transmission scheduling of delay-sensitive data over a point-to-point correlated Rayleigh fading channel with channel estimation errors. According to the imperfect channel state information (CSI) and the buffer state, the transmit power and the modulation and coding scheme (MCS) are determined to jointly maximize the energy efficiency, and minimize transmission delay and overflow probability. To account of the effects of the channel estimation errors, the CSI imperfection is modeled as uncertain sets using the ellipsoidal approximation. Then the joint optimization problem is formulated using the weighted sum method. Using the idea of online learning, two algorithms are proposed to schedule the delay-sensitive data for the situations with and without the uncertainty bound of channel estimation, respectively. The numerical results indicate that the proposed online learning based scheduling algorithms can tackle the imperfect CSI issue and improve the system performance in terms of the energy efficiency, transmission delay and overflow probability. Moreover, the convergence times are very short, which highlights the feasibility of the proposed online learning based scheduling for practical systems.

Recently, optical spatial modulation (OSM) has been proposed for indoor optical wireless communications (OWC), which is considered as a feasible complementary solution for high data rate transmission. This paper investigates the constellation optimization problem for OSM based OWC. An OWC system with multiple transmitters and multiple receivers is considered. By using OSM, only a single transmitter is active at each time instance. Considering the non-negativity and the peak optical intensity constraints, the constellation space for OSM based OWC system is established. By exploiting the channel state information at the transmitter, this paper designs the multi-dimensional constellations by maximizing the minimum Euclidean distance between the received constellation points. Two feasible algorithms are proposed to solve the optimization problem. To evaluate the performance of the proposed algorithms, the symbol error rate is also derived. Simulation results show that the derived constellations using the proposed two algorithms outperform the existing uniformly distributed constellations.

Prior visible-light communication (VLC) positioning systems require the receiver to be placed towards a certain angle, or extra sensors like gyroscopes must be equipped to estimate the angle of the receiver. In this work, we propose a positioning scheme using cameras based on angle difference of arrival (ADOA). ADOA-based positioning does not need the receiver to know its tilting angle, and the position estimation is modeled as a three-variate optimization problem in a finite search region, which is tractable in most smart devices. Our experimental and numerical results show that the ADOA-based VLC positioning scheme achieves accuracy of centimeters and the average cost time is as low as 0.2 seconds.

In this paper, an indoor visible light communication (VLC) system with the input-dependent noise is considered. In the system, the main noise is caused by Gaussian noise, however, with a noise variance depending on the current input signal strength. In the presence of the input-dependent noise, the theoretical expression of the bit error rate (BER) for the VLC using on-off keying is derived. Based on the derived BER, an optimization problem is formulated to improve the BER performance by tilting the receiver plane. The proposed optimization problem is proven to be a convex optimization problem, which can be efficiently solved by using the specialized solver such as the CVX toolbox for MATLAB. To verify the accuracy of the derived expression of the BER, all theoretical results are thoroughly confirmed by using the Monte-Carlo simulations. Moreover, simulation results show that the larger the variance of the input-dependent noise is, the worse the BER performance becomes. Additionally, the BER performance can be dramatically improved by tilting the receiver plane properly.

This paper presents an enhanced hybrid asymmetrically clipped optical orthogonal frequency division multiplexing (OFDM) scheme referred to as EHACO-OFDM. The scheme uses asymmetrically clipped optical OFDM (ACO-OFDM) on the odd subcarriers, pulse-amplitude-modulated discrete multitone modulation (PAM-DMT) on the imaginary parts of even subcarriers, and direct-current-biased optical OFDM (DCO-OFDM) on the real parts of even ones. Since the entire available bandwidth is utilized for data modulation, this scheme can achieve higher spectral efficiency than HACO-OFDM and ACO-OFDM. Moreover, as a smaller DC bias is introduced in our scheme, it is more power efficient than asymmetrically clipped DC-biased optical OFDM (ADO-OFDM) and DCO-OFDM. Simulation results show that EHACO-OFDM performs much better than ADO-OFDM and HACO-OFDM at high bit rates.

In this paper, we focus on a dimmable visible light communication (VLC) system using PIN photodiodes. In such a system, the main distortion is caused by additive Gaussian noise, however, with a noise variance depending on the current signal strength. Under the non-negativity, peak power and dimmable average power constraints, the lower and upper bounds on the channel capacity are derived, respectively. Specifically, the derivation of the lower bound is based on the fact that the entropy of the output is always larger than the entropy of the input, while the derivation of the upper bound relies on the dual expression of the channel capacity and the notion of capacity-achieving input distribution that escape to infinity. Numerical results show that the gap between the lower and upper bounds is very small in the VLC application zone.

This paper aims to derive the upper and lower bounds for the channel capacity of dimmable visible light communications (VLC) systems. Because the information is modulated into the instantaneous optical intensity of light emitting diodes (LEDs), the transmitted optical intensity signal is represented by a nonnegative input, which is corrupted by an additive white Gaussian noise. Considering the illumination support and LED device ability in VLC systems, the transmitted optical intensity signal must satisfy the illumination and the allowed peak optical intensity constraints. With these constraints, a lower bound on the channel capacity is derived through the maximum mutual information between the channel input and output, which is determined by the source entropy maximization. By applying the dual expression of capacity, an upper bound on channel capacity is derived. Both the upper and lower bounds are presented as the closed forms. The numerical results show that the presented bounds are very tight. Moreover, the peak optical intensity constraints will result in the loss of channel capacity. However, such capacity loss is so small that it can be negligible when the allowed peak optical intensity is twice of the nominal optical intensity of LED devices.

In the last 2 years, all‐optical relaying techniques for free‐space optical (FSO) communications have drawn considerable attention. In this study, the outage performance of an FSO communication system with parallel all‐optical relays is investigated. A composite channel is established, which includes atmospheric loss, pointing error and atmospheric turbulence. To show the impact of the channel state information (CSI) on system performance, either full CSI or semi‐blind CSI at the relay nodes is considered. After that, the theoretical expressions of the outage probabilities for different scenarios are derived. Numerical results show that the derived expressions are quite accurate to evaluate the system performance. Moreover, the derived results demonstrate that the systems with semi‐blind CSI relaying can provide comparable performance to systems with full CSI relaying, and also indicate that the performance over strong turbulence channels with clear weather outperforms that over weak turbulence channels with light fog.

The transmitted optical intensity in visible light communications (VLC) system is represented by a nonnegative input, which is corrupted by an additive white Gaussian noise. In this paper, we consider that the transmitted optical intensity signal must satisfy the illumination constraint to fulfill the illumination support in VLC system. So the average transmitted optical intensity is constrained by a target illumination intensity which is determined by the nominal optical intensity of light source devices and the dimming target. The derivation of the upper bound is based on signal space geometry via a sphere-packing argument. The lower bound is derived through the maximum mutual information between the channel input and output, which is determined by the source entropy maximization. Both the bounds are presented in terms of the closed forms. The numerical results show that the presented bounds are very tight at the application zone of dimmable VLC links.

This paper studies the system uplink outage probability in distributed antenna systems (DAS). Firstly, owing to the complexity of actual wireless environments, this paper establishes a composite channel model which takes path loss, lognormal shadowing and Rayleigh fading into account. Then, the probability density function (PDF) of the output signal-to-noise ratio (SNR) is derived. After that, an analytical expression of the uplink outage probability for the MS over a given position is obtained after employing the selective transmission (ST) scheme. Further, considering the distribution of MSs in the cell, a closed-form expression of the system outage probability is derived. Numerical results show that the closed-form expression of the system outage probability can provide sufficient precision for evaluating the outage performance of DAS.