Federated Learning enables large-scale collaborative training across distributed devices. However, in massive-scale Internet-of-Things (IoT) deployments, ensuring the trustworthy sensor-level operations remains a critical challenge. We introduce a hierarchical framework that combines a three-tier architecture (devices → gateways → server) with a high-speed recursive proof system to enforce scalable zero-knowledge proofs (ZKPs). At the device level, each proof serves as a unified cryptographic commitment, binding the device’s identity, local data integrity, and training correctness into a single attestation. These proofs are then individually verified at intermediate gateways, and compressed into a single, succinct proof using a folding scheme inspired by Nova [1] - a state-of-the-art system that can excel at this task at best. The server then verifies a small number of batched proofs before aggregation, reducing workload (∼ 571× in data load) by replacing hundreds of thousands of individual proof and model update transmissions with just one per gateway. Our fully implemented R1CS precursor demonstrates resilience against various vectors (e.g., backdoor-style attacks,) achieves a ∼ 34× verification speedup on a 105-device network, and maintains both strong security and model performance. Our prototype, evaluated on an Internet-of-Vehicles (IoV) use case, demonstrates that recursive proofs add succinct overhead while providing scalable, robust integrity guarantees against adversarial environments.

This paper proposes a novel quantum key distribution (QKD) set-up designed to enhance the security of a free-space optical (FSO) quantum communication system. By incorporating channel ordering information, the proposed QPSK-QKD (P-QPSK-QKD) system leverages the inherent randomness of FSO channels, providing dual protection against eavesdroppers (Eve). The first layer of security is achieved through the QPSK-QKD mechanism, while the second arises from the randomness of the FSO channels. To ensure a comprehensive investigation, the performance of P-QPSK-QKD and the existing QPSK-QKD (E-QPSK-QKD) system is analyzed using a Málaga distributed atmospheric turbulence channel model incorporating pointing errors. Novel closed-form expressions are derived for different performance metrics, including probability of sifted keys, quantum bit error rate, probability of Eve (Peve), and ergodic secret key rate (ESKR), under both perfect and imperfect feedback conditions. Intensive examination indicates that, unlike E-QPSK-QKD, wherePeveshows a water-falling trend with increasing signal-to-noise ratios (SNR) under dual thresholds, P-QPSK-QKD achieves a saturatedPeve, enhancing security. Moreover, under the single threshold,Peveof P-QPSK-QKD is twice that of E-QPSK-QKD. Additionally, due to channel randomness, the mutual information between Alice and Eve remains zero (for both single and dual thresholds), even at infinite SNR for P-QPSK-QKD, providing consistently higher ESKR than E-QPSK-QKD system under both perfect and imperfect feedback conditions.

Federated Learning (FL) enables multiple participants to collaboratively train a shared model without sharing their private data. However, FL remains vulnerable to malicious clients submitting incorrect updates to disrupt training. To address this, we formalize each client’s local training step as a Nondeterministic Polynomial-time (NP) statement, verifiable via zero-knowledge proofs (ZKPs) at every round. We propose Jolt-FL, the first general-purpose verifiable FL framework that immediately detects and excludes malicious clients upon their first dishonest action – without relying on heuristics, statistical assumptions, or multi-round analysis. Built on Jolt’s zkVM, a state-of-the-art zero-knowledge virtual machine (zkVM) developed by a16zcrypto, Jolt-FL guarantees training integrity and data privacy without trusted hardware or third-party intermediaries. By witnessing every computation step, it defends against a wide range of attack vectors, securely filtering dishonest updates even if up to 50% of clients are malicious, while preserving convergence and final model performance. To demonstrate feasibility, we implement a prototype featuring a complete end-to-end Convolutional Neural Network (CNN) for image classification using the MNIST dataset. To our knowledge, this is the first fully verifiable end-to-end CNN training under ZKPs without any custom circuit design. Our solution achieves competitive proof generation times, compact proof sizes, and low verification costs–all while preserving model accuracy on par with standard FL.

This paper investigates resource allocation for optical intelligent reflecting surfaces (OIRS) on high-altitude platforms (HAPs) supporting multiple UAV-mounted base stations. We propose a rate-optimized spatial resource allocation (R-SRA) scheme that first maximizes the number of QoS-guaranteed UAVs, then allocates remaining OIRS elements to boost the total system rate. Numerical results show R-SRA outperforms conventional methods, even with UAV mobility.

In this paper, two techniques including uplink positioning and multiple-input multiple output (MIMO) singular value decomposition (SVD) beamforming are proposed and utilized to provide a novel physical layer security (PLS) scheme for visible light communication (VLC) systems, which much enhance the integrated location-sensing and data security strength. The paper first develops a closed-form mathematical model for ubiquitous uplink positioning using a single light-emitting diode with the trilateration algorithm, considering the field-of-view constraints due to the user’s optical transmitter and access point receivers. SVD in MIMO VLC is subsequently introduced to exploit the acquired user’s location to form a pair of public and private keys for secure data transfer over the physical medium. The proposed system performance is evaluated in terms of the root mean square positioning error$\varepsilon _{\mathbb {X}}$and the achieved bit error rate (BER) for the uplink positioning and the downlink data transmission, respectively. Results show that the effective area of the photodiode significantly impacts$\varepsilon _{\mathbb {X}}$, with smaller areas resulting in higher$\varepsilon _{\mathbb {X}}$. It is also observed that the$\varepsilon _{\mathbb {X}}$directly relates to the strength of ambient light inducing noise in the system. However, the proposed uplink positioning is less prone to natural ambient light as compared to the traditional downlink visible light positioning. The BER analysis of the downlink data transmission shows that the proposed SVD-based PLS enhances the system’s confidentiality by significantly narrowing the communication zone area by over 90% in comparison to the zero-forcing beamforming scheme and achieves reasonable secrecy capacity.

This paper proposes a joint design of probabilistic constellation shaping (PCS) and precoding to enhance the sum-rate performance of multi-user visible light communications (VLC) broadcast channels subject to signal amplitude constraint. In the proposed design, the transmission probabilities of bipolarM-pulse amplitude modulation (M-PAM) symbols for each user and the transmit precoding matrix are jointly optimized to improve the sum-rate performance. The joint design problem is shown to be a complex multivariate non-convex problem due to the non-convexity of the objective function. To tackle the original non-convex optimization problem, the firefly algorithm (FA), a nature-inspired heuristic optimization approach, is employed to solve a local optima. The FA-based approach, however, suffers from high computational complexity. Thus, using zero-forcing (ZF) precoding, we propose a low-complexity design, which is solved using an alternating optimization approach. Additionally, considering the channel uncertainty, a robust design based on the concept of end-to-end learning with autoencoder (AE) is also presented. Simulation results reveal that the proposed joint design with PCS significantly improves the sum-rate performance compared to the conventional design with uniform signaling. For instance, the joint design achieves$\mathbf {17.5\%}$and$\mathbf {19.2\%}$higher sum-rate for 8-PAM and 16-PAM, respectively, at 60 dB peak amplitude-to-noise ratio. Some insights into the optimal symbol distributions of the two joint design approaches are also provided. Furthermore, our results show the advantage of the proposed robust design over the non-robust one under uncertain channel conditions.

Uncrewed Aerial Vehicle-mounted Base Stations (UAV-BSs) have been envisioned as a promising solution to enable high-quality services in next-generation mobile networks. With inherent flexibility, one key challenge is placing the UAV-BSs adaptively to time-varying network conditions to maintain stable connections. Conventional methods mainly focus on optimizing UAV-BS deployment in static networks where users are static or with limited mobility. This study considers a dynamic network where multiple non-stationary UAV-BSs are deployed to serve mobile users with time-varying heterogeneous traffic. Incomplete downloads of users are backlogged in download queues at the UAV-BSs, and together with the newly requested traffic, the download queue size reflects the user’s instantaneous traffic demand. With constraints on the queue stability, we aim to maximize the user’s long-term mean opinion score (MOS), reflecting how the perceived data rate satisfies their traffic demand. Since the users’ location and traffic demand vary over time, we dynamically group users into clusters using a K-means-based algorithm and adjust the 3D location of UAV-BSs using an actor-critic deep reinforcement learning (DRL) framework. The actor module is encoded using a deep neural network (DNN) that obtains the UAV-BS’s current location and a traffic heatmap of users to predict the optimal movement for UAV-BSs. The critic module utilizes Lyapunov optimization to control the queue stability constraint and evaluate the actor’s decisions. Extensive simulations demonstrate the proposed method’s superior performance over conventional rate-maximization approaches.

This paper proposes a joint design of probabilistic constellation shaping (PCS) and precoding to enhance the sum-rate performance of multi-user visible light communications (VLC) broadcast channels subject to signal amplitude constraint. In the proposed design, the transmission probabilities of bipolar M-pulse amplitude modulation (M-PAM) symbols for each user and the transmit precoding matrix are jointly optimized to improve the sum-rate performance. The joint design problem is shown to be a complex non-convex problem due to the non-convexity of the objective function. To tackle the problem, the firefly algorithm (FA), a nature-inspired heuristic optimization approach, is employed to solve a local optima to the original non-convex optimization problem. The FA-based approach, however, suffers from high computational complexity. Therefore, we propose a low-complexity design based on zero-forcing (ZF) precoding, which is solved using an alternating optimization (AO) approach. Simulation results reveal that the proposed joint design with PCS significantly improves the sum-rate performance compared to the conventional design with uniform signaling. Some insights into the optimal symbol distributions of the two joint design approaches are also provided.

This paper investigates the energy efficiency (EE) of rate-splitting multiple access (RSMA)-based visible light communications (VLC) with confidential private messages. We first formulate an EE maximization problem that takes into account the achievable rate of the common message and the sum secrecy rate of private messages. Due to the fractional non-convex nature of the design problem, an algorithm that leverages the Dinkelbach algorithm and convex-concave procedure (CCP) is proposed to solve local optima. In this study, the channel similarity$S_{C}$and the rate-splitting power allocation ratio$\rho$are jointly considered to evaluate EE performance and trade-offs between the achievable common rate and the sum secrecy rate. Numerical results reveal that when$S_{C}$is below 0.7, the EE saturates at its optimum as$\rho$increases, while when$S_{C}$exceeds 0.7, an optimal$\rho$exists beyond which the EE starts declining. Moreover, it is observed that while the relationship between the sum secrecy rate and$S_{C}$is inversely proportional, it is directly proportional in the case of the common rate.

Federated learning (FL)-enabled digital twin (DT) has recently attracted research attention to bring intelligent applications. However, enabling the FL-enabled DT in vehicular networks becomes challenging due to vehicle mobility’s impact on communication channels. In this regard, we propose to deploy an unmanned aerial vehicle (UAV) as a relay node to support the vehicular network. The objective is to minimize energy consumption under the trade-off with the latency and accuracy constraints of the DT model via a joint optimization of local accuracy, the local computation frequency, relay decision, and transmission power. To do so, we derive instantaneous formulas to update the accuracy and latency constraints, then solve the proposed problem using an iterative algorithm with convex optimization techniques. Numerical results show that the proposed dynamic optimization for UAV-aided vehicular networks can reduce up to 39.9% of consumption energy compared to conventional methods.

Physical layer security (PLS) offers a unique approach to protecting information confidentiality against eavesdropping by malicious users. This paper studies a joint design of adaptive M−ary pulse amplitude modulation (PAM) and precoding for performance improvement of PLS in visible light communications (VLC). It is known that higher-order modulation results in a better secrecy capacity at the expense of a higher bit-error rate (BER). On the other hand, a proper precoding design can also enhance secrecy performance. The proposed design, therefore, aims at the optimal PAM modulation order and precoder to maximize a utility function that takes into account the secrecy capacity and BERs of the legitimate user (Bob)’s and the eavesdropper (Eve)’s channel. Due to the lack of a closed-form expression for the utility function, a Q-learning-based design is proposed and evaluated. Compared to the non-adaptive approach under all different settings of Bob’s and Eve’s positions, simulation results verify that the proposed joint adaptive design achieves a good balance between the secrecy capacity and BER of Bob’s channel while maintaining a sufficiently high BER of Eve’s channel.

Mobile Edge Computing (MEC) is a key technology towards delay-sensitive and computation-intensive applications in future cellular networks. In this paper, we consider a multi-user, multi-server system where the cellular base station is assisted by a UAV, both of which provide additional MEC services to the terrestrial users. Via dual connectivity (DC), each user can simultaneously offload tasks to the macro base station and the UAV-mounted MEC server for parallel computing, while also processing some tasks locally. We aim to propose an online resource management framework that minimizes the average power consumption of the whole system, considering long-term constraints on queue stability and computational delay of the queueing system. Due to the coexistence of two servers, the problem is highly complex and formulated as a multi-stage mixed integer non-linear programming (MINLP) problem. To solve the MINLP with reduced computational complexity, we first adopt Lyapunov optimization to transform the original multi-stage problem into deterministic problems that are manageable in each time slot. Afterward, the transformed problem is solved using an integrated learning-optimization approach, where model-free Deep Reinforcement Learning (DRL) is combined with model-based optimization. Via extensive simulation and theoretical analyses, we show that the proposed framework is guaranteed to converge and can produce nearly the same performance as the optimal solution obtained via an exhaustive search.

This paper proposes a new implementation of the BBM92 protocol in satellite continuous-variable quantum key distribution (CV-QKD) systems using dual-threshold/direct detection (DT/DD). The proposed method is less complex and thus possibly cheaper than current discrete-variable (DV) and CV-QKD systems using coherent detection. We model and analyze the performance of the proposed system in the context that a satellite distributes secret keys to two legitimate users. The analytical results are derived by considering the channel loss, atmospheric turbulence-induced fading, and receiver noises. The Gaussian beam model is considered to evaluate the impact of geometrical spreading on the signal received by legitimate users and the possibility of being eavesdropped on. Based on the design criteria for the system and analytical results, we find suitable parameters for the transmitter and the receivers to properly achieve the QKD function for distributing secret keys between two legitimate parties.

A large-scale multiple-input multiple-out (LS-MIMO) transmission technique with low-resolution analog-to-digital converters (ADCs) has become one of the promising techniques for 5G and future wireless networks. In this paper, we first present the mathematical derivation to fit the high-order 4-ary Amplitude Shift-Keying (ASK) superposition modulation scheme in the conventional deep-learning LS-MIMO signal detector designed previously for the binary phase-shift-keying (BPSK) modulation scheme. Importantly, we also propose a two-step deep-learning detection network that does not require training the network again when changing the modulation order, for example, from BPSK to 4-ary ASK and more, provided that the MIMO configuration is kept unchanged. The two-step model offers a low computing requirement and shorter processing time and still achieves better bit error rate (BER) performance over the one-step architecture. The essential attribute of the proposed two-step detector is that no further training is needed makes it promising for the Internet of Things, where devices with a low computing capacity are embedded. Moreover, the advantages of the two-step deep-learning detector also open up a great possibility to deploy the adaptive modulation transmission scheme to enjoy the channel gain variation of wireless fading channels.

In this paper, we newly present a closed-form expression for the bit-error rate (BER) of an M-ary pulse-amplitude modulation (M-PAM) over additive white Gaussian noise (AWGN) channels by analytically characterizing the bit decision regions and positions. The obtained expression is then used to derive the conditional BER of a rectangular quadrature amplitude modulation (QAM) for a given value of phase noise. Numerical results show that the impact of phase noise on the conditional BER performance is proportional to the constellation size. Moreover, it is observed that given a constellation size, the square QAM is more resilient to phase noise in the sense that it achieves the lowest phase noise-induced performance loss compared to other rectangular constellations.

In this paper, an energy-efficient precoding scheme is designed for multi-user visible light communication (VLC) systems in the context of physical layer security, where users' messages are kept mutually confidential. The design problem is shown to be non-convex fractional programming, therefore Dinkelbach algorithm and convex-concave procedure (CCCP) based on the first-order Taylor approximation are utilized to tackle the problem. Numerical results are performed to show the convergence behaviors and the performance of the proposed solution for different parameter settings.

This paper addresses the link-layer error-control solutions of high platform altitude (HAP)-aided relaying satellite free-space optical (FSO) systems for the Internet of Vehicles. Specifically, we propose a design of cooperative incremental redundancy (IR) hybrid automatic repeat request (HARQ) protocol to mitigate the transmission errors over the turbulence fading channels. The performance metrics, including average throughput and average frame delay, are analytically derived. The numerical results confirm the effectiveness of our proposed cooperative IR-HARQ protocol in FSO-based satellite-HAP-vehicle systems and support the proper selection of parameters. Monte-Carlo simulations are also performed to validate the correctness of theoretical results.

Physical layer security (PLS) has recently gained a lot of attention in the research and development of visible light communication (VLC). In this article, we study the designs of PLS in VLC systems in the presence of multiple unauthorized users (i.e. eavesdroppers) using artificial noise (AN)-aided precoding. The design objective focuses on minimizing the total transmit power subject to specific constraints on the signal-to-interference-plus-noise ratios (SINRs) of the legitimate and unauthorized users. In particular, two design approaches are investigated considering the availability of unauthorized users' channel state information (CSI) at the transmitter. In the case of unknown CSI, the AN is constructed to lie on the null-space of the legitimate user's channel. The design problem is convex, thus, can be effectively solved. When the CSI is available, the design additionally imposes constraints on the maximum allowable unauthorized users' SINRs. The design problem, in this case, is, nevertheless, non-convex. Therefore, instead of finding the optimal solution, we examine two different sub-optimal yet low-complexity approaches to solve the problem, namely: Concave-Convex Procedure (CCP) and Semidefinite Relaxation (SDR). Additionally, robust designs that take into account channel uncertainty are also investigated. Extensive numerical results are shown to demonstrate the feasibility and performance of each design with practical parameters.

Satellite-based Internet access for the whole globe, a newly emerging market, has recently received much attention from both academia and industry. In this paper, we present an analytical investigation of transmission control protocol (TCP), which is the most popular protocol for various Internet applications, in free-space optical (FSO) communications based low earth orbit (LEO) satellite systems. Specifically, the throughput performance of the potential deployed TCP variants for high-speed and long-distance of FSO-based satellite networks, namely TCP Hybla and TCP Cubic, are analyzed. Additionally, the incremental redundancy hybrid automatic repeat request (IR-HARQ) protocol is employed to enhance the system performance over satellite-to-vehicles FSO links. The numerical results quantitatively demonstrate the impact of atmospheric turbulence on the TCP throughput and show that TCP Cubic outperforms Hybla in the low error-rate conditions while Hybla provides the better performance when the transmission errors happen more frequently. Monte Carlo simulations are also performed to validate the accuracy of theoretical derivations.

In this paper, we study the performance of unmanned aerial vehicle (UAV)-based free-space optical (FSO) systems over atmospheric turbulence channels considering the pointing misalignment and UAV hovering. The Gamma-Gamma distribution is used for modeling the turbulence-induced fading and the Gaussian beam is assumed for laser beam between two UAVs at the low and high altitudes. A closed-form expression for the symbol error probability is derived and validated by Monte-Carlo simulations. The selected results show the impact of some key factors such as UAV position and beam-waist on the system performance so that the practical system parameters can be determined.

This paper focuses on the free-space optics (FSO) links between high-altitude platforms (HAPs) and unmanned aerial vehicles (UAVs) which have not been addressed in the literature. In the considered system model, a HAP and a UAV play the roles as a transmitter and a receiver, respectively. The UAV is in operation when it is within the beam coverage of the HAP. This work aims to model the HAP-UAV FSO channel taking into account the effects of both the atmospheric turbulence and the pointing error caused by the UAV's hovering. A Gaussian beam model is assumed for the laser transmitted from the HAP and the log-normal distribution is adopted for the atmospheric turbulence-induced fading. For performance analysis, the outage probability and outage capacity versus the distance from the UAV to the center of the received Gaussian beam footprint are numerically investigated. Moreover, Monte-Carlo simulations are also performed to verify the numerical results.

The use of free-space optical (FSO) systems as secure transmission media has recently attracted research efforts worldwide. However, their secrecy performance may be compromised by the presence of an adversarial eavesdropper. In addition, misalignments between transceivers could severely affect the legitimate FSO channel and increase eavesdropping risks. This paper, for the first time, offers a complete framework to analyze the impact of an eavesdropper's location on the secrecy performance of terrestrial FSO systems under generalized misalignments and atmospheric turbulence conditions. Particularly, the probability density functions (PDFs) of the eavesdropping channel are newly developed and presented in closed-form expressions. Capitalizing on the derived PDFs, secrecy performance metrics in the physical-layer security (PLS) and intensity modulation/direct detection (IM/DD) continuous-variable quantum key distribution (CV-QKD) systems can be analytically analyzed, incorporating all combined effects of the atmospheric turbulence, transceiver misalignments, receiver noises, and the eavesdropper's location. Monte-Carlo (MC) simulations are also implemented to corroborate the analytical results.

This paper studies the error-control protocol design for free-space optical (FSO) burst transmission in satellite communication systems. Specifically, we model and analyze the throughput performance of LEO-to-ground FSO systems over atmospheric turbulence channels when incremental redundancy hybrid automatic repeat request (IR-HARQ) protocols, which combine rate-compatible punctured convolutional (RCPC) code and sliding window ARQ, are employed. For this purpose, the time-varying behavior of atmospheric turbulence channels is first captured by a finite-state Markov chain. Then, the channel model is used to develop the burst loss model for IR-HARQ in order to analytically derive the system throughput. The results quantitatively show the impact of atmospheric turbulence on the throughput performance and support the optimal selection of system parameters. Monte Carlo simulations are also performed to validate the accuracy of theoretical derivations.

This paper proposes a high-altitude platform (HAP)-aided relaying satellite free-space optics (FSO) quantumkey distribution (QKD) system for the secure vehicular networks supporting unmanned vehicles (UAV) and regular vehicles. The subcarrier intensity modulation (SIM) binary phase shift keying (BPSK) and dual-threshold/direct detection (DT/DD) receiver are employed. The relaying HAP is equipped with optical amplifyand-forward (OAF) relaying node. We analytically derive the ergodic secret-key rate of the proposed system under the impact of atmospheric turbulence and other noises. Gaussian beam model is used to evaluate the impact of geometrical spreading on the signal received by the legitimate users and the probability of being eavesdropped. The numerical results confirm the feasibility of the proposed system.

This paper studies multi-user multi-cell visible light communications networks in which each cell is composed of multiple light emitting diode (LED) arrays. The use of multiple LED transmitters enables each cell to support multiple users by means of precoding techniques. In such multi-user multi-cell networks, the signal for each user can be severely interfered not only by the signals that are intended to other users in the same cell, i.e., intra-cell interference, but also by the signals for users of the other cells, i.e., inter-cell interference. While intra-cell interference can be handled by the underlying precoding scheme, it is hard to deal with the inter-cell one. This paper focuses on cell coordination/cooperation strategies and their corresponding coordinated/cooperative precoder designs as the approaches to alleviate, or possibly, to cancel out the inter-cell interference. We first derive lower and upper bounds on the capacity of Gaussian interference channels with amplitude constraints on the input and the interference. Capitalizing on derived bounds and the zero-forcing scheme as the underlying precoding technique, optimal coordinated/cooperative precoding designs to maximize users' sum-rate are investigated under the non-negativity and amplitude-limited constraints on the channel inputs. The comprehensive numerical results are presented to compare the performance of the considered coordination/cooperation strategies.

Clustering is widely used for exploratory data analysis in a variety of applications. Traditionally clustering is studied as an unsupervised task where no human inputs are provided. A recent trend in clustering is to leverage user provided side information to better infer the clustering structure in data. In this paper, we propose a probabilistic graphical model that allows user to provide as input the desired cluster sizes, namely the cardinality constraints. Our model also incorporates a flexible mechanism to inject control of the crispness of the clusters. Experiments on synthetic and real data demonstrate the effectiveness of the proposed method in learning with cardinality constraints in comparison with the current state-of-the-art.

Multiple-instance learning is a framework for learning from data consisting of bags of instances labeled at the bag level. A common assumption in multi-instance learning is that a bag label is positive if and only if at least one instance in the bag is positive. In practice, this assumption may be violated. For example, experts may provide a noisy label to a bag consisting of many instances, to reduce labeling time. Here, we consider generalized multi-instance learning, which assumes that the bag label is non-deterministically determined based on the number of positive instances in the bag. The challenge in this setting is to simultaneous learn an instance classifier and the unknown bag-labeling probabilistic rule. This paper addresses the generalized multi-instance learning using a discriminative probabilistic graphical model with exact and efficient inference. Experiments on both synthetic and real data illustrate the effectiveness of the proposed method relative to other methods including those that follow the traditional multiple-instance learning assumption.

The present paper introduces a novel construction of structured ternary sequences having a zero-correlation zone (ZCZ) for both periodic and aperiodic correlation functions. The cross-correlation function and the side lobe of the autocorrelation function of the proposed sequence set are zero for phase shifts within the ZCZ. The proposed ZCZ sequence set can be generated from an arbitrary Hadamard matrix of order ℓh. For m > 0, the sequence set of order (m+1) is constructed from the sequence set of order m by sequence concatenation and interleaving. The sequence set of order m has 2 × 4msubsets of size ℓh. The length of the sequence is equal to 4 (8m(ℓh+1)+2m(4m-1) /3). The phase shift of the ZCZ for the entire sequence set is from -(2m-1) to (2m-1). The sequence set of order 0 is coincident with the rows of the given Hadamard sequence with no ZCZ. The subsets can be associated with a perfect quadtree of height m with 4mleaves. The r-th sequence subset is associated with the r-th leaf. For a longer distance between the corresponding leaves to the r-th and s-th sequences, the ZCZ of the r-th and s-th sequences is wider. This tree-structured width of ZCZ of a pair of the proposed sequences enables flexible design in applications of the proposed sequence set. The proposed sequence is suitable for a heterogeneous wireless network, which is a candidate for the fifth generation of radio access networks.

Long Term Evolution (LTE) networks are expected to play a key role in providing connections to billions of Machine-Type Devices (MTDs) in the 5G big picture. Since the ALOHA-based access framework of LTE-A alone cannot support bursty massive access scenarios caused by the MTDs, the 3GPP has additionally employed the Access Class Barring (ACB) scheme as the baseline traffic control method. While the scheme certainly improves access success probability of the devices, corresponding delay degradation may be unacceptable. In this paper, we renounce the ALOHA-based framework of LTE to propose a new protocol, namely the Free Access Distributed Queue (FADQ), accompanied by an estimation method to resolve the massive synchronized access issue in a more efficient manner. Simulations under the 3GPP's reference setup show that FADQ protocol significantly reduces access delay while maintaining an access success probability on par with the ACB.

Active Constellation Extension (ACE) is widely used to reduce Peak-to-Average Power Ratio (PAPR) in Offset Quadrature Amplitude Modulation based Orthogonal Frequency Division Multiplexing (OFDM/OQAM). To improve overall performance and energy efficiency in OFDM/OQAM systems, this paper proposes Adaptive Scaling (AS) for effective ACE (AS-ACE). The proposed scheme exploits the overlapping structure of the OFDM/OQAM signals and jointly considers adjacent data blocks to obtain the clipping noise. The proposed scheme adaptively extends the constellation points to effectively eliminate peaks in OFDM/OQAM signals. This is achieved by using peak samples of clipping noise, used to generate the peak correcting signal. Least square approximation algorithm is used to fit the waveform of peak correcting signal to the waveform of clipping noise without any decrease in the constellation distance. Simulation results show that the AS-ACE reduces PAPR and Bit Error Rate (BER) and improves convergence speed compared to OSGP technique without requiring increased processing or additional information at the receiver end.

HTTP adaptive streaming (HAS) has become popular for delivering videos over the Internet. However, most HAS services are currently based on the traditional HTTP/1.1, which has limitations for live streaming. Meanwhile, the new HTTP/2 was standardized in 2015 with many improvements. In this letter, we present a novel HTTP/2-based adaptation scheme for low-delay live streaming over mobile networks. The proposed scheme leverages two HTTP/2 features called server push and stream termination to enable a shorter camera-to-display delay. Experimental results with small buffer sizes show that our scheme can provide users with high video bitrate and stable buffer level. Furthermore, the buffer size in live streaming can be reduced to two sec without sacrificing video quality.

This paper investigated the comparative performance of different cell cooperation strategies for multi-cell multi-user visible light communications (VLC) networks. In practical deployment of VLC, multiple LED arrays are deployed to provide sufficient illumination for large rooms/offices. As a consequence, multi-cell configurations are a natural progression for indoor VLC networks. In this study, to support multiple users simultaneously by means of precoding technique, each VLC cell is formed by 4 separated LED arrays. In such multi-cell networks, a user can be severely interfered not only by the signals that are intended to other users within the cell (intra-cell interference) but also by the signals for users of the other cells (inter-cell interference). In order to suppress these interferences, cell cooperation can be applied for precoder designs. We consider several strategies of cell cooperation and investigate the design of optimal precoding matrix corresponding to each cooperative strategy to maximize the achievable sum capacity of users. Comprehensive numerical results are shown to compare the performance of the considered cooperation strategies.

This paper proposes a novel two-way free-space quantum key distribution (QKD) protocol, which can be implemented using standard free-space optical (FSO) systems with subcarrier intensity-modulation (SIM) binary phase-shift-keying (BPSK) and direct-detection (DD) receiver. Different eavesdropping threats, including unauthorized receiver, beam-splitting, and intercept-resend attacks, are considered in the security analysis of the proposed protocol. Under the constraints on security requirements, we analytically investigate the design criteria for transmitter and receiver, in particular, the intensity modulation depth at the transmitter and the dual-threshold setting of the receiver in two-way free-space QKD systems. Quantum bit error rate (QBER), the ergodic secret-key rate, and the probability of detecting eavesdropper of the proposed system are analytically derived in closed-form expressions, considering the atmospheric loss, turbulence, and receiver noises.

In this paper, we propose a new adaptation approach for viewport-adaptive streaming of 360-degree videos over the Internet. The proposed approach is able to systematically decide quality levels of tiles according to user head movements and network conditions by taking into account not only prediction errors but also user head movements in each adaptation interval. Experimental results show that the proposed approach can effectively adapt 360-degree videos to both varying network conditions and user head movements. Compared to existing approaches, the proposed approach can improve the average viewport quality by up to 3.9dB and reduce the standard deviation of the viewport quality by up to 50%.

Hidden‐tag problem is one of the most important issues in the implementation of radio‐frequency identification (RFID) systems. Due to effects of imperfect wireless channels, RFID tags can be hidden during the identification process by either another tag or an unsuccessful detection. The former is known as the capture effect (CE) while the latter is the detection error (DE). This study newly proposes two modified tree‐based identification protocols, namely tweaked binary tree (TBT) and tweaked query tree (TQT), which are able to tackle the hidden‐tag problem caused by both the CE and DE. The performance of the proposed TBT and TQT protocols, in terms of the average number of slots required to detect a tag, and the tag‐loss rate, is evaluated in comparison with that of previously proposed ones. Computer simulations and numerical results confirm the effectiveness of the proposed protocols.

This paper studies zero-forcing (ZF) precoding designs for multi-user multiple-input single-output visible light communication (VLC) broadcast channels. In such broadcast systems, the main challenging issue arises from the presence of multi-user interference (MUI) among non-coordinated users. In order to completely suppress the MUI, ZF precoding, which is originally designed for radio frequency (RF) communications, is adopted. Different from RF counterpart, VLC signal is inherently non-negative and has a limited linear range, which leads to an amplitude constraint on the input data signal. Unlike the average power constraint, obtaining the exact capacity for an amplitude-constrained channel is more cumbersome. In this paper, we first investigate lower and upper bounds on the capacity of an amplitude-constrained Gaussian channel, which are especially tight in the high signal-to-noise regime. Based on the derived bounds, optimal beamformer designs for the max-min fairness sum-rate and the maximum sum-rate problems are formulated as convex optimization problems, which then can be efficiently solved by using standard optimization packages.

In this paper, we present an approach for learning in the semi-supervised setting in the presence of novel class instances. In this setting, data consists of a labeled portion and an unlabeled portion that contains novel class instances along with unlabeled known class instances. Novel class instances are instances from concepts that do not have labeled training examples. This setting is appropriate for the case in which data is abundant and labeling the entire data is prohibitively expensive. We provide a model and an inference framework that allow for a direct control over the portion of novel class instances in the unlabeled data. Experiments on synthetic data demonstrate the usefulness of the proposed approach. Comparison to state-of-the-art approaches for learning in the presence of novel class instances using unlabeled data illustrates the advantage in using the proposed method in term of accuracy.

Two-way transmission protocol is an efficient method to overcome the spectral loss incurred due to half-duplex communication. In this paper, we propose to implement two-way transmission in an amplify-and-forward (AF) relaying free-space optical (FSO) system utilizing an AF relay with optical amplifier. The performance of the proposed FSO system using subcarrier intensity modulation (SIM) with intensity modulation/direct detection (IM/DD) over independent but not necessarily identically distributed (i.n.i.d) Malaga (M) atmospheric turbulence channels in presence of pointing errors is studied. Exact closed-form expressions for the moment generating function (MGF) and cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) are obtained in terms of extended generalized bivariate Meijer's G-functions (EGBMGF). Capitalizing on these new results, we derive exact closed-form expressions for various performance metrics of the considered FSO system including the outage probability, the average bit error rate (ABER), and the ergodic achievable-rate. All analytical results are thoroughly confirmed by Monte-Carlo (M-C) simulations.

This paper proposes a novel operation for hybrid Free Space Optics (FSO)/Radio Frequency (RF) systems. We add a new function to current hybrid systems, which is responsible for operation mode selection (OMS). A dynamic OMS policy is proposed by taking intelligent control decisions at the transmitter taking into account states of both queue and channel (i.e. queue-aware and channel- aware). System performance metrics are analytically studied based on a combination of queuing and Markov chain theories. Numerical results quantitatively show how the proposed operation outperforms the conventional ones.

This paper presents a concept of parallel Free-Space Optics/Millimeter-Wave (FSO/MMW) systems, in which adaptive rate is employed in both FSO and MMW links. We newly propose an analytical framework based on Markov chain model for system performance analysis. System performance metrics, including throughput and reliability rate, are analytically studied under the presence of various weather conditions. Numerical results quantitatively show how the adaptive-rate FSO/MMW significantly outperform conventional ones, and how weather conditions affect on the systems performance.

This paper proposes a new RFID binary tree-based identification protocol, namely Tweaked Binary Tree (TBT), to cope with hidden tag problem caused by capture effect and detection error phenomena. In TBT, the whole identification process is divided into multiple binary tree cycles, and the hidden tags in a cycle are checked and re-transmitted in the first slot of the next one. The average number of slots for a successful detection of a tag, and the tag loss rate, defined as a ratio between the number of missing tags and the whole tag cardinality, are theoretically analyzed. Computer simulations are also performed to validate the theoretical analysis. We also confirm the superiority of the proposed method in comparison with a conventional General Binary Tree (GBT) one.

In integrated free-space optical/passive optical networks (FSO/PON), providing efficient media access control (MAC) protocol and ensuring high reliable transmission are two major challenging issues. This paper comprehensively addresses these issues through a protocol stack design, which jointly considers the dynamic bandwidth allocation (DBA), adaptive rate (AR) transmission, and automatic repeat request (ARQ) with different retransmission strategies. A 2-D Markov chain model is developed to qualify quality-of-service (QoS) performance metrics in terms of frame loss probability, throughput and delay. Selected numerical results show that the proposed protocol stack design can offer considerable performance improvement over conventional ones.

A common framework of identifying bird species from audio recordings involves detecting bird song segments, which will be subsequently input to a classifier. In-field recordings are contaminated with various environmental noise. For such recordings, supervised segmentation has been observed to outperform unsupervised energy-based approaches. Prior supervised segmentation work considers only pixel-level predictions and ignores the supervision provided at the segment-level. We propose a hierarchical approach that learns to isolate bird song syllables based on both pixel-level and segment-level information. Experimental results suggest that our method outperforms an existing supervised method that learns only from pixel-level supervision.

This paper proposes two novel medium access control (MAC) protocols, which jointly employ bandwidth allocation and adaptive rate concepts, to enhance the performance of uplink transmission of the integrated free-space optical/passive optical networks (FSO/PON). System performance metrics, including frame-loss rate, goodput and delay, are analytically studied under the presence of atmospheric turbulence. Numerical results quantitatively show how the proposed protocols significantly outperform the conventional one with fixed bandwidth allocation/fixed rate.

In this paper, we newly propose and theoretically analyze the performance of all-optical amplify-and-forward (OAF) relaying free-space optical (FSO) systems using erbium-doped fiber amplifier (EDFA) combined with optical hard-limiter (OHL) over atmospheric turbulence channels. The use of OHL enables OAF relaying FSO systems to remove accumulated background noise, which is one of the main factors that limit the system performance. The performance of proposed systems is analytically studied by which closed-form expression for bit-error rate (BER) is formulated, taking into account the effects of atmospheric turbulence channels and noises caused by background radiation and receiver. The numerical results, which are validated by Monte-Carlo (M-C) simulations, confirm the superiority of the proposed systems in comparison with conventional ones.

Multi-instance multi-label learning (MIML) is a framework for learning in the presence of label ambiguity. In MIML, experts provide labels for groups of instances (bags), instead of directly providing a label for every instance. When labeling efforts are focused on a set of target classes, instances outside this set will not be appropriately modeled. For example, ornithologists label bird audio recordings with a list of species present. Other additional sound instances, e.g., a rain drop or a moving vehicle sound, are not labeled. The challenge is due to the fact that for a given bag, the presence or absence of novel instances is latent. In this paper, this problem is addressed using a discriminative probabilistic model that accounts for novel instances. We propose an exact and efficient implementation of the maximum likelihood approach to determine the model parameters and consequently learn an instance-level classifier for all classes including the novel class. Experiments on both synthetic and real datasets illustrate the effectiveness of the proposed approach.

We study the use of moment generating function (MGF) method to approximate the distribution of the sum of independent, but not necessarily identical, Gamma-Gamma variables, which is crucial in performance evaluation of multiple- input multiple-output (MIMO) free-space optical (FSO) systems. We show that the MGF-based approximation method can flexibly provide sufficient accuracy in the upper and lower tails of the cumulative distribution function (CDF) for both identically and non- identically distributed cases. Comparisons to highlight the advantages of the proposed method over existing ones are also presented. We then apply the proposed method to analytically derive closed-form expressions for the outage probability and average bit-error rate of MIMO-FSO systems. Monte-Carlo simulations are also performed to validate analytical results.

In this paper, we theoretically analyze the performance of a dual-hop fixed-gain amplify-and-forward (AF) system with mixed millimeter-wave radio-frequency (MMW RF) and free-space optics (FSO) links. The system is considered as a high-capacity, scalable and cost-effective backhaul solution for the 5G cellular- based vehicular networks. MMW RF and FSO channels are respectively modeled by the Ricean and Gamma-Gamma fading channels. Novel closed-form expressions for the end-to-end outage probabilities of the proposed system under various impacts of the transmission channels are analytically derived. Numerical results validate the mathematical analysis by Monte-Carlo (M-C) simulations and perform a comprehensive outage performance analysis of the proposed system.

We investigate the primary user emulation (PUE) attack, which is a serious security problem in cognitive radio (CR) networks. There exist three types of PUE attackers: 1) a selfish one, which aims at maximizing its selfish usage of channel resource; 2) a malicious one, which points for obstructing the operation of CR network; and 3) a mixed one, which is between a selfish and malicious PUE attacker. For combating a selfish PUE attacker, a channel surveillance process has to be implemented in order to determine active user's identification and so selfish PUE attacker. An extra-sensing process has to be implemented for observing new opportunities to access the channel and so for mitigating the malicious PUE attacker's effect. Relevant strategies for deploying the above processes are obtained through a game theory-based analysis and the exhibition of Nash equilibrium (NE). We show the NE strongly depends on the network demand, the availability of the spectrum resource, and the type of the attacker.

This paper analytically studies the performance of selection decode-and-forward (DF) cooperative free-space optical communication (FSO) systems, employing adaptive subcarrier quadrature amplitude modulation (SC-QAM) and taking into account the fading effect caused by atmospheric turbulence. Closed-form expressions of outage probability, spectral efficiency and bit-error rate (BER) are derived, using a novel accurate series approximation method. Numerical results highlight the improvement of the proposed system compared with all-active relaying and non-adaptive FSO systems. The validity of the analytical method is also confirmed by Monte-Carlo simulations.

Atmospheric turbulence is one of the main impairments degrading the performance of free-space optical (FSO) systems. Similar to radio-frequency communications, the use of spatial diversity techniques in FSO can significantly mitigate the fading effect caused by atmospheric turbulence. In this paper, closed-form expressions for the average capacity of multiple-input-multiple-output FSO systems over strong atmospheric turbulence using Gamma-Gamma fading channel model are presented. Our analysis is carried out for both equal gain combining and maximal ratio combining diversity techniques. Numerical examples compare analytical and simulation results, quantitatively verifying the advantages of spatial diversity techniques.

A novel method is presented to analyse the effects of atmospheric turbulence and misalignment fading (or pointing error) on performance of serial‐relaying M ‐ary pulse‐position modulation (PPM) free‐space optical (FSO) systems. This study is more comprehensive than previous ones, since the effect of beam size variation due to turbulence by using the partially coherent Gaussian beam model is taken into account. In addition, a closed‐form expression is formulated for bit error rate of serial‐relaying M ‐ary PPM FSO systems over Gamma–Gamma atmospheric turbulence channel, taking into account the effects of atmospheric attenuation, extinction ratio and signal‐dependent noise. The authors find that the laser source's coherent parameter, which governs the beam size at the receiver, plays an important role in the system design. If this parameter is not chosen properly, the system impairment will be either dominated by pointing error or geometric spreading loss. Thanks to the use of serial‐relaying and M ‐ary PPM, the effects of atmospheric turbulence and misalignment fading is mitigated; hence the ability of combating atmospheric turbulence and the transmission distance of FSO systems are significantly improved. In addition, useful information for system design, such as the required number of relays for a specific turbulence strength and transmission distance, could be obtained from the numerical results.

This study studies the performance of multihop free‐space optical systems using the subcarrier binary phase‐shift keying modulation over atmospheric turbulence channels. The authors propose a modified relaying strategy, termed ‘amplify–decode‐and‐forward’, realised by using avalanche photodiode (APD) receivers. The outage probability of the proposed system is analytically derived considering the atmospheric turbulence and the receiver noise, including APD shot noise and thermal noise. The analytical results are verified by Monte Carlo simulations, and a good agreement between the analytical and simulation results is confirmed. In the authors’ analysis, they quantitatively discuss the impact of turbulence strength, number of relay nodes, relaying configuration, system bit rate and receiver parameters on the system outage probability. In addition, the optimal value of APD gain for achieving the lowest outage probability in different cases of relaying configuration, number of relays and receiver parameters is also discussed.

HTTP streaming has become a cost-effective means for multimedia delivery nowadays. For adaptivity to networks and terminals, a provider should generate multiple representations of an original video as well as the related metadata. Recently, there have been various adaptation methods to support adaptive HTTP streaming. In this paper, we investigate typical adaptation methods in the context of live video streaming. We first discuss the trade-off among typical adaptation methods. The evaluation and comparison are then carried out not only in terms of bitrate and buffer behaviors but also in terms of the perceptual impact on end users. It is found that the perceptual impact depends not only on adaptation method but also on the content itself. We also show that the preparation of representation sets may affect the behaviors of some adaptation methods.

We theoretically analyze the performance of free-space optical (FSO) multiple-input multiple-output (MIMO) systems using rectangular sub-carrier quadrature modulation (SC-QAM) signaling. The systems's average symbol-error rate (ASER) is derived taking into account the atmospheric turbulence effects on the FSO MIMO channel, which is modeled by lognormal and the gamma-gamma processes for the cases of weak-to-strong turbulence conditions. We quantitatively discuss the influence of turbulence strength, link distance and different MIMO configurations on the ASER. We also derive and discuss the FSO MIMO average (ergodic) channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE), under the impact of various channel conditions.

In this study, the authors theoretically study the performance of direct‐detection free‐space optical communication systems using binary phase‐shift keying subcarrier‐intensity modulation and avalanche photodiode (APD). The system bit‐error rate and channel capacity are theoretically derived in cases of log‐normal and gamma‐gamma channel models for weak‐to‐moderate and moderate‐to‐strong atmospheric turbulence conditions, respectively. The authors quantitatively discuss the optimal values of the APD average gain, required transmitted optical power, and operating bit‐rate considering various turbulence conditions, APD shot noise and thermal noise. It is seen that, although the impact of turbulence is severe, a proper selection of APD average gain could significantly improve the system performance in both cases of turbulence channels. The optimal value of APD average gain remains almost the same for different levels of turbulence; nevertheless it varies significantly in accordance to the change of receiver noise temperature.

In this paper, we present a comprehensive study of the effects of atmospheric turbulence, including intensity fluctuation and pulse broadening, on the performance of FSO/CDMA systems. A realistic model of Gaussian pulse propagation is used for analyzing the bit error rate (BER). The numerical results show that pulse position modulation (PPM) with high modulation level should not be used for FSO/CDMA systems as it requires to send high chip rate (i.e., short pulse), which is significantly affected by pulse broadening effect. To overcome the limitation of PPM, we propose to use multi-wavelength PPM (MWPPM), which achieves high modulation level by combining PPM and wavelength shift keying. By using MWPPM, the effects of both intensity fluctuation and pulse broadening are mitigated thus the BER is reduced. In addition, we found that the performance of FSO/CDMA systems using MWPPM can be further improved and lower BER can be achieved by using avalanche photodiode with the gain around 80 to 100.

In this paper, we comprehensively study the performance of direct-detection free-space optical (FSO) communication systems using subcarrier binary phase-shift keying (SC-BPSK) modulation and avalanche photodiode (APD). The system bit-error rate is theoretically derived in case of two atmospheric turbulence channel models: the log-normal and gamma-gamma ones for the weak-to-moderate and moderate-to-strong turbulence conditions, respectively. We quantitatively discuss the optimal values of the average APD's gain, required received optical powers and operating bit-rates considering various turbulence conditions, APD shot noise and thermal noise. It is seen that the effect of temperature on the value of optimal gain is stronger than that of the turbulence. We also find that the impact of turbulence is severe; however using APD receiver with optimal average gain can significantly improve the system performance in both cases of turbulence channels.

Previous works show that pulse-position modulation (PPM) is an effective signalling method for mitigating multiple-access interference, and hence is able to increase the number of users in two-dimensional (2-D) optical code-division multiple-access (OCDMA) systems. However, in order to achieve high bit-rates, 2-D OCDMA systems using PPM signalling require very high transmitted power because of the negative impact of dispersion. In this study, the authors propose a novel modulation technique of multi-code PPM (MCPPM), which is the combination of the PPM and multi-code modulation (MCM). As the proposed technique inherits advantages from both MCM (in mitigating the dispersion) and PPM, 2-D OCDMA systems using MCPPM signalling are able to support higher user bit-rates for a larger number of users at low transmitted powers. Numerical results show that 2-D OCDMA systems using 4-4-MCPPM can support 60 users with 5 Gbps per user at the transmitted power of −7 dBm. The power gain in this case is 11 dB compared to 2-D OCDMA systems using 4-PPM signalling. The proposed systems using 4-2-MCPPM can support as many as 36 users with the bit-rate of 10 Gbps per user and transmitted power is −2 dBm.

In OCDMA systems, pulse position modulation (PPM) and multi-code modulation (MCM) have been proven as efficient methods for respectively mitigating multiple access interference (MAI) and dispersion. In this paper, we propose to combine PPM and MCM to create a novel modulation scheme, multi-code pulse position modulation (MCPPM). We then theoretically analyze the performance of the 2-D OCDMA system using MCPPM over a linear dispersive channel, while taking into account the negative impact of MAI, optical-beating interference (OBI), and receiver noise. It is seen that the use of MCPPM can simultaneously relax the effects of MAI, OBI, and dispersion. As a result, in comparison to the conventional systems using PPM and MCM, the one using MCPPM can support a higher user bit rate and a larger number of users. Also, a lower transmitted power can be achieved.

This paper proposes a novel two-dimensional wavelength hopping/time spreading (WH/TS) optical code division multiplexing (2-D WH/TS OCDM) system using prime sequences and a heterodyne detection receiver for broadband optical multiple access networks (OMAN). The performance of the proposed system is theoretically analyzed taking into account various kinds of noise and interference, including multiple access interference (MAI), optical beating interference (OBI), crosstalk and receiver noise. The prime sequences are used as the signature codes for both wavelength hopping and time spreading. Both symmetric and over-colored asymmetric systems are considered. Analytical results show that the proposed system offers much better performance compared with that of a conventional 2-D WH/TS system using direct-detection. As a matter of fact, the OBI is well suppressed in the proposed system resulting in a considerable increase in the number of supportable users. Moreover, the system's sensitivity is significantly improved enabling the proposed system to be a promising candidate for the broadband OMAN deployed using the passive optical network (PON) configuration.