Onboard IoT edge computing provides a real-time and efficient platform for levitation control of the high-speed maglev train. Aiming at the stability control problem of levitation systems, a closed-loop control framework integrating Transformer networks with Model Predictive Control (MPC) to enhance levitation stability and dynamic response performance is proposed. To handle time-varying dynamics and disturbances, an edge-deployed temporal Transformer network predicts short-horizon system states, improving MPC optimization within finite prediction horizons. Simultaneously, safety constraints are introduced with the combination of Control Barrier Function (CBF) method, ensuring critical variables, including levitation gap, remain within safe bounds. The framework covers nonlinear dynamics, linearized system equations, Transformer-based forecasting, MPC design with constraints, and CBF-embedded safety control. Experiments on the hardware-in-the-loop test platform demonstrate significant performance improvements over traditional methods: maximum deviation reduced by 50%, recovery time shortened by 60%, and response speed increased by 50%, while maintaining safety during high-speed operation. However, these results were obtained in a simulated environment rather than under actual operating conditions at 600 km/h, and the effects of aerodynamic disturbances at 600 km/h still require further investigation in subsequent research.

Salient object detection (SOD) is a fundamental component of unmanned aerial vehicle (UAV) vision systems, as it enhances autonomous perception and facilitates precise target localization. However, achieving an optimal balance between model efficiency and detection accuracy remains a significant challenge, particularly in resource-constrained scenarios such as UAVs. To address this issue, a lightweight SOD framework enhanced with edge information is proposed, aiming to achieve both high efficiency and high precision under limited computational resources. First, an edge-aware depthwise separable convolution module is introduced to replace conventional encoder operations, thereby enhancing spatial detail preservation while reducing computational cost. Second, a novel Edge Feature Enhancement Module is designed to extract fine-grained edge features from encoder outputs and to guide the decoder in reconstructing object with higher accuracy. Third, an edge-integrated loss function is developed by incorporating edge supervision into the standard cross-entropy loss, thereby further improving the model’s capability to delineate salient object boundaries. Extensive experiments conducted on multiple benchmark SOD datasets demonstrate that the proposed method achieves competitive, and in some cases superior, performance compared to existing state-of-the-art lightweight models, while maintaining low computational complexity. The proposed framework provides a promising solution for real-time and energy-efficient SOD in low-power computing environments.

With the emerging privacy sensitive applications, anonymity is recognized as an important attribute in privacy-preserving communications. Existing anonymous precoding approaches at the physical (PHY) layer aim to mask sender’s channel characteristic while overlooking the fact that other PHY characteristics contain information that can be traced back to the sender. In this paper, we first reveal that the sender’s in-phase and quadrature-phase imbalance (IQI) characteristic of its radio frequency (RF) front end can also be exploited as unique signature of the sender. Since the signal is transmitted through the RF front end and then is propagated through the channel, the received signal carries the composite characteristics of the IQI and channel which can be exploited to identify the sender. To prevent the sender detection enhanced by IQI, an IQI aware anonymous alias sender construction scheme is proposed with the concept of Kullback-Leibler divergence (KLD). It manipulates the signaling of transmitted signal, so that from the perspective of detector, the detection statistic of the real sender is close to that of the alias. To mitigate the communication performance loss caused by the IQI, we exploit the IQI interference as a constructive element. While the constructive IQI design increases the degree of freedom of precoding design, it does not violate the sender anonymity requirement. Finally, an IQI aware anonymous precoder (IAA) is proposed. Simulation demonstrates that the anonymity and communication performance of the proposed IAA precoder is maintained at a high level and is robust to the IQI parameters, where existing approaches fail.

To address the challenges of information leakage, low energy efficiency, and the Doppler effect in mobile Internet of Vehicles (IoV), this paper proposes an enhanced IoV cooperation framework, where privacy information is forwarded by the untrusted relay assisted by unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS), which can improve security and energy efficiency. To meet the requirements of green communication, we formulate a secrecy energy efficiency maximization problem by jointly optimizing the transmit power allocation, the relay’s amplification factor, the two-hop RIS phase shift matrices, and the UAV trajectory. Given the non-convex nature of this problem, we introduce an iterative algorithm based on the convex-concave procedure and Dinkelbach’s method to optimize the transmit power and amplification factor. Additionally, we conceive the majorization-minimization (MM) algorithm to optimize the two-hop RIS phase shift matrices, and a designed firefly algorithm-deep deterministic policy gradient (FA-DDPG) algorithm is proposed to obtain the UAV trajectory. Simulation results demonstrate the effectiveness of the proposed scheme in enhancing secrecy energy efficiency. Specifically, compared to the DDPG-only and FA-based schemes, the proposed scheme achieves an improvement of 33.3% and 64.2%, respectively, in secrecy energy efficiency.

In recent years, joint radar and communication (JRC) systems have garnered significant attention due to their enhanced equipment utilization and high spectrum efficiency. This paper investigates a JRC-enabled multi-UAV cooperative system, where multiple UAVs concurrently execute communication tasks for communication users (CUs) and perception tasks for sensed targets (STs) distributed across a specified region. To strike the trade-off between the communication performance and sensing accuracy, we formulate a weighted performance optimization problem aimed at simultaneously maximizing the data transmission for CUs and minimizing the squared position error bound (SPEB) for STs, by jointly optimizing user association and channel assignment, power allocation, as well as UAV deployment. To effectively address this challenging problem, we initially recast the non-differentiable objective function into a more tractable and interpretable form with the aid of smooth approximation techniques. Subsequently, by virtue of the specific problem structure, we decompose the original joint optimization problem and develop an iterative method to optimize each subproblem sequentially. Extensive simulations demonstrate the significant performance gains of the proposed design compared to other benchmark schemes.

Time synchronization is critical for time-sensitive cell-free massive MIMO systems, as packet loss from mobility or poor channels degrades performance. In this paper, we propose robust coordinated time synchronization (Co-TS) schemes for the cell-free massive MIMO to combat the impact of packet loss. Specifically, a multi-criteria based AP association mechanism is first proposed where in addition to the large-scale fading factor, the effects of received signal strength and packet loss probability are also considered during the AP-device association process. In addition, the fuzzy logic theory is utilized to balance among the three criteria to achieve higher robustness against packet loss over the conventional single-criterion based AP association approaches. After that, a Co-TS model considering both the coordination among APs and the effect of packet loss is developed, where the unsynchronized node can receive a set of timestamps from its associated APs during each synchronization cycle. We use maximum likelihood estimation (MLE) to jointly estimate the clock offset and skew under Gaussian-distributed random delays, and derive their closed-form Cramér-Rao Lower Bounds. Simulation results demonstrate that our proposed schemes are robust against packet loss and can significantly enhance time synchronization performance over the existing methods.

In this paper, we consider a practical integrated sensing and communication (ISAC) scenario in industrial Internet of Things (IIoT). In this scenario, a robot acted as a mobile base station (BS) performing sensing to locate a logistics transport robot (LTR) while also communicating with multiple production lines (PL). We predict the motion parameters of LTR in each time slot and derive the Cramér-Rao bound (CRB) of angle and distance estimation. Afterward, we formulate a joint CRB minimization problem by optimizing the transmit beamforming for communication and sensing. We convert the formulated problem into a two-tier alternating optimization approach by constructing precise surrogates for the non-convex objective functions and constraints. A closed-form expression is derived for solving the outer layer problem. In addition, we employ a convex framework to address the inner layer problem. Numerical results validate the superiority of the proposed algorithm, especially when the BS is far away from the sensing target.

In this article, we focus on the resource allocation and autonomous aerial vehicle (AAV) 3-D trajectory design for the AAV-ground base station (GBS) coordinated multipoint nonorthogonal multiple access (CoMP-NOMA) system to maximize the sum-rate of CoMP users while maintaining users’ high Quality of Service requirements. The main contributions of this article are summarized as follows: 1) with the assistance of closed-form power allocation result, a generalized joint user scheduling and power allocation (G-USPA) algorithm is proposed to derive the optimal user scheduling solution; 2) by revealing the monotone increasing relationship between the sum transmit power and the transmit rates of non-CoMP users, the optimal rate of each non-CoMP users turns out to be its inherent minimum required rate, consequently, the optimal transmit rates and power allocation of all users can also be derived; and 3) moreover, considering the Line of Sight (LoS) and non-LoS factors in the air-ground channel, the 3-D trajectory of AAV is designed based on successive convex approximation to provide a flexible user-centric service. The proposed G-USPA algorithm is compatible with the AAV trajectory design, which is optimized alternatively and can lead to fast convergence. Numerical results verify that the 3-D AAV-GBS CoMP-NOMA model and the G-USPA scheme have a superior performance in terms of total system sum rate and the sum rate of CoMP users over the non-CoMP AAV assisted nonorthogonal multiple access (NOMA) systems.

Reconfigurable intelligent surface (RIS) has emerged as a highly promising technology for future wireless sensing applications, primarily due to its capability to dynamically manipulate the incoming signals through meticulous configuration of the RIS profile. This paper delves into the optimal design strategy for the RIS profile, aiming at maximizing the localization accuracy of the non-line-of-sight user within typical downlink orthogonal frequency division multiplexing (OFDM) systems. Assuming prior knowledge of the user’s location, we first derive the measurement model and corresponding position error bound (PEB) for the considered OFDM systems. Subsequently, under the total power budget constraint, we establish a closed-form solution for the optimal covariance matrix of the RIS profile by leveraging the subspace structure information of the channel states. Building upon this, the design of the optimal RIS profile is executed using the time-sharing technique. Taking into account the hardware limitations, we further formulate a more practical RIS profile design problem by incorporating the unit-modulus constraint for each RIS element, which, however, is non-convex and thus hard to tackle. To address this issue, we employ the alternating minimization technique to compute a suboptimal solution for the constrained RIS profile design problem. Simulation results demonstrate the remarkable PEB performance achieved by both the proposed optimal and constrained RIS profile design strategies. It is also illustrated that the proposed constrained RIS profile design surpasses other state-of-the-art alternatives, exhibiting a comparable performance to our devised optimal benchmark.

We study an unmanned aerial vehicle (UAV)-enabled uplink heavy non-orthogonal multiple access (NOMA) system in this paper, where the UL communication becomes extremely important in some hot spot areas such as live concerts or soccer stadiums, and investigate the joint optimization of bandwidth assignment (BA) and power allocation (PA) with UAV three-dimensional (3D) trajectory design to maximize the minimum average rate among all ground users, while meeting their heterogeneous rate requirements. More specifically, we propose a joint BA and PA algorithm by revealing that the inter-user interference in each NOMA group can be eliminated naturally while deriving the sum rate of users. The algorithm is proposed to get the optimal BA and PA solutions with the help of closed-form results and ellipsoid method. After that, in order to solve the UAV 3D trajectory design problem we introduce the elevation angle as a supplementary variable, and the successive convex approximation method is adopted to obtain the UAV 3D trajectory. The joint BA and PA algorithm and the UAV 3D trajectory design can be optimized alternatively, which leads to fast convergence and demonstrates a superior minimum average rate among users and user fairness performance over the previous methods.

The reconfigurable holographic surface (RHS) designs precoding by controlling the amplitude of its radiation elements. The existing RHS-aided precoder treat multiuser interference as a harmful element. However, if the multiuser interference is constructively aligned to the desired signal, it becomes a beneficial element for improving signal’s receive-quality. In this work, we exploit the knowledge of the data to be transmitted and channel state information (CSI), for the purpose of interference utilization. A novel hybrid precoding is formulated for RHS multiuser systems, aiming for maximizing the lower bound of signal-to-interference-plus-noise ratio (SINR) of multiple users. To strike the balance between the complexity and system performance, the optimization problem is decoupled into two convex subproblems i.e., one for optimizing digital precoder and the other for optimizing holographic precoder. Finally, a novel constructive interference (CI) based holographic hybrid precoding algorithm is proposed, which iterates its digital and holographic precoders with a fast convergence rate. Simulation results demonstrate the superiority of the proposed algorithm for enhancing receiving performance against the benchmarks.

While symbol-level (SL) precoders have been shown to improve transmission performance by treating multi-user interference (MUI) as a useful resource, the SL precoders only employ uniform modulation for all downlink users, and the incurred complexity increases linearly with the block length. In this letter, we investigate the possibility of mixed-modulations interference exploitation (IE) for satellite communications, at a sub-block level. By exploiting the specific detection regions of constellation points of different modulations, a novel sub-block level mixed-modulation (BL-MIE) design is proposed, guaranteeing that MUI is always constructive in each sub-block duration, regardless of the users’ heterogeneous modulation schemes. Compared to the classic SL design, it is proved that the BL-MIE provides complexity reduction on the order of square root of the sub-block length, i.e., ${\mathcal{O}}(\sqrt{n})$, with n denoting the number of symbols per sub-block. Hence, it well strikes the balance between the performance and complexity. Simulation demonstrates that the proposed designs significantly outperform the benchmarks in terms of power consumption and throughput performance.

In last decades, joint design of user scheduling and precoding has been investigated for single transmission time interval (TTI). However, this family of single-stage design cannot optimize real-time metrics that are measured in temporal dimension. In this paper, we target on optimizing the experience rate, which is defined as the ratio of a user's data packet size to the total time for completely delivering the user's data. A novel multi-stage dynamic resource programming is formulated as a multi-stage mixed integer nonlinear programming (MINLP) problem. Then, a low-complexity iterative algorithm is proposed for a jointly optimizing user scheduling and precoding. In particular, a second cone programming problem is dedicatedly designed, for providing a high-quality initial point for the iterative algorithm. The simulation results demonstrate that the proposed design endorses enhanced experience rate performance, with fast convergence behavior.

In this paper, we propose an uplink non-orthogonal multiple access (NOMA) based hybrid long-packet and short-packet frame structure for data collection in industrial wireless sensor networks (IWSNs) with heterogeneous quality of service (QoS) requirements of sensors. The proposed NOMA-based hybrid frame structure allows the superimposition between a number of short packets and a long packet during data collection, where the short packets can be firstly decoded to maintain the low-latency requirement, and the long packet is decoded later to achieve a high signal-noise-ratio (SNR). In addition, a joint short packet scheduling and pilot and block length optimization (JSLO) algorithm is proposed to minimize the maximum block error probabilities among short packets while maintaining a high SNR of long packet, with the assistance of optimal closed-form short packet scheduling results and pilot and block length expressions. The JSLO algorithm achieves near-optimal performance and a dramatic complexity reduction compared to exhaustive search and can lead to fast convergence. Numerical results demonstrate the proposed NOMA-based hybrid frame structure and JSLO algorithm can significantly reduce the maximum error probability among short packets and maintain a high level of fairness.

The success of the Internet of Things has recently spread to the industrial sector, commonly referred to as Industrial IoT (IIoT). IIoT, which has a far-reaching impact on the operation of industries around the world, is recognized as a key enabler for the fourth industrial revolution. It has the potential to prompt economic growth and global competitiveness, in terms of improving productivity, efficiency, and so on.

Underwater covert communication (UCC) technology can prevent legitimate transmission from being intercepted upon by potential eavesdroppers while ensuring a certain rate at the receiver under the condition of underwater acoustic channels. Previous studies have focused on UCC designs that rely on fixed transmitters and receivers, with limited attention given to dynamic moving senders, such as the widely-used autonomous underwater vehicle (AUV). Therefore, the establishment of a secure link between the mobile AUV and the receiver remains unexplored. In this paper, we construct an AUV-aided UCC architecture. Specifically, leveraging the unique characteristics of the underwater environment i.e., time-variant channel, severe attenuation, and ambient noise, the AUV plans its trajectory from the settled start point to the destination, adjusting its transmission power for covert communications. Accounting for both green energy consumption and communication security, we develop a novel multi-objective deep deterministic policy gradient (MODDPG) framework for jointly optimizing AUV’s diving energy consumption as well as effective throughput under the covertness constraint. Moreover, we propose an active-trust mechanism at the receiving side to pose an extra safe guard. To handle this, an evolutionary game model between the receiver and eavesdropper is built. Simulations and numerical results demonstrate that our proposed method can achieve a Pareto-optimal solution for covert communications with rapid convergence speed. The evolutionary stable strategy (ESS) enables the receiver to attain superior benefits and security compared to other strategies.

Sketch-based method has emerged as a promising direction for per-flow measurement in data center networks. Usually in such a measurement system, a sketch data structure is placed as a whole at one switch for counting all passing packets, but when summarizing measurement results from multiple switches, the overall accuracy is generally constrained by a few individual switches with small-sized sketches due to their limited memory resources. To address this problem, in this paper, we present Distributed Sketch, a new method for per-flow network measurement in data center networks. In Distributed Sketch, each network path is associated with a logical sketch, whose data structure is collectively maintained by all the switches along the path; meanwhile, each switch multiplexes its physical sketch to the constructions of the logical sketches of all the paths it belongs to. With Distributed Sketch, switches collaborate to measure network flows, and the network-wide measurement workload is fairly distributed among all the switches in the network. We implement Distributed Sketch with P4 on commodity hardware programmable switch, and in particular, to overcome the limitation that hardware switches do not support float-point computation, we present an optimal approximation method that involves only integer operations. We also propose an In-band Network Telemetry (INT) based method for addressing the challenges in deploying Distributed Sketch in large-scale data centers. Experiment results and theoretical analysis show that our proposed method is lightweight regarding measurement overhead, and by aggregating and making fair uses of resources from all the switches in the network, Distributed Sketch achieves a higher measurement accuracy compared with the state-of-the-art solutions.

In this paper, a novel reconfigurable intelligent surface (RIS)-assisted HAP-UAV secure multi-user mixed radio frequency (RF)/free space optical (FSO) system is proposed. Specifically, the Gamma-Gamma distribution is utilized to characterize the atmospheric turbulence effect for the FSO link from UAV to HAP, while the Rayleigh and Nakagami-$m$distribution fading are applied to simulate the legitimate and wiretap RF links, respectively. We present the closed-form expressions for the probability density functions, the cumulative distribution functions, and the secrecy outage probability (SOP) of the end-to-end signal-to-noise ratio (SNR) in terms of Meijer’s G-function. To gain more insight into secrecy performance, we further obtain the closed-form expressions for the asymptotic SOP, the asymptotic probability of positive secrecy capacity (PPSC), the diversity gain, and the coding gain at high SNR regions. We can observe that the secrecy performance depends on the weaker channel between the RF and FSO, and is closely related to the number of RIS elements, the number of terrestrial users, the atmospheric turbulence factor, pointing error parameters, and the fading parameter of Nakagami-$m$distributed wiretap link. Finally, numerical results validate the derived results and demonstrate that the proposed design achieves superior secrecy performance over the benchmarks.

Departing from traditional data security-oriented designs, the aim of anonymity is to conceal the transmitters’ identities during communications to all possible receivers. In this work, joint anonymous transceiver design at the physical (PHY) layer is investigated. We first present sender detection error rate (DER) performance analysis, where closed-form expression of DER is derived for a generic precoding scheme applied at the transmitter side. Based on the tight DER expression, a fully DER-tunable anonymous transceiver design is demonstrated. An alias channel-based combiner is first proposed, which helps the receiver find a Euclidean space that is close to the propagation channel of the received signal for high quality reception, but does not rely on the recognition of the real sender’s channel. Then, two novel anonymous precoders are proposed under a given DER requirement, one being able to provide full multiplexing performance, and the other flexibly adjusting the number of multiplexing streams with further consideration of the receive-reliability. Simulation demonstrates that the proposed joint transceiver design can always guarantee the subscribed DER performance, while well striking the trade-off among the multiplexing, diversity and anonymity performance.

Traditional physical layer secure beamforming is achieved via precoding before signal transmission using channel state information (CSI). However, imperfect CSI will compromise the performance with imperfect beamforming and potential information leakage. In addition, multiple RF chains and antennas are needed to support the narrow beam generation, which complicates hardware implementation and is not suitable for resource-constrained Internet-of-Things (IoT) devices. Moreover, with the advancement of hardware and artificial intelligence (AI), low-cost and intelligent eavesdropping to wireless communications is becoming increasingly detrimental. In this paper, we propose a multi-carrier based multi-band waveform-defined security (WDS) framework, independent from CSI and RF chains, to defend against AI eavesdropping. Ideally, the continuous variations of sub-band structures lead to an infinite number of spectral features, which can potentially prevent brute-force eavesdropping. Sub-band spectral pattern information is efficiently constructed at legitimate users via a proposed chaotic sequence generator. A novel security metric, termed signal classification accuracy (SCA), is used to evaluate the security robustness under AI eavesdropping. Communication error probability and complexity are also investigated to show the reliability and practical capability of the proposed framework. Finally, compared to traditional secure beamforming techniques, the proposed multi-band WDS framework reduces power consumption by up to six times.

We consider a three-dimensional (3D) unmanned aerial vehicle (UAV)-terrestrial base station (TBS) coordinated multi-point non-orthogonal multiple access (CoMP-NOMA) scheme where UAV coordinates with TBS to allow joint transmission for the terrestrial users. With the assistance of closed-form power allocation derivations, a joint user scheduling and power allocation (J-USPA) algorithm is proposed to obtain the optimal user scheduling solution, with the consideration of imperfect channel estimation. Moreover, considering the line of sight (LoS) and non-LoS factors in the air-ground channel, the 3D trajectory of UAV is designed to provide a flexible user-centric service. Numerical results verify that the 3D UAV-TBS CoMP-NOMA model and the J-USPA scheme have a superior performance in terms of sum rate of users over the TBS CoMP-NOMA and the UAV assisted NOMA systems without CoMP transmission.

In this paper, we consider a unmanned aerial vehicle (UAV)-enabled uplink (UL) heavy non-orthogonal multiple access (NOMA) system where the UL communication becomes increasingly important in some hot spot regions such as live concerts or football stadiums, and study the maximization of the minimum average rate among all users by jointly optimizing bandwidth assignment (BA) and power allocation (PA) alongside UAV trajectory design, while meeting their specified heterogeneous rate requirements. Specifically, by revealing that the inter-user interference can be naturally eliminated while deriving the sum rate of users in each NOMA group, an one-step BA and PA algorithm is proposed, with the assistance of closed-form results. Afterwards, the elevation angle is introduced as an auxiliary variable to help solve the UAV trajectory design problem. The joint BA and PA algorithm and the UAV trajectory design can be optimized alternatively, which leads to fast convergence and demonstrates a superior minimum average rate among users and user fairness performance over the previous methods.

Multiplexing or transmission diversity via dual links enables the reduction in age of information (AoI). We address the open issue of selection between the two transmission modes for AoI-oriented short-packet system over fading channels, with a comprehensive analysis. Closed-form expressions for the average AoI and peak AoI (PAoI) are derived based on the discrete-time Markov-chain process. Then, to obtain the explicit region of preference (RoP) and quantitative PAoI gains of multiplexing/diversity over the single-queue case, we derive the signal-to-noise ratio (SNR) threshold for transmission mode selection, which is shown to be a decreasing function of the arrival rate and saturates at high arrival rate. Also, the monotonicity of the PAoI gains by multiplexing and diversity, and their achievable gains, are analyzed in a comprehensive manner. It is shown that diversity is able to achieve a PAoI gain of more than 3 dB over the single-queue case at low SNR, while multiplexing has a larger RoP than diversity and is selected at high SNR and high arrival rate. Furthermore, both throughput and PAoI violation probability are considered alongside the average PAoI for a wide range of tradeoff in system design.

Different from traditional security-oriented designs, the aim of anonymizing techniques is to mask users' identities during communication, thereby providing users with unidentifiability and unlinkability. The existing anonymizing techniques are only designated at upper layers of networks, ignoring the risk of anonymity leakage at physical layer (PHY). In this paper, we address the PHY anonymity design with focus on a typical uplink scenario where the receiver is equipped with more antennas than the sender. With the increased degrees-of-freedom at the receiver side, we first propose a maximum likelihood estimation (MLE) signal trace-back detector, which only analyzes the signaling pattern of the received signal to disclose the sender's identity. Accordingly, an anonymity entropy anonymous (AEA) precoder is proposed, which manipulates the transmitted signalling pattern to counteract the receiver's trace-back detector and meanwhile to guarantee high receive signal-to-interference-plus-noise ratio for communication. More importantly, more data streams can be multiplexed than the number of transmit antennas, which is particularly suitable for the strong receiver configuration. Simulation demonstrates that the proposed AEA precoder can simultaneously provide high anonymity and communication performance.

Multiplexing or transmission diversity via dual queues enables the reduction in age of information (AoI) in industrial Internet-of-Things (IIoT). We address the open issue of how to select between the two transmission modes for AoI-oriented short-packet systems over fading channels. Closed-form expressions for the average peak AoI (PAoI) in the finite block length regime over fading channels are derived based on the average block error probability. The analytical results match the simulation results well. To assist with obtaining the explicit region of preference (RoP) between the multiplexing and diversity modes, the signal-to-noise ratio (SNR) threshold for transmission mode selection is derived, which is shown to be a mono-decreasing function of the arrival rate and to saturate at high arrival rate. The multiplexing mode demonstrates a larger RoP than diversity and is shown to be preferable at high SNR and high arrival rate. While the diversity mode is preferable in the case of low SNR and low arrival rate by presenting a more significant PAoI reduction over the single-queue case.

Given the increasing attention paid to the security of underwater communications, covert communication system has been envisaged as a key enabler for empowering the marine information networks to address the challenge of ever-increasing demand of anti-eavesdropping. However, dynamic underwater hydrology environment and ambient noise make it substantially difficult to reduce the decoding error probability as much as possible on the premise of meeting the concealment requirements. In this paper, we first build up underwater covert communication (UCC) system and analyze its secrecy performance at the physical (PHY) layer. Moreover, we propose a dynamic power-threshold based bargaining game model to preserve the receiver’s concealment, while ensuring high receiver-side signal-to-interface-noise ratio (SINR). The simulation results show the detection probability at the equilibrium of our model is optimal, and thus it is capable of both overcoming the dynamic changes and of increasing the system’s stability significantly by analyzing the time discount factor.

In industrial Internet of Things (IIoT), the existing access class barring (ACB) random access (RA) strategy suffers severe performance degradation with massive contention devices, due to high probability of access collision. In this paper, we propose a collision-aware (CA) ACB RA scheme by reusing the colliding preambles, to enhance the resource utilization. The proposed scheme employs dynamic adjustment of the ACB factor and the preamble resources for delay-sensitive and -non-sensitive devices, respectively. A joint optimization problem is formulated and solved to maximize the preamble utilization ratio (PAUR) subject to the delay constraints and the available preambles. The system performance is evaluated by a Markov Chain based analytical model. Simulation results verify the correctness of our analysis and also show that the proposed CA-ACB RA scheme significantly outperforms the existing ACB RA schemes in terms of PAUR, network throughput, and average access delay.

In this article, we investigate the grant-free communications with adaptive period for Industrial Internet of Things, where only a fraction of devices is active at a time. To the best of our knowledge, this is the first work to exploit the noncontinuous temporal correlation of the received signal for joint user activity detection (UAD), channel estimation, and signal detection, while all the previous work requires continuous transmission. Two schemes are proposed toward this purpose, namely, periodic block orthogonal matching pursuit (PBOMP) and periodic block sparse Bayesian learning (PBSBL), which outperform the previous schemes in terms of the success rate of UAD, bit error rate, and accuracy in period estimation and channel estimation. The Cramér–Rao lower bounds (CRLBs) of channel estimation by PBOMP and PBSBL are derived. It is shown that the two proposed approaches have close CRLBs and normalized mean-square error at high SNR.

In the era of e-Health, privacy protection has become imperative in applications that carry personal and sensitive data. Departing from the data-perturbation based privacy-preserving techniques that reduce the fidelity of the disclosed data, in this paper we investigate anonymous communications, which mask the identity of the data sender while providing high data reliability. Focusing on the physical (PHY) layer, we first explore the break of privacy through a statistical attribute based sender detection (SD) from the receiver. Compared to the existing literature, this enables a much enhanced SD performance, especially when the users are equipped with different numbers of antennas. To counteract the advanced SD approach above, we formulate explicit anonymity constraints for the design of the anonymous precoder, which mask the sender’s PHY attributes that can be exploited by SD, while at the same time preserving the reliability of the data. Then, anonymity entropy-oriented precoders are proposed for different antenna configurations at the users, which adaptively construct a maximum number of aliases while obeying users’ signal-to-noise-ratio requirements for data accuracy. Simulation results demonstrate that the proposed anonymous precoders provide the highest level of anonymity entropy over the benchmarks, while achieving reasonable symbol error rate for the communication signal.

In this paper, we investigate unmanned aerial vehicle (UAV) assisted communication systems that require quasi-balanced data rates in uplink (UL) and downlink (DL), as well as users’ heterogeneous traffic. To the best of our knowledge, this is the first work to explicitly investigate joint UL-DL optimization for UAV assisted systems under heterogeneous requirements. A hybrid-mode multiple access (HMMA) scheme is proposed toward heterogeneous traffic, where non-orthogonal multiple access (NOMA) targets high average data rate, while orthogonal multiple access (OMA) aims to meet users’ instantaneous rate demands by compensating for their rates. HMMA enables a higher degree of freedom in multiple access and achieves a superior minimum average rate among users than the UAV assisted NOMA or OMA schemes. Under HMMA, a joint UL-DL resource allocation algorithm is proposed with a closed-form optimal solution for UL/DL power allocation to achieve quasi-balanced average rates for UL and DL. Furthermore, considering the error propagation in successive interference cancellation (SIC) of NOMA, an enhanced-HMMA scheme is proposed, which demonstrates high robustness against SIC error and a higher minimum average rate than the HMMA scheme.

In-band Network Telemetry (INT) is a novel framework for monitoring network health in real-time, and its recent variant, Probabilistic INT (PINT), reduces its bandwidth consumption with a probabilistic approach. However, as we show in this paper, a PINT task can be successfully accomplished only when it is allocated a sufficient number of packets, and if there are many tasks executed in parallel, packets become a scarce resource. Meanwhile, today’s production network generally executes multiple measurement tasks for tracing different network states simultaneously. Therefore, in such a context, scheduling parallel PINT tasks on one single INT flow that has a limited number of packets becomes a critical problem. In this paper, we address this problem for the first time. We propose an algorithm that efficiently schedules multiple parallel PINT tasks on a flow by allocating the flow’s packets to the tasks and showing that the allocation is optimal. We realize the algorithm with a packet processing pipeline and implement it on software and hardware-programmable switches. Comprehensive evaluation on a FatTree testbed shows that at a low scheduling overhead, our algorithm can conduct parallel PINT tasks to detect various network faults in a timely and accurate manner. Additionally, the algorithm accomplishes more PINT tasks with higher quality than the alternative solutions.

We investigate a multi-device ultra-reliable low-latency communication system with heterogeneous traffic and finite block length over temporally-correlated fading channels. In light of the challenging demand for accurate channel estimation with limited pilot in a short frame, two frame structures, which respectively adopt independent pilots and shared pilot, are investigated. Block lengths and pilot lengths are jointly optimized for the two frame structures, through instantaneous channel state information (CSI) based dynamic optimization and statistical CSI based static optimization, to strike the tradeoffs among performance, complexity and signaling overhead. The proposed joint optimization algorithms significantly outperform the existing approaches that solely optimize block lengths or pilot lengths. The dynamic optimization algorithms achieve near-optimal performance at dramatic complexity reduction over exhaustive search, and maintain robustness against traffic heterogeneity. Also, the static optimization algorithms are conducted offline, while still outperforming the previous instantaneous CSI based dynamic optimization approaches. It is demonstrated that the independent-pilot frame structure with dynamic optimization is preferable in the scenario with high traffic heterogeneity or high mobility, and that the shared-pilot frame structure with static optimization presents a comparable performance to the former in the case of low mobility, incurring negligible complexity and signaling overhead.

We study security solutions for dual-functional radar communication (DFRC) systems, which detect the radar target and communicate with downlink cellular users in millimeter-wave (mmWave) wireless networks simultaneously. Uniquely for such scenarios, the radar target is regarded as a potential eavesdropper which might surveil the information sent from the base station (BS) to communication users (CUs), that is carried by the radar probing signal. Transmit waveform and receive beamforming are jointly designed to maximize the signal-to-interference-plus-noise ratio (SINR) of the radar under the security and power budget constraints. We apply a Directional Modulation (DM) approach to exploit constructive interference (CI), where the known multiuser interference (MUI) can be exploited as a source of useful signal. Moreover, to further deteriorate the eavesdropping signal at the radar target, we utilize destructive interference (DI) by pushing the received symbols at the target towards the destructive region of the signal constellation. Our numerical results verify the effectiveness of the proposed design showing a secure transmission with enhanced performance against benchmark DFRC techniques.

In the era of big data, anonymity is recognized as an important attribute in privacy-preserving communications. The existing anonymous authentication and routing designs are applied at higher layers of networks, ignoring the fact that physical layer (PHY) also contains privacy-critical information. In this paper, we introduce the concept of PHY anonymity, and reveal that the receiver can unmask the sender’s identity by only analyzing the PHY information, i.e., the signaling patterns and the characteristics of the channel. We investigate two scenarios, where the receiver has more antennas than the sender in the strong receiver case, and vice versa in the strong sender case. For each scenario, we first investigate sender detection strategies at the receiver, and then we develop anonymous precoding to address anonymity while guaranteeing high signal-to-interference-plus-noise-ratio (SINR) for communications. In particular, an interference suppression anonymous precoder is first proposed, assisted by a dedicated transmitter-side phase equalizer for removing phase ambiguity. Afterwards, a constructive interference anonymous precoder is investigated to utilize inter-antenna interference as a beneficial element without loss of the sender’s anonymity. Simulations demonstrate that the anonymous precoders are able to preserve the sender’s anonymity and simultaneously guarantee high SINR, opening a new dimension on PHY anonymous designs.

Both information age and delay are critical performance metrics of emerging time-sensitive applications. However, their inherent correlation in the finite block length (FBL) regime has remained uninvestigated as it is affected by block length and update rate in a complex manner. In this paper, closed-form expressions for average age of information (AoI), peak AoI (PAoI) and delay are derived for an FBL Last-Come First-Served system with retransmission and non-preemption policies, based on which a comprehensive analysis of the relationship among the three metrics in the FBL regime is presented. It is proved that there exists a strong tradeoff between delay and AoI/PAoI given a block length, and that AoI, PAoI and delay have positive correlation given an update rate, regardless of the weight. With the goal of minimizing delay and AoI simultaneously, the weighted sum of delay and PAoI (upper bound on AoI) is formulated and proved to be convex with respect to block length and update rate. A low-complexity optimization algorithm is developed with a closed-form expression of the optimal update rate, whose performance approaches the Pareto boundaries of the PAoI-delay and the AoI-delay regions, at much lower complexity than exhaustive search.

In this paper, directional modulation (DM) is investigated to enhance physical layer security. Practical transmitter designs are exploited under imperfect channel state information (CSI) and hardware constraints, such as finite-resolution phase shifters (PSs) and per-antenna power budget. Tailored for the practical issues in realizing DM, a series of practical scenarios are investigated. Starting from the scenario where eavesdroppers (Eve)s' information is completely unknown, corresponding designs are proposed to optimize legitimate users (LU)s' receiving performance while randomizing the Eves' received signal. When the Eves' CSI is imperfectly known, in the second scenario, the Eves' receiving performance is further deteriorated by imposing destructive interference to the Eves. For each scenario, three algorithms are proposed under hardware constraints and imperfect CSI, i.e., one direct-mapping algorithm suitable for high/moderate number of bits in PSs, one heuristic algorithm with improved receiving performance at the cost of complexity, and one iterative-closed-form algorithm with enhanced practicality of symbol-level based DM. Simulation demonstrates that the algorithms achieve lower symbol error rate (SER) at the LUs while significantly deteriorating the Eves' SER, leading to an improved secrecy throughput over the benchmarks.

In this paper, we propose an unmanned aerial vehicle (UAV) base station (BS) assisted communication system for a special event (e.g., a football game) with heterogeneous traffic demands by all users and the uplink (UL)-downlink (DL) rate balancing requirement. With respect to UAV's high mobility, we propose a hybrid mode multiple access (HMMA) strategy where both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) techniques are utilized to meet heterogeneous traffic demands. Specifically, NOMA is utilized to achieve high average data rate, and OMA helps to meet the instantaneous rate demands of users. The proposed HMMA strategy has a high degree of freedom and provides superior minimum average rate across all users and a higher user fairness than the previous work with OMA only or NOMA only, where the instantaneous rate demands of users may not always be guaranteed during UAV's flight time due to dynamic channel changes, the inter-user interference and successive interference cancellation (SIC) error propagation. Furthermore, we investigate joint UL-DL optimization for a UAV assisted wireless system. Based on the channel reciprocity of the air-ground channels, an alternative algorithm is proposed to conduct joint UL-DL optimization of bandwidth assignment and UAV trajectory to accommodate heterogeneous rate demands across users and achieve quasi-balanced average rates in UL and DL.

As mission-critical Internet of Things (MC-IoT) is expected to carry important and private information, its high quality of service (QoS) and high physical layer (PHY) security are indispensable. Nevertheless, most existing PHY security related work is built on the assumption of infinite blocklength, which is not applicable to finite blocklength (FBL) transmission, a typical scenario in MC-IoT such as factory automation. In this paper, we address the PHY security issue of a hybrid duplex relay aided MC-IoT system with FBL. Closed-form expressions for statistical secrecy throughput of full-duplex (FD) and half-duplex (HD) relay systems are derived, respectively, which are verified by numerical results. Based on the closed-form secrecy throughput, joint optimization of blocklength and transmission powers at source and relay is conducted for FD and HD relay systems, respectively. A hybrid duplex relaying scheme is also proposed by selecting the duplex mode with a higher achievable secrecy throughput. Numerical results show that, together with the hybrid relaying scheme, the proposed relay system with joint power allocation and blocklength adaptation, relay mode selection achieves much higher secrecy throughput over the conventional sole FD or HD mode relaying systems. Also, it is revealed that increasing blocklength or transmitting power may not always lead to a higher secrecy throughput and energy efficiency (EE).

We propose an unmanned aerial vehicle (UAV) ground base station (GBS) coordinated NOMA scheme where UAV and GBS jointly serve the cell-edge users. To the best of our knowledge, this is the first work to investigate air-ground BSs coordination for UAV-assisted NOMA systems, by taking advantage of the interference between UAV and GBS. Therefore, the proposed UAV-GBS coordinated NOMA scheme achieves much higher sum rate of cell-edge users than the non-coordinated UAV-assisted NOMA schemes where interference is suppressed as much as possible. The proposed scheme also outperforms GBSs coordinated NOMA due to more flexible and cost-effective interference management, thanks to the deployment of low-cost UAV BS. We conduct joint optimization of power allocation, user scheduling and UAV trajectory for the UAV-GBS coordinated system. A closed-form optimal solution to power allocation is derived. In addition, a dedicated successive interference cancellation (SIC) ordering approach is proposed. It is proven that the selection of a cell-center user with higher SIC order contributes to a higher rate of cell-edge user, based on which an SIC order based user scheduling algorithm for both cell-center and cell-edge users is presented.

In this paper, we investigate power-efficient constructive interference (CI) exploitation in multi-cell coordination systems. By only sharing channel state information (CSI) among the coordinated base stations (BS)s, we propose a CI-based coordinated beamforming (CBF) scheme to judiciously exploit multiuser interference as a beneficial element rather than strictly mitigating it, while simultaneously suppressing inter-cell interference as a destructive element. Then taking imperfect channel state information (CSI) into consideration, we minimize the total transmission power consumption with multiple users' probabilistic signal-to-interference-and-noise ratio (SINR) requirements, where the users' SINR requirements are guaranteed in a statistical manner. Finally, under the presence of CSI error, simulation results demonstrate that the proposed CI-based CBF scheme consumes much lower transmission power compared to the classical CBF benchmarks, where both intra-cell multi-user and inter-cell interference need to be strictly cancelled as destructive elements. Last but not least, the incurred overhead and computational complexity of the proposed scheme are analytically analyzed, confirming its practicality as a new dimension on multi-cell coordination.

Conventional request-grant based non-orthogonal multiple access (NOMA) incurs tremendous overhead and high latency. To enable grant-free access in NOMA systems, user activity detection (UAD) is essential. In this paper, we investigate compressive sensing (CS) aided UAD, by utilizing the property of quasi-time-invariant channel tap delays as the prior information. This does not require any prior knowledge of the number of active users like the previous approaches, and therefore is more practical. Two UAD algorithms are proposed, which are referred to as gradient based and time-invariant channel tap delays assisted CS (g-TIDCS) and mean value based and TIDCS (m-TIDCS), respectively. They achieve much higher UAD accuracy than the previous work at low signal-to-noise ratio (SNR). Based on the UAD results, we also propose a low-complexity CS based channel estimation scheme, which achieves higher accuracy than the previous channel estimation approaches.

In this article, we propose a semi-blind full-duplex (FD) amplify-and-forward (AF) relay system with adaptive self-interference (SI) processing assisted by independent component analysis (ICA) for low-latency and high-reliability (LLHR) Internet of Things (IoT). The SI at FD relay is not necessarily canceled as much as possible like the conventional approaches, but is canceled or utilized based on a signal-to-residual-SI ratio (SRSIR) threshold at relay. According to the selected SI processing mode at relay, an ICA-based adaptive semi-blind scheme is proposed for signal separation and detection at destination. The proposed FD relay system not only features reduced signal processing cost of SI cancelation but also achieves a much higher degree of freedom in signal detection. The resulting bit error rate (BER) performance is robust against a wide range of SRSIR, much better than that of conventional FD systems, and close to the ideal case with perfect channel state information (CSI) and perfect SI cancelation. The proposed system also requires negligible spectral overhead as only a nonredundant precoding is needed for ambiguity elimination in ICA. In addition, the proposed system enables full resource utilization with consecutive data transmission at all time and same frequency, leading to much higher throughput and energy efficiency than the time-splitting and power-splitting-based self-energy recycling approaches that utilize only partial resources. Furthermore, an intensive analysis is provided, where the SRSIR thresholds for the adaptive SI processing mode selection and the BER expressions with ICA incurred ambiguities are derived.

In this article, we address physical layer security in the distributed antenna (DA) systems, where eavesdroppers (Eves) can intercept the information transmitted for the intended receiver (IR). To realize a device-centric, power-efficient, and physical-layer security-aware system, we aim at minimizing power consumption by jointly designing DA selection and secure precoding. Different from the conventional artificial noise (AN)-aided secure transmission, where AN is treated as an undesired element for the IR, we design AN such that it is constructive to the IR while keeping destructive to the Eves. Importantly, we investigate two practical scenarios, where the IR and Eves' channel state information (CSI) are imperfectly obtained or the Eves' CSI is completely unknown. To handle the CSI uncertainties, we solve the problems in probabilistic and deterministic robust optimizations, respectively, both satisfying the IR' signal-to-interference-plus-noise ratio (SINR) requirement by the use of constructive AN and addressing security against the Eves. The simulation results demonstrate our algorithms consume much less power compared to the centralized antenna (CA) systems with/without antenna selection, as well as the DA systems with conventional AN processing. Last but not least, by the proposed algorithms, the activation of DAs closely relates to devices' locations and quality-of-service (QoS) requirements, featuring a device-centric and on-demand structure.

In this paper, we propose a series of novel coordination schemes for multi-cell downlink communication. Starting from full base station (BS) coordination, we first propose a fully-coordinated scheme to exploit beneficial effects of both inter-cell and intra-cell interference, based on sharing both channel state information (CSI) and data among the BSs. To reduce the coordination overhead, we then propose a partially-coordinated scheme where only intra-cell interference is designed to be constructive while inter-cell is jointly suppressed by the coordinated BSs. Accordingly, the coordination only involves CSI exchange and the need for sharing data is eliminated. To further reduce the coordination overhead, a third scheme is proposed, which only requires the knowledge of statistical inter-cell channels, at the cost of a slight increase on the transmission power. For all the proposed schemes, imperfect CSI is considered. We minimize the total transmission power in terms of probabilistic and deterministic optimizations. Explicitly, the former statistically satisfies the users' signal-to-interference-plus-noise ratio (SINR) while the latter guarantees the SINR requirements in the worst case CSI uncertainties. Simulation verifies that our schemes consume much lower power compared to the existing benchmarks, i.e., coordinated multi-point (CoMP) and coordinated-beamforming (CBF) systems, opening a new dimension on multi-cell coordination.

In this paper, to realize a power-efficient, user-centric and physical layer security-addressing system, we investigate total power minimization by jointly designing antenna selection and secure precoding for distributed antenna (DA) systems. Different from the conventional artificial noise (AN)-aided secure transmission, where AN is treated as an undesired element for the intended receiver (IR), we design AN such that it is constructive to the IR while keeping destructive to the eavesdroppers (Eves). Importantly, we investigate a practical scenario, where the IR and Eves' channel state information (CSI) is imperfectly obtained. To handle the CSI uncertainties, we solve the problem in a probabilistic manner, which statistically satisfies the IR' signal-to-interference-and-ratio (SINR) requirement by use of constructive AN and addresses security against the Eves. Simulation demonstrates our algorithm consumes much less power compared to the centralized antenna (CA) systems, as well as the DA systems with conventional AN processing. Last but not least, a user-centric and on-demand structure is presented by the algorithm, thanks to the adaptive DAs activation/deactivation mechanism.

Distributed antenna (DA) is considered as a strong alternative to conventional centralized multiple-input multiple-output (MIMO), to provide a greener and user-centric network structure. However, physical layer (PHY) security becomes more challenging in DA systems because of the proximity to the transmitters. In this paper, we jointly optimize DA activation/deactivation and secure precoding to minimize the total power consumption, subjected to legitimate user's (LU) quality-of-service (QoS) and PHY security constraints against potential eavesdroppers (Eves). A practical scenario is considered, where channel state information (CSI) of all the nodes can only be imperfectly obtained. In the presence of infinite probabilities of CSI uncertainties, a deterministic robust based algorithm is designed to always satisfy LU's QoS requirement and address PHY security constraints against Eves. Moreover, essentially different from existing artificial noise (AN)-aided secure transmission schemes, where AN' leakage effect at LU needs to be suppressed, we utilize AN as a beneficial element at LU end while keeping it destructive at potential Eves. Simulation results verify that, the proposed algorithm incurs much lower power consumption compared to its benchmarks, thanks to the additional degrees of freedom of antenna selection and utilizing constructive AN. Last but not least, by adaptively facilitating DA activation/deactivation, the proposed algorithm addresses a user-centric network structure, which is more flexible over the conventional centralized MIMO systems.

We investigate a downlink multi-cell non-orthogonal multiple access (NOMA) system with coordinated base stations (BSs) and propose a joint resource allocation (RA) scheme alongside adaptive user association to green the system. To the best of our knowledge, this is the first work to investigate joint allocation of subchannels and power for coordinated NOMA systems, while the previous work on RA for coordinated orthogonal multiple access (OMA) systems is not applicable. A serving channel gain based joint RA (SCG-JRA) algorithm is proposed, based on the theoretical proof that the total transmission power is mono-decreasing with respect to the SCGs of non-coordinated users. As for user association, an adaptive fuzzy logic (FL) based multi-criterion approach is proposed to achieve higher robustness against the combined effect of shadowing, fading and inter-cell interference, compared to the previous single-criterion based approaches. Numerical results show that the proposed SCG-JRA with adaptive FL based user association significantly outperforms the previous RA schemes assisted by single-criterion user association, in terms of energy efficiency (EE) and total transmission power, enabling a greener system.

We investigate an amplify-and-forward (AF) full-duplex (FD) relay system, where the FD incurred self-interference (SI), through partial cancellation at relay, is treated as a useful source at destination to enhance degree of freedom in signal detection, while reducing the signal processing cost of SI cancellation. An independent component analysis (ICA) based equalization structure is employed at destination to separate and detect the desired signal from the residual SI in a semi-blind way. The mode of SI cancellation at relay is chosen adaptively based on the threshold of signal-to-interference ratio (SIR) at relay. The proposed FD relay system not only features reduced signal processing cost of SI cancellation, but also achieves much higher energy efficiency (EE) than conventional FD relay systems where SI is canceled as much as possible. Also, the proposed system enables full resource utilization via consecutive data transmission at all time and the same frequency, leading to much higher throughput and EE than the conventional time-splitting and power-splitting based SI recycling approaches that occupy partial resources. Last but not least, the proposed system demonstrates a bit error rate (BER) performance that is robust against a wide range of SI and close to the ideal case with perfect channel state information (CSI) and perfect SI cancellation, while requiring no training sequence for estimation of any channel involved.

Unmanned aerial vehicles (UAVs) have been widely used in both military and civilian applications. Equipped with diverse communication payloads, UAVs cooperating with satellites and base stations constitute a space-air-ground three-tier heterogeneous network, which are beneficial in terms of both providing the seamless coverage as well as of improving the capacity for increasingly prosperous Internet of Things networks. However, cross-tier interference may be inevitable among these tightly embraced heterogeneous networks when sharing the same spectrum. The power association problem in satellite, UAV and macrocell three-tier networks becomes a critical issue. In this paper, we propose a two-stage joint hovering altitude and power control solution for the resource allocation problem in UAV networks considering the inevitable cross-tier interference from space-air-ground heterogeneous networks. Furthermore, Lagrange dual decomposition and concave-convex procedure method are used to solve this problem, followed by a low-complexity greedy search algorithm. Finally, simulation results show the effectiveness of our proposed two-stage joint optimization algorithm in terms of UAV network's total throughput.

Unmanned aerial vehicles (UAVs) cooperating with satellites and base stations (BSs) constitute a space-air-ground three-tier heterogeneous network, which is beneficial in terms of both providing the seamless coverage as well as of improving the capacity for the users. However, cross-tier interference may be inevitable among these tightly embraced heterogeneous networks. In our paper, we propose a two-stage joint hovering altitude and power control solution for the resource allocation problem. Furthermore, Lagrange dual decomposition and concave-convex procedure (CCP) method are used to solve this problem. Finally, simulation results show the effectiveness of our proposed two-stage joint optimization algorithm in terms of UAV network's total throughput.

Combining non-orthogonal multiple access (NOMA) with coordination techniques among base stations (BSs) is a promising solution to enhance spectral efficiency and alleviate inter-cell interference of cell-edge users in 5th generation (5G) networks. In this paper, we consider a multi-cell NOMA network with coordinated BSs in the downlink, and investigate its user coordination mode selection and resource allocation to achieve a green system. A fuzzy logic (FL) based multi-criterion scheme is proposed for user coordination mode selection. It is more robust against shadowing and fading than the previous selection schemes that classify coordinated and non-coordinated users by a single criterion. Also, the FL ranking list is fed into subcarrier allocation, leading to significant reduction in searching complexity of subcarrier allocation. A dramatic performance enhancement is achieved over the previous schemes based on single-criterion, in terms of transmission power and energy efficiency.

Motivated by the high data rate requirement, full- duplex (FD) multiple-input multiple-output (MIMO) has attracted much attention in both academia and industry. However, FD and MIMO techniques require high power consumption. To strike the balance between the data rate and power consumption, we propose a novel hybrid duplexing strategy, in which antennas are distributed across the service areas and are capable of working in hybrid modes of FD, half- duplex (HD) and sleeping mode, leading to higher energy efficiency (EE) than FD mode only due to enhanced degree of freedom. Based on the hybrid duplexing strategy, we maximize system EE by jointly designing transmitting/receiving chains' activation/deactivation at DAs, downlink beamformer, and uplink transmission power. Novel optimization algorithms are developed. Simulation results confirm that the hybrid duplexing distributed antenna (DA) system provides significant EE improvement over the conventional centralized FD MIMO system, showing its green evolution and applicability to future network deployment.

Thanks to recent advance in massive social data and increasingly mature big data mining technologies, information diffusion and its control strategies have attracted much attention, which play pivotal roles in public opinion control, virus marketing as well as other social applications. In this paper, relying on social big data, we focus on the analysis and control of information diffusion. Specifically, we commence with analyzing the topological role of the social strengths, i.e., tie strength, partial strength, value strength, and their corresponding symmetric as well as asymmetric forms. Then, we define two critical points for the cascade information diffusion model, i.e., the information coverage critical point (CCP) and the information heat critical point (HCP). Furthermore, based on the two real-world datasets, the proposed two critical points are verified and analyzed. Our work may be beneficial in terms of analyzing and designing the information diffusion algorithms and relevant control strategies.

To address the problem of unbalanced received signal-to-interference-and-noise ratio (SINR) at relay and destination nodes in wireless power transfer (WPT)- supported relay system, we propose a novel asymmetric full-duplex (FD) decode-and-forward (DF) WPT relay strategy, where the transmission time slots are not necessarily identical. By introducing asymmetric time slots, higher degree of freedom is obtained than the conventional symmetric WPT relay system. Furthermore, based on the asymmetric strategy, we develop a spectral efficiency (SE)- oriented resource allocation algorithm by jointly designing time slots, transmission power at source and relay. Simulation results show that the proposed asymmetric system demonstrates higher SE than the symmetric WPT-powered FD and the time- switching based FD relay systems. Besides, more energy can be harvested at the relay node by the proposed system benefiting from the enhanced degree of freedom, showing its applicability in WPT-powered relay systems.

We propose a semi-blind precoding aided maximum likelihood (ML) carrier frequency offset (CFO) estimation method and a precoding aided equalization based on independent component analysis (ICA) receiver structure for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) wireless communication systems. By carefully designing a constant in the precoding process, the power between reference data and source data can be balanced to enable ML CFO estimation and ambiguity elimination for the ICA output signals at the receiver. This proposed semi-blind non-redundant structure is much more bandwidth-and-energy efficient than the pilot aided ML CFO estimation method, as no real-time training or extra transmission power is required. Simulation results show that the proposed scheme provides a bit error rate (BER) performance the same as the performance of the pilot aided ML CFO estimation method, and close to the ideal case with perfect channel state information (CSI) and no CFO.

Energy efficiency (EE) is an important issue at 60 GHz due to high power consumption of devices working at such high frequency. In this paper, we investigate EE optimization for full-duplex (FD) decode-of-forward (DF) relay-assisted 60 GHz multiuser indoor networks. In contrast to the existing spectral efficiency (SE) optimization, our scheme maximizes system EE for FD relaying system under cross-layer constraints, addressing the typical problems at 60 GHz, such as the effect of imperfect channel estimation due to serious signal blockage. A low-complexity EE-orientated optimization algorithm is proposed, by which the transmission power, subcarriers and throughput are allocated jointly across multiple users. Simulation results verify our analytical results and confirm that the proposed algorithm achieves a higher EE than the SE-oriented approach, while offering a comparable SE. Also, FD relaying with the proposed algorithm outperforms HD relaying in terms of both EE and SE. In addition, a much lower throughput outage probability is guaranteed by the proposed algorithm, showing its robustness against channel estimation errors. A full range of power consumption sources and imperfect self-interference cancellation are considered to rationalize our analysis.

Energy-efficiency (EE)-oriented green communication design is an important issue at 60 GHz due to high power consumption of devices working at such a high frequency. In this paper, we investigate EE-oriented resource allocation for full-duplex (FD) decode-and-forward relay-assisted 60-GHz multiuser indoor systems. In contrast to the existing spectral efficiency (SE)-oriented designs, our scheme maximizes the EE for a FD relaying system under cross-layer constraints, addressing the typical problems at 60 GHz, such as the intermittent signal blockage caused by the small wavelength of millimeter-wave. A low-complexity EE-orientated resource allocation algorithm is proposed, by which the transmission power allocation, subcarrier allocation, and throughput assignment are performed jointly across multiple users. Simulation results verify our analytical results and confirm that the FD relaying with the proposed algorithm achieves a higher EE than the FD relaying with SE-oriented approaches, while offering a comparable SE. In addition, a much lower throughput outage probability is guaranteed by the proposed resource allocation algorithm, showing its robustness against channel estimation errors. A full range of power consumption sources and imperfect self-interference cancellation are considered to rationalize our analysis.

We provide a comprehensive energy efficiency (EE) analysis of the full-duplex (FD) and half-duplex (HD) amplify-and-forward (AF) relay-assisted 60-GHz dual-hop indoor wireless systems, aiming to answer the question of which relaying mode is greener (more energy efficient) and to address the issue of EE optimization. We develop an opportunistic relaying mode selection scheme, where FD relaying with one-stage self-interference cancellation (passive suppression) or two-stage self-interference cancellation (passive suppression + analog cancellation) or HD relaying is opportunistically selected, together with transmission power adaptation, to maximize the EE with given channel gains. A low-complexity joint mode selection and EE optimization algorithm are proposed. We show a counter-intuitive finding that with a relatively loose maximum transmission power constraint, FD relaying with two-stage self-interference cancellation is preferable to both FD relaying with one-stage self-interference cancellation and HD relaying, resulting in a higher optimized EE. A full range of power consumption sources is considered to rationalize our analysis. The effects of imperfect self-interference cancellation at relay, drain efficiency, and static circuit power on EE are investigated. Simulation results verify our theoretical analysis.