The rapid evolution of Internet of Things (IoT) demands secure and lightweight authentication schemes for resource-asymmetric environments, where gateways are powerful but user and device sides are constrained. Existing authentication and key agreement (AKA) protocols often fail to provide dynamic anonymity, resist malicious gateways, and support low-entropy passwords. To address these limitations, we propose a certificateless AKA scheme that combines a one-time password algorithm based on hash chains (HOTP) with fuzzy extractors for multi-factor authentication. The scheme ensures full dynamic anonymity, resists replay and impersonation attacks, and eliminates reliance on time synchronization. We formally verify its security using ProVerif and provide informal analysis. Performance comparisons demonstrate that the proposed scheme significantly reduces computational overhead while enhancing security, outperforming existing methods. These results confirm its suitability for secure, scalable IoT applications.

Advancements in large language models (LLMs) are driving progress towards general artificial intelligence. Ensuring differential privacy during fine-tuning and inference on domain-specific data is essential, but balancing privacy and utility, especially for sequential and label data, remains challenging. Existing methods protect sequential data well but struggle with label data due to traditional definitions of label differential privacy, which ignore label-feature correlations and weaken label privacy. We propose an optimized privacy-utility trade-off for label data by introducing a new definition for conditional feature-label differential privacy and enhancing the double randomized response (DRR) mechanism with a Rényi divergence optimizer. Additionally, a dynamic perturbation factor function improves usability across various tasks. Experimental results show that our method enhances resistance to label inference attacks by over 20% while maintaining similar accuracy, offering stronger privacy with a reduced privacy overhead and achieving an optimal balance during LLMs fine-tuning and inference.

Database vendors have made significant redesigns and developments to the relational database for providing cloud-hosted and cloud-native database services. Thus, the original knob-tuning experiences of DBAs are no longer applicable to the cloud database era. An interpretable estimation service is urgently needed to provide explicit guidance for database knob tuning. Unfortunately, less attention has been paid to estimating the performance of the knob configuration. To fill this gap, we propose EAST, a knob estimation system to provide interpretable & transferable knob estimation services for cloud databases. Firstly, we design an interpretable knob-embedding-based estimator to achieve the trusted and white-box knob estimation for researchers, practitioners, and even artificial intelligence knob tuners. Secondly, we design a two-stage transfer estimation approach by stacking ensemble learning to utilize historical experiences, improving time efficiency. Thirdly, EAST provides a user-friendly interface to support direct knob estimation and transfer knob estimation services. We have deployed our EAST11https://gitee.com/opengauss/openGauss-DBMind/tree/incubator/dbmind/components/knob_estimator to the DBMind component of OpenGauss and demonstrated the effectiveness of our system under the open-source benchmark TPCC.

Smart factories and homes represent resourceasymmetric environments where gateways offer abundant resources, while user and edge devices remain constrained. Existing authentication and key agreement (AKA) protocols for the settings typically overlook threats from malicious gateways and cannot reconcile dynamic anonymity with minimal overhead. To address these challenges, we propose the Secure dynamic Anonymity updates and Gateway-side secure Authentication (SAGA), a lightweight AKA protocol based on three synergistic layers: dual-threshold Shamir's Secret Sharing (SSS) to distribute trust across multiple gateways, a Merkle Tree mechanism with one-time password algorithm based on hash chains (HOTP) for efficient gateway verification, and an active shared key-refresh method to maintain dynamic anonymity and session keys. Formal security proofs using Burrows-Abadi-Needham (BAN) logic and ProVerif validate SAGA's rigorous security, while experimental results show it achieves stronger security properties with lower computational and communication costs than existing schemes.

Unit commitment (UC) is a critical component for the power system dispatching departments. Current methodologies for solving UC problems predominantly rely on mixed-integer linear programming and are supplemented by data-driven approaches. These methodologies have two primary limitations: first, as the scale of the power grid expands, the complexity of algorithms increases sharply. Second, they fail to fully exploit grid topology information and historical data trends. To address these limitations, this article proposes a constrained graph-temporal convolutional network, which addresses the UC problem by directly predicting power output with constraints. The algorithm takes historical load data from grid nodes as input, utilizes graph convolutional networks to capture the physical grid topology information, and employs temporal convolutional networks to extract temporal features. Ultimately, the output of the graph-temporal convolutional network is projected into the feasible domain through a linear constraint activation layer, achieving accurate power prediction. Experiments conducted on the IEEE 30-BUS and IEEE 118-BUS systems validate the feasibility and superiority of our method in terms of accuracy and computational efficiency.

The knob tuning aims to optimize database performance by searching for the most effective knob configuration under a certain workload. Existing works suffer from two significant problems. First, there exist multiple useless evaluations of knob tuning even with diverse searching methods because of the different sensitivities of knobs on a certain workload. Second, the single evaluation of knob configurations may bring overestimation or underestimation because of query performance uncertainty. To solve the above problems, we propose a query uncertainty-aware knob classifier, called${\sf KnobCF}$, to enhance knob tuning. Our method has three contributions: (1) We propose uncertainty-aware configuration estimation to improve the tuning process. (2) We design a few-shot uncertainty estimator that requires no extra data collection, ensuring high efficiency in practical tasks. (3) We provide a flexible framework that can be integrated into existing knob tuners and DBMSs without modification. Our experiments on four open-source benchmarks demonstrate that our method effectively reduces useless evaluations and improves the tuning results. Especially in TPCC, our method achieves competitive tuning results with only 60% to 70% time consumption compared to the full workload evaluations.

To address the imbalance problem between supply and demand for taxis and passengers, this paper proposes a distributed ensemble empirical mode decomposition with normalization of spatial attention mechanism based bi-directional gated recurrent unit (EEMDN-SABiGRU) model on Spark for accurate passenger hotspot prediction. It focuses on reducing blind cruising costs, improving carrying efficiency, and maximizing incomes. Specifically, the EEMDN method is put forward to process the passenger hotspot data in the grid to solve the problems of non-smooth sequences and the degradation of prediction accuracy caused by excessive numerical differences, while dealing with the eigenmodal EMD. Next, a spatial attention mechanism is constructed to capture the characteristics of passenger hotspots in each grid, taking passenger boarding and alighting hotspots as weights and emphasizing the spatial regularity of passengers in the grid. Furthermore, the bi-directional GRU algorithm is merged to deal with the problem that GRU can obtain only the forward information but ignores the backward information, to improve the accuracy of feature extraction. Finally, the accurate prediction of passenger hotspots is achieved based on the EEMDN-SABiGRU model using real-world taxi GPS trajectory data in the Spark parallel computing framework. The experimental results demonstrate that based on the four datasets in the 00-grid, compared with LSTM, EMD-LSTM, EEMD-LSTM, GRU, EMD-GRU, EEMD-GRU, EMDN-GRU, CNN, and BP, the mean absolute percentage error, mean absolute error, root mean square error, and maximum error values of EEMDN-SABiGRU decrease by at least 43.18%, 44.91%, 55.04%, and 39.33%, respectively.

Recently, hybrid analog/digital beamforming (BF) system is attracting increasing attention in the study on multiuser millimeter wave systems. In these systems, a relatively large number of antennas are connected to a less number of analog front-end chains so as to reduce both of the hardware complexity and power consumption. This paper investigates on optimizing phase-only analog BF and digital BF weights, with the objective of minimizing the total transmit power subject to signal-to-interference-plus-noise ratio (SINR) constraints. An floating-point genetic algorithm, in which the fitness function is defined as the linear scale of the objective function, is proposed to solve the optimization problem. Chaos crossover probability, chaos mutation probability and elitist strategy are introduced into the genetic algorithm in purpose of improving the operating efficiency as well as increasing the convergent rate. Simulations results under Gaussian channel environment reveal the advantages of the proposed genetic algorithm over the existed iterative algorithm. Besides, under 60GHz channel model, it is shown that the correlation on different subcarriers has profound impact on the performance of hybrid phase-only analog/digital BF.

This paper investigates a typical optimization problem for 60 GHz multiuser hybrid beamforming, which is to maximize the minimal SINR over all of the considered subcarriers under a total power constraint. In order to reduce the complexity, two methods of using the fixed analog beamforming (ABF) weights are presented rather than traditional iterative methods, which are codebook-based method and singular value decomposition (SVD) based method. The performance of hybrid beamforming with the fixed ABF weights are evaluated by computer simulations and compared with that of using the existing iterative method. Channel model defined in IEEE 802.11ad is utilized in the simulation. Simulation results show that the average max-min SINR achieved by the presented methods of using the fixed ABF weights are close to or even higher than that of the iterative method.

Power consumption and costs of analogue front‐end (AFE) chains are often not negligible for large‐scale antenna array systems. A low‐complexity hardware architecture is to use a number of AFE chains that are less than the number of antennas. Beamforming for this low‐complexity hardware architecture involves both digital and analogue beamforming, which is termed hybrid analogue/digital beamforming. In this study, minimising the transmit power subject to signal‐to‐interference‐plus‐noise ratio (SINR) constraints and maximising the minimal SINR under the constraint of the transmit power, are investigated, respectively, for hybrid analogue/digital beamforming. Properties on the feasibility and optimality of the two problems are derived. Numerical algorithms based on semi‐definite positive relaxation are proposed in an attempt to solve the two optimisation problems. The performance of the proposed algorithms is evaluated under the Gaussian and 60 GHz channel models. It is shown that the performance of hybrid analogue/digital beamforming is highly related to the correlation of the channel coefficients of subcarriers. Additionally, for different extents of the users’ spatial separability, some heuristics ways of designing analogue beamforming are shown to be able to approach to at least the local optimums under the 60 GHz channel model.

Antenna calibration to enhance the channel reciprocity between the uplink and downlink channels is necessary for the practical wireless system operating in the time division duplexing (TDD) mode. This paper investigates on the computation of the antenna calibration coefficients of the cooperative base stations' antennas in the network multiple-input and multiple-output (MIMO) system. An efficient scheme for computing the calibration coefficients for an arbitrary number of distributed antennas is proposed. In addition, we also propose two methods of refining the calibration coefficients for the proposed scheme. The evaluations of the proposed scheme and methods are performed through computer simulations.

Under the consideration of the cost and power consumption, analog or radio frequency (RF) beamforming is usually adopted in the 60 GHz wireless systems. Hence, obtaining the multiple- input and multiple-output (MIMO) channel information is costly and of high overhead for the concerned system. In this work, an efficient multi-user scheme is proposed for the single carrier block transmission (SCBT) based 60 GHz system. It schedules users that are unlikely to cause strong multi-user interference (MUI) without knowing the MIMO channel information. Additionally, the proposed scheme enables to further mitigate the residual MUI after scheduling on the effective channels while the system can still employ low cost arrays that have very limited capability of nulling the interference. Evaluation of the proposed scheme is performed by computer simulation based on the channel model defined in 802.11ad.

This paper investigates the performance of multi- antenna spatial diversity in the overlaid wireless ad hoc network. We apply the more practical stochastic geometry tools to model the network. Then we derive closed-form expressions for the outage probability of two coexisting networks employing two basic diversity techniques, the maximum ratio combining (MRC) and the transmit antenna selection (TAS). Monte Carlo simulations verify the accuracy of our expressions, based on which, we further evaluate these two basic diversity schemes from the newly developed perspectives of transmission capacity and overlaid network. We explore the gain source for the transmission capacity of the overlaid network over that of a single network. Our work shows that employing low complexity diversity schemes at either transmit or receive side can significantly improve the overall transmission capacity requiring little or no feedback.

This paper investigates the transmission capacity of the secondary network in overlaid ad hoc networks with multi-antenna spatial multiplexing. Based on stochastic geometry tools, we study the effects of the node density and the transmission power of the secondary network on the transmission capacity performance. We derive the optimal node density for the secondary network, and subsequently the optimal transmit power ratio between the primary network and the secondary network. Our findings show that increasing the node density of the secondary network will result in an increase in the transmission capacity of the secondary network under a reasonable target outage probability assumption. The optimal node density and transmit power ratio are mainly influenced by the target outage probability and the permitted outage probability increment. On the other hand, numerical results show that the transmission capacity increases over the antenna number. Moreover, the antenna number has little effect on the optimal transmission power ratio.

In this paper, we investigate the performance of open-loop spatial multiplexing in overlaid ad hoc networks. Based on a stochastic geometry model, we derive exact closed-form expressions for the transmission capacity of two coexisting networks (a primary network vs. a secondary network) employing spatial multiplexing with zero-forcing (ZF) receivers. Simulation results confirm the accuracy of our expressions. In addition, we discuss the impact of multi-antenna scheme on the transmission capacity of the overlaid networks. Our findings show that the sum transmission capacity of the overlaid networks will improve significantly over that of a single network if a slight outage probability increase is allowable for the primary network. This improvement can be further boosted if spatial multiplexing is employed with more antennas. But when the antenna number exceeds a certain limit, spatial multiplexing may produce negative effect for the overlaid network.

In this paper, we investigate the performance of multiuser scheduling with open-loop spatial multiplexing in ad hoc networks. Closed-form expressions for outage probability and spatial throughput are derived for spatial multiplexing transmission with zero forcing (ZF) receiver and multiuser scheduling. Monte Carlo simulation results reveal that these expressions accurately demonstrate the performance of multiuser scheduling with open-loop spatial multiplexing. Based on these expressions, transmission capacity performance is analyzed and the effects of system parameters over network performance metrics are studied. Our finding indicates that spatial multiplexing with opportunistic multiuser scheduling can provide boosted network performance for ad hoc network by exploiting multiuser diversity gain, whilst requiring very low feedback requirements.

Recently, Coordinated Multi-Point (CoMP) transmission/Reception technology is introduced into the fourth-generation cellular mobile communication system. Time-division duplex (TDD) system is more suitable to apply CoMP when joint processing is needed because it can easily get the channel information through channel reciprocity. Actually, a crucial point to realise channel reciprocity is the antenna calibration, especially in the inter-base station (BS) case. Self-antenna calibration within the BS in the conventional system has been studied in previous works. In this paper, the authors investigate the impact of un-calibrated antennas of BSs and mobile stations (MSs) on the precoding matrix of two precoding techniques [block diagonal (BD) and zero forcing (ZF)] in the CoMP system. A theoretical model is set and analysed. The discussion of some properties gives a complete overview of the calibration problem in the CoMP system. In addition, the authors propose a practical scheme to solve inter-BS antenna calibration problem. System simulation results, which validate their analysis, are presented to show the necessity of antenna calibration.

In real environments, channel reciprocity cannot be directly exploited between uplink and downlink in time-division duplex (TDD) due to antenna gain mismatch. Previous work about antenna calibration mainly focused on single cell. This work proposes an adaptive scheme for antenna calibration between two cooperative BSs. The proposed scheme aims at achieving an equal ratio between antenna transmitter and receiver analog gains among cooperative BSs in flat fading channels. The essential idea is to relay calibration parameter through a calibration path. This procedure can be controlled by a certain BS dubbed primary BS. Evaluation of the proposed scheme is carried out by computer simulation.

Block diagonalization (BD) algorithm is an efficient precoding technique for multiuser multiple-input multiple-output (MU-MIMO) system. In previous researches, BD precoding was mostly realized based on the singular value decomposition (SVD). However, in the cooperative transmission scenario where the dimension of channel matrix is significantly enlarged compared with the single base station (BS) transmission scenario, implementing SVD decomposition requires heavy computational amount, which is impractical in some real systems. The main contribution of this work is a low complexity solution scheme for BD. When the number of antennas of the receiver is two, instead of using SVD, the proposed scheme computes the null space and eigenvectors by solving linear equations and projection method, respectively. It has a lower complexity when the number of transmit antennas is not large. For example, when the number of transmit antennas is 20, the total computational amounts of the proposed scheme is about 53000 flops while it is around 78000 flops in the SVD based scheme.

We investigate linear detection and precoding for denoising-based physical network coding (D-PNC) in two-way multi-input multi-output relay channels. We propose an MMSE-based detector, which first gives a coarse detection to the two source messages using MMSE detector and then detects the product of the two coarse detected messages. The advantage of such detector is to randomize the interference. A simple precoder is also proposed for relay message transmission, which provides fairness. Simulation results show that D-PNC with the proposed detector and precoder has similar pair error rate performance to other schemes while keeps simple structure and lower complexity.

Antenna gain mismatch between transmitter and receiver circuits has been regarded as an obstacle for exploiting channel reciprocity between uplink and downlink channels in time-division duplex (TDD) multiple-input multiple-output (MIMO) systems. To the best knowledge of the authors, little work to date has been on about the impact of antenna mismatches on the precoding vector. Motivated by this fact, this paper investigates some characteristics of downlink precoding in the presence of non-ideal antenna gains. Specifically, properties about inter-MS interference when mismatches exist at the base station (BS) side are presented as well as the perturbation of non-normalized precoding vector caused by mismatches at the mobile station (MS) side under two kinds of linear precoding algorithms. These properties are mostly irrelevant to specific distributions of antenna mismatch parameters and can help to provide a deeper insight into the antenna gain mismatch problem and the corresponding calibration.

Coordinated Multi-Point (CoMP) Transmission/Rec-eption technology has shown to improve the system performance. In Time-division duplex system, it can easily obtain channel information by the channel reciprocity. However, a crucial point to realize the channel reciprocity is the antenna calibration problem. This paper aims at analyzing the impact of un-calibrated channel on the precoding matrix under zero forcing precoding in CoMP system. A theoretical model is set and some properties presented in this work give an overview of the calibration problem. Additionally, we propose a new scheme for inter BS calibration. System simulation results show the necessity of antenna calibration.

Multi-cell cooperation has been regarded as a promising technique of the future cellular wireless network to achieve higher transmission rate and better QoS (quality of service) performance. Cooperation among base stations can be classified into two categories: centralized and distributed cooperation. In this work, we mainly consider efficient and practical cooperation clustering approaches in the downlink Coordinated Multi-Point (CoMP) system. A novel Multi-Layered clustering method is proposed for distributed cooperation, which is able to make a significant enhancement with limited overhead increment compared with traditional static clustering. We also develop a new concept for centralized cooperation. Simulation results are presented under the block diagonal precoding algorithm.

Coordinated scheduling is a hot topic recently. Inter-cell interference is crucial to the improvement of system throughput, especially in OFDMA system. In this work, the optimization of beamforming in multiple-input single-output (MISO) downlink system is considered. The uplink-downlink duality has been widely used in this sort of research. By the conclusion of a previous work, we provide some practical iterative algorithms which help to obtain the beamformers satisfying the necessary optimality conditions of the dual uplink problem. Simulation results show the convergence and the efficiency of proposed algorithms.

We consider the resource allocation of centralized and distributed scheduling in the two-hop relaying cellular system. The limited spectrum resource is one of the obstacles which conflicts with the evolution of being wider coverage and larger capacity in the wireless system. In this paper, system performance and signaling overhead are analyzed and compared. Then we propose a novel routing strategy for choosing the access link and three practical scheduling strategies. Simulation results are provided and analyzed in several scenarios, which show the benefit of adopting the relay technique.