Deep learning based channel state information(CSI)fingerprint indoor localization schemes need to collect massive labeled data samples for training,and the parameters of the deep neural network are used as the fingerp...Deep learning based channel state information(CSI)fingerprint indoor localization schemes need to collect massive labeled data samples for training,and the parameters of the deep neural network are used as the fingerprints.However,the indoor environment may change,and the previously constructed fingerprint may not be valid for the changed environment.In order to adapt to the changed environment,it requires to recollect massive amount of labeled data samples and perform the training again,which is labor-intensive and time-consuming.In order to overcome this drawback,in this paper,we propose one novel domain adversarial neural network(DANN)based CSI Fingerprint Indoor Localization(D-Fi)scheme,which only needs the unlabeled data samples from the changed environment to update the fingerprint to adapt to the changed environment.Specifically,the previous environment and changed environment are treated as the source domain and the target domain,respectively.The DANN consists of the classification path and the domain-adversarial path,which share the same feature extractor.In the offline phase,the labeled CSI samples are collected as source domain samples to train the neural network of the classification path,while in the online phase,for the changed environment,only the unlabeled CSI samples are collected as target domain samples to train the neural network of the domainadversarial path to update parameters of the feature extractor.In this case,the feature extractor extracts the common features from both the source domain samples corresponding to the previous environment and the target domain samples corresponding to the changed environment.Experiment results show that for the changed localization environment,the proposed D-Fi scheme significantly outperforms the existing convolutional neural network(CNN)based scheme.展开更多
It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed tha...It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor environment.Here,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless link.We designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor environment.Moreover,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver scenario.We faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.展开更多
Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at runtime.In order to improve the utiliz...Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at runtime.In order to improve the utilization of multi-core processors and ensure the real-time performance of the system,it is necessary to adopt a reasonable real-time task allocation method,but the existing methods are only for single-core processors or the performance is too low to be applicable.Aiming at the task allocation problem when mixed real-time tasks are dynamically added,we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF(Virtual Utilization Worst Fit)in multi-core processor.First,a 4-tuple task model is established to describe the fixedpoint task and the sporadic task in a unified manner.Then,a VDS(Virtual Deferral Server)for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is derived.Finally,combined with the analysis of VDS's capacity,VU-WF is proposed,which selects cores in ascending order of virtual utilization for the schedulability test.Experiments show that the overall performance of VU-WF is better than available algorithms,not only has a good schedulable ratio and load balancing but also has the lowest runtime overhead.In a 4-core processor,compared with available algorithms of the same schedulability ratio,the load balancing is improved by 73.9%,and the runtime overhead is reduced by 38.3%.In addition,we also develop a visual multi-core mixed task scheduling simulator RT-MCSS(open source)to facilitate the design and verification of multi-core scheduling for users.As the high performance,VU-WF can be widely used in resource-constrained and safety-critical real-time systems,such as spacecraft,self-driving cars,industrial robots,etc.展开更多
In this paper,based on the block Markov superposition transmission(BMST)technique,we present a new class of coupled low-density parity-check(LDPC)codes for the transport block(TB)-based transmission to improve the err...In this paper,based on the block Markov superposition transmission(BMST)technique,we present a new class of coupled low-density parity-check(LDPC)codes for the transport block(TB)-based transmission to improve the error-correcting performance.For encoding,the previous LDPC codewords corresponding to a TB(at prior time slot)are interleaved and superimposed onto the current LDPC codewords,resulting in the transmitted codewords.For decoding,the sliding window decoding algorithm with sum-product or min-sum implementations can be employed,inheriting a relatively low-latency decoding.A distinguished advantage of the proposed coded transmission over spatially coupled LDPC(SC-LDPC)codes is that the encoder/decoder of the proposed codes can be designed by reusing the encoder/decoder architecture of component block LDPC codes.To analyze the waterfall performance of BMST-LDPC code ensembles,we present the protograph-based EXIT chart analysis,which can efficiently predict the error-correcting performance in waterfall region.To analyze the error-floor performance of BMST-LDPC codes,we employ the genie-aided(GA)lower bound,which can efficiently predict the error-correcting performance in error-floor region.For ease of implementation,the BMST-LDPC codes are constructed by taking the(2,4)-raptor-like LDPC codes or the 5G LDPC codes as the basic components.The numerical results reveal that the proposed codes can have capacity-approaching performance,exhibiting a gap of 0.007 dB away from the corresponding Shannon limit.They also reveal that,by using the proposed BMST construction,the error-correcting performance of the original 5G block LDPC codes can be significantly improved,achieving coding gains up to one dB over the AWGN channels and two dB over the fast fading channels.展开更多
A novel broadband metasurface (MTS) antenna array with high front-to-back ratio (FBR) is proposed for 28 GHz millimeter-wave applications. With slot pairs loaded on patch cells, an aperturecoupled slotted-mushroom MTS...A novel broadband metasurface (MTS) antenna array with high front-to-back ratio (FBR) is proposed for 28 GHz millimeter-wave applications. With slot pairs loaded on patch cells, an aperturecoupled slotted-mushroom MTS antenna is designed to obtain broadband radiation characteristicswith a compact size. To suppress the backward radiation of this antenna, the printed ridge gapwaveguide (PRGW) technology with a perfect magnetic conductor (PMC) shielding made ofmushroom unit-cells underneath the microstrip feeding line is applied. On this basis, a 4×4 MTSantenna array with the PRGW feed network is developed. Simulated results show that the FBR canbe highly improved by over 16 dB within the entire bandwidth. To validate the design, a prototypeof the proposed antenna is fabricated. Measured results show that an FBR greater than 28 dB canbe obtained over a 24% impedance bandwidth (from 24.9 GHz to 31.7 GHz) with the reflectioncoefficient less than 10 dB. The measured antenna gain ranges from 17 dBi to 19.2 dBi and thecorresponding measured aperture efficiencies are 35% and 45.6%. The measured results alsosuggest that the proposed MTS antenna possesses -35 dB cross-polarization level and stable radiation patterns. In addition, the proposed antenna remains a very low profile of 1.7 mm (0.17λ_(0) at28 GHz). All the achieved features indicate that the proposed MTS antenna is an importantcandidate for B5G and 6G wireless communication.展开更多
Satellite communications and reconfigurable intelligent surface (RIS) are considered as twopromising technologies that can significantly improve the coverage and energy efficiency of futurewireless communication netwo...Satellite communications and reconfigurable intelligent surface (RIS) are considered as twopromising technologies that can significantly improve the coverage and energy efficiency of futurewireless communication networks. The satellite communications security is often threatened dueto its broadcasting nature. To enhance the physical layer security (PLS) of satellite communications with channel similarity, an aerial RIS-aided dual full-duplex (DFD-ARIS) cooperative jamming method is presented in this paper. Specifically, unlike the existing works that relied onchannel difference, DFD-ARIS utilizes the channel similarity against the eavesdroppers with thehelp of ARIS. In addition, the power allocation is further studied in conjunction with the phasedesign of RIS to minimize the total power under the constraints of data rate, satellite powerlimitation and secrecy rate. Then, the closed-form solutions are achieved. Simulation results showthat the performance of the proposed scheme is superior to the traditional method.展开更多
With the increasing popularity of civilian unmanned aerial vehicles(UAVs),safety issues arising from unsafe operations and terrorist activities have received growing attention.To address this problem,an accurate class...With the increasing popularity of civilian unmanned aerial vehicles(UAVs),safety issues arising from unsafe operations and terrorist activities have received growing attention.To address this problem,an accurate classification and positioning system is needed.Considering that UAVs usually use radio frequency(RF)signals for video transmission,in this paper,we design a passive distributed monitoring system that can classify and locate UAVs according to their RF signals.Specifically,three passive receivers are arranged in different locations to receive RF signals.Due to the noncooperation between a UAV and receivers,it is necessary to detect whether there is a UAV signal from the received signals.Hence,convolutional neural network(CNN)is proposed to not only detect the presence of the UAV,but also classify its type.After the UAV signal is detected,the time difference of arrival(TDOA)of the UAV signal arriving at the receiver is estimated by the cross-correlation method to obtain the corresponding distance difference.Finally,the Chan algorithm is used to calculate the location of the UAV.We deploy a distributed system constructed by three software defined radio(SDR)receivers on the campus playground,and conduct extensive experiments in a real wireless environment.The experimental results have successfully validated the proposed system.展开更多
In this paper,we introduce a new concept,namelyε-arithmetics,for real vectors of any fixed dimension.The basic idea is to use vectors of rational values(called rational vectors)to approximate vectors of real values o...In this paper,we introduce a new concept,namelyε-arithmetics,for real vectors of any fixed dimension.The basic idea is to use vectors of rational values(called rational vectors)to approximate vectors of real values of the same dimension withinεrange.For rational vectors of a fixed dimension m,they can form a field that is an mth order extension Q(α)of the rational field Q whereαhas its minimal polynomial of degree m over Q.Then,the arithmetics,such as addition,subtraction,multiplication,and division,of real vectors can be defined by using that of their approximated rational vectors withinεrange.We also define complex conjugate of a real vector and then inner product and convolutions of two real vectors and two real vector sequences(signals)of finite length.With these newly defined concepts for real vectors,linear processing,such as linear filtering,ARMA modeling,and least squares fitting,can be implemented to real vectorvalued signals with real vector-valued coefficients,which will broaden the existing linear processing to scalar-valued signals.展开更多
Graph convolutional networks(GCNs)have been successfully applied to node representation learning in various real-world applications.However,the performance of GCNs drops rapidly when the labeled data are severely scar...Graph convolutional networks(GCNs)have been successfully applied to node representation learning in various real-world applications.However,the performance of GCNs drops rapidly when the labeled data are severely scarce,and the node features are prone to being indistinguishable with stacking more layers,causing over-fitting and over-smoothing problems.In this paper,we propose a simple yet effective contrastive semantic calibration for graph convolution network(CSC-GCN),which integrates stochastic identity aggregation and semantic calibration to overcome these weaknesses.The basic idea is the node features obtained from different aggregation operations should be similar.Toward that end,identity aggregation is utilized to extract semantic features from labeled nodes,while stochastic label noise is adopted to alleviate the over-fitting problem.Then,contrastive learning is employed to improve the discriminative ability of the node features,and the features from different aggregation operations are calibrated according to the class center similarity.In this way,the similarity between unlabeled features and labeled ones from the same class is enhanced while effectively reducing the over-smoothing problem.Experimental results on eight popular datasets show that the proposed CSC-GCN outperforms state-ofthe-art methods on various classification tasks.展开更多
Reconfigurable intelligent surface(RIS)is emerged as a promising technique to solve the challenges faced by future wireless communication networks.Although the most commonly used electrically-controlled RISs can achie...Reconfigurable intelligent surface(RIS)is emerged as a promising technique to solve the challenges faced by future wireless communication networks.Although the most commonly used electrically-controlled RISs can achieve millisecond-scale speed of dynamic switch,they have a large number of microwave circuit elements(such as PIN diodes or varactors)which will bring non-negligible insertion loss,and the complicity of the bias network to electrically addressing each element will increase with the expansion of the RIS aperture.Aiming at further reducing the fabrication cost and power consumption,herein an electromechanical RIS used for sub-6G wireless communication is proposed.The electromechanical RIS is designed with a passive metasurface and step-motor driver modules,providing simultaneous high-efficiency reflection(over 80%)and continuous reflection phase coverage of 360.Through electromechanical control,the RIS system can realize different reflective wavefront shaping,and has been employed in the indoor sub-6G wireless environment demonstrating a maximum signal improvement of 8.3 dB.The proposed electromechanical RIS is particularly useful for wireless signal enhancement in static blind area,and has the obvious advantage of not requiring continuous power supply after the RIS being regulated.Therefore,it greatly reduces the overall cost and power consumption which may have potentials in indoor application scenarios for improving wireless communication performance.展开更多
This paper proposes a new method to generate a two-dimensional(2D)Airy beam and Airy autofocusing beam by using the scalar holographic metasurface with amplitude-phase modulation in the microwave band.The proposed hol...This paper proposes a new method to generate a two-dimensional(2D)Airy beam and Airy autofocusing beam by using the scalar holographic metasurface with amplitude-phase modulation in the microwave band.The proposed holographic metasurface comprises subwavelength patch unit cells with a period of fewer than 1/8 wavelengths,which means that it has the finer sampling for electromagnetic waves and can simultaneously achieve precise modulations for the amplitude and phase of electromagnetic waves.Firstly,the 2D-Airy beam with quasi-non-diffraction and selfbending characteristics is generated,from which the holographic metasurface is designed to realize four different 2D-Airy beams with the same focus,achieving the 2D-Airy autofocusing beam in the microwave frequency.The holographic metasurface for Airy beam generation has high efficiency and an ultra-lower profile.Meanwhile,for applying the Airy beam in wireless power transfer(WPT),the efficiency of the generated Airy beam and Airy autofocusing beam is calculated for the first time in the microwave field.The simulation results show that the efficiency of the 2D-Airy beam can reach 66%at 150 mm away from the metasurface,while the efficiency of the 2D-Airy autofocusing beam at the focus,which is 280 mm from the metasurface,can reach 35%.The theoretical,simulated,and measured results show that the proposed method and holographic metasurfaces can flexibly achieve the special characteristics of self-autofocusing and self-bending Airy beams in the microwave domain,providing an effective path for wireless power transfer(WPT)scenario with radial obstructions.展开更多
The joint adoption of sub-6GHz and millimeter wave(mmWave)technology can prevent the blind spots of coverage,enabling comprehensive coverage while realizing high-speed communication rate.According to the sensitivity o...The joint adoption of sub-6GHz and millimeter wave(mmWave)technology can prevent the blind spots of coverage,enabling comprehensive coverage while realizing high-speed communication rate.According to the sensitivity of mmWave,base stations should be more densely deployed,which is not well described by existing Poisson hole process(PHP)and the Poisson point process(PPP)models.This paper establishes a sub-6GHz and mmWave hybrid heterogeneous cellular network based on the modified Poisson hole process(MPHP).In our proposed model,the sub-6GHz base stations follow the PPP,and the mmWave base stations(MBSs)follow MPHP distribution.The expressions of the coverage probability are derived by using the interference calculation method of integrating the nearest sector exclusion area.Our theoretical analysis has been verified through simulation results,suggesting that the increase in the cell radius decreases the coverage probability of signal-to-interference-plus-noise ratio(SINR),whereas the increase in the sector parameter has the opposite effect.The variation of sub-6GHz base stations(SBSs)density imposes more significant impact than the MBSs on the SINR coverage probability.In addition,the decrease in MBSs density will reduce the average bandwidth allocated to the user equipment(UE),thus reducing the rate coverage probability.展开更多
To solve the data island problem,federated learning(FL)provides a solution paradigm where each client sends the model parameters but not the data to a server for model aggregation.Peer-to-peer(P2P)federated learning f...To solve the data island problem,federated learning(FL)provides a solution paradigm where each client sends the model parameters but not the data to a server for model aggregation.Peer-to-peer(P2P)federated learning further improves the robustness of the system,in which there is no server and each client communicates directly with the other.For secure aggregation,secure multi-party computing(SMPC)protocols have been utilized in peer-to-peer manner.However,the ideal SMPC protocols could fail when some clients drop out.In this paper,we propose a robust peer-to-peer learning(RP2PL)algorithm via SMPC to resist clients dropping out.We improve the segmentbased SMPC protocol by adding a check and designing the generation method of random segments.In RP2PL,each client aggregates their models by the improved robust secure multi-part computation protocol when finishes the local training.Experimental results demonstrate that the RP2PL paradigm can mitigate clients dropping out with no significant degradation in performance.展开更多
In this paper,we propose a new class of nonbinary polar codes,where the symbol-level polarization is achieved by using a 2×2 q-ary matrix[10β1]as the kernel.Under bit-level code construction,some partially-froze...In this paper,we propose a new class of nonbinary polar codes,where the symbol-level polarization is achieved by using a 2×2 q-ary matrix[10β1]as the kernel.Under bit-level code construction,some partially-frozen symbols exist,where the frozen bits in these symbols can be used as activecheck bits to facilitate the decoder.The encoder/decoder of the proposed codes has a similar structure to the original binary polar codes,admitting an easily configurable and flexible implementation,which is an obvious advantage over the existing nonbinary polar codes based on ReedSolomon(RS)codes.A low-complexity decoding method is also introduced,in which only more competitive symbols are considered rather than the whole q symbols in the finite field.To support high spectral efficiency,we also present,in addition to the single level coded modulation scheme with field-matched modulation order,a mixed multilevel coded modulation scheme with arbitrary modulation in order to trade off the latency against complexity.Simulation results show that our proposed nonbinary polar codes exhibit comparable performance with the RS4-based polar codes and outperform binary polar codes with low decoding latency,suggesting a potential application for future ultra-reliable and low-latency communications(URLLC).展开更多
In this paper,we proposed an active metasurface in reflection manner that can generate reconfigurable OAM vortex beams with high purity in the X-band.The metasurface has a high reflectance of 0.94 and achieves a phase...In this paper,we proposed an active metasurface in reflection manner that can generate reconfigurable OAM vortex beams with high purity in the X-band.The metasurface has a high reflectance of 0.94 and achieves a phase coverage of 320between 9.8 GHz and 11 GHz.Then,by encoding the phase distribution of the meta-atoms,various OAM vortex beams including 1,2,3,and 4 orders are generated,where the purity of all modes can be above 70%.Moreover,the metasurface can also deflect the OAM beam with a certain angle while maintaining high purity,which can be applied to reduce the influence of the alignment deviation between transmitting and receiving antennas during the communication processes.As a validation,the metasurface composed of 30×30 meta-atoms is fabricated and measured.Both simulation and measurement results demonstrate the capability of the proposed metasurface to generate reconfigurable OAM beams with high purity,indicating the application potentials of proposed meta-devices in future OAM communications.展开更多
In view of the difficulty of obtaining downlink channel state information,partial reciprocity based channel covariance matrix(CCM)reconstruction has attracted a lot of attention in frequency division duplex(FDD)multi-...In view of the difficulty of obtaining downlink channel state information,partial reciprocity based channel covariance matrix(CCM)reconstruction has attracted a lot of attention in frequency division duplex(FDD)multi-antenna systems.Taking both the impact of CCM reconstruction on system performance and design complexity,we investigate an adaptive CCM reconstruction in this paper.Specifically,to effectively evaluate the validity of the reciprocity,we firstly analyze the characteristics of the partial reciprocity and define a reciprocity evaluation criterion.Then,we propose a partial antenna based angular power spectrum(APS)estimating algorithm to further reduce the complexity of the CCM reconstruction.Finally,simulation results demonstrate the superiority of our proposed schemes.展开更多
Autoencoder-based rating prediction methods with external attributes have received wide attention due to their ability to accurately capture users'preferences.However,existing methods still have two significant li...Autoencoder-based rating prediction methods with external attributes have received wide attention due to their ability to accurately capture users'preferences.However,existing methods still have two significant limitations:i)External attributes are often unavailable in the real world due to privacy issues,leading to low quality of representations;and ii)existing methods lack considering complex associations in users'rating behaviors during the encoding process.To meet these challenges,this paper innovatively proposes an inherent-attribute-aware dual-graph autoencoder,named IADGAE,for rating prediction.To address the low quality of representations due to the unavailability of external attributes,we propose an inherent attribute perception module that mines inductive user active patterns and item popularity patterns from users'rating behaviors to strengthen user and item representations.To exploit the complex associations hidden in users’rating behaviors,we design an encoder on the item-item co-occurrence graph to capture the co-occurrence frequency features among items.Moreover,we propose a dual-graph feature encoder framework to simultaneously encode and fuse the high-order representations learned from the user-item rating graph and item-item co-occurrence graph.Extensive experiments on three real datasets demonstrate that IADGAE is effective and outperforms existing rating prediction methods,which achieves a significant improvement of 4.51%~41.63%in the RMSE metric.展开更多
Reconfigurable intelligent surfaces(RISs)are a promising technology for wireless communication applications,but their performance is often optimized using simplified electromagnetic reradiation models.In this study,we...Reconfigurable intelligent surfaces(RISs)are a promising technology for wireless communication applications,but their performance is often optimized using simplified electromagnetic reradiation models.In this study,we explore the impact on the RIS performance of more realistic assumptions,including the(possibly imperfect)quantization of the reflection coefficients,subwavelength inter-element spacing,near-field location,and presence of electromagnetic interference.We find that design constraints can cause an RIS to reradiate power in unwanted directions.Therefore,it is important to optimize an RIS by considering the entire reradiation pattern.Overall,our study indicates that a 2-bit digitally controllable RIS with a nearly constant reflection amplitude and RIS elements with a size and inter-element spacing between(1/8)th and(1/4)th of the signal wavelength may offer a reasonable tradeoff between performance,complexity,and cost.展开更多
Information metamaterials and metasurfaces are artificial structures composed of meta-atoms integrated with active tunable devices,which can tightly combine the physical and digital spaces.The digital coding represent...Information metamaterials and metasurfaces are artificial structures composed of meta-atoms integrated with active tunable devices,which can tightly combine the physical and digital spaces.The digital coding representation of the information metamaterials and metasurfaces can also introduce the concepts,theories,and signal processing methods in information science to the physical metamaterials and metasurfaces,thereby realizing effective controls of electromagnetic waves.In addition to manipulating the electromagnetic waves,the information metamaterials and metasurfaces can also process and modulate digital information.Hence,this concept has been emerging as an entirely new system of metamaterials and metasurfaces,which can provide unprecedented opportunities for achieving theoretical breakthroughs and new research methodologies,and building up novel electronic information platforms to revolutionize the traditional methods and functionalities in the applications of wireless communication,sensing,imaging,and radar systems.展开更多
The sharding technique enables blockchain to process transactions in parallel by dividing blockchain nodes into small groups,each of which handles a subset of all transactions.One of the issues with blockchain shardin...The sharding technique enables blockchain to process transactions in parallel by dividing blockchain nodes into small groups,each of which handles a subset of all transactions.One of the issues with blockchain sharding is generating a large number of cross-shard transactions that need to be checked on the output shard as well as the destination shard.Our analysis suggests that the processing efficiency of cross-shard transactions is consistent with the barrel effect,i.e.,that efficiency is more dependent on slower processing shard.Most of the existing studies focus on how to deal with cross-shard transactions,but neglecting the fact that the relative independence between sharding results in different incentive costs between sharding.We perform a sharding analysis on 100,000 real transactions data on Ethereum,and the results show that there is a large difference in gas prices between different shards indeed.In this paper,we propose an Adaptive Weight Incentive(AWI)for Blockchain Sharding,which uses adaptive weight in place of traditional incentive,to address the problem of differing incentive costs for each shard.Take Ethereum as an example,AWI-BS computes the weight of a transaction as a function of a combination of the underlying gas price,the latency of the transaction,and the urgency of the transaction.Then the node chooses which transaction to pack based on the AWI-BS.Lastly,we also perform an in-depth analysis of AWI-BS's security and effectiveness.The evaluation indicates that AWI-BS outperforms the other alternatives in terms of transaction confirmation latency,transaction hit rate,and system throughput.展开更多
基金supported in part by the China National Key R&D Program under Grant(YFA1000500)in part by the Key Research and Developement Program of Shaanxi under Grant(2017DCXL-GY-04-02).
文摘Deep learning based channel state information(CSI)fingerprint indoor localization schemes need to collect massive labeled data samples for training,and the parameters of the deep neural network are used as the fingerprints.However,the indoor environment may change,and the previously constructed fingerprint may not be valid for the changed environment.In order to adapt to the changed environment,it requires to recollect massive amount of labeled data samples and perform the training again,which is labor-intensive and time-consuming.In order to overcome this drawback,in this paper,we propose one novel domain adversarial neural network(DANN)based CSI Fingerprint Indoor Localization(D-Fi)scheme,which only needs the unlabeled data samples from the changed environment to update the fingerprint to adapt to the changed environment.Specifically,the previous environment and changed environment are treated as the source domain and the target domain,respectively.The DANN consists of the classification path and the domain-adversarial path,which share the same feature extractor.In the offline phase,the labeled CSI samples are collected as source domain samples to train the neural network of the classification path,while in the online phase,for the changed environment,only the unlabeled CSI samples are collected as target domain samples to train the neural network of the domainadversarial path to update parameters of the feature extractor.In this case,the feature extractor extracts the common features from both the source domain samples corresponding to the previous environment and the target domain samples corresponding to the changed environment.Experiment results show that for the changed localization environment,the proposed D-Fi scheme significantly outperforms the existing convolutional neural network(CNN)based scheme.
基金supported by the National Key Research and Development Program of China(2021YFA1401002,2017YFA0700201,2017YFA0700202 and 2017YFA0700203).
文摘It is of great importance to control flexibly wireless links in the modern society,especially with the advent of the Internet of Things(IoT),fifth-generation communication(5G),and beyond.Recently,we have witnessed that programmable metasurface(PM)or reconfigurable intelligent surface(RIS)has become a key enabling technology for manipulating flexibly the wireless link;however,one fundamental but challenging issue is to online design the PM's control sequence in a complicated wireless environment,such as the real-world indoor environment.Here,we propose a reinforcement learning(RL)approach to online control of the PM and thus in-situ improve the quality of the underline wireless link.We designed an inexpensive one-bit PM working at around 2.442 GHz and developed associated RL algorithms,and demonstrated experimentally that it is capable of enhancing the quality of commodity wireless link by a factor of about 10 dB and beyond in multiple scenarios,even if the wireless transmitter is in the glancing angle of the PM in the realworld indoor environment.Moreover,we also prove that our RL algorithm can be extended to improve the wireless signals of receivers in dual-receiver scenario.We faithfully expect that the presented technique could hold important potentials in future wireless communication,smart homes,and many other fields.
文摘Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft,and various types of real-time tasks are dynamically added at runtime.In order to improve the utilization of multi-core processors and ensure the real-time performance of the system,it is necessary to adopt a reasonable real-time task allocation method,but the existing methods are only for single-core processors or the performance is too low to be applicable.Aiming at the task allocation problem when mixed real-time tasks are dynamically added,we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF(Virtual Utilization Worst Fit)in multi-core processor.First,a 4-tuple task model is established to describe the fixedpoint task and the sporadic task in a unified manner.Then,a VDS(Virtual Deferral Server)for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is derived.Finally,combined with the analysis of VDS's capacity,VU-WF is proposed,which selects cores in ascending order of virtual utilization for the schedulability test.Experiments show that the overall performance of VU-WF is better than available algorithms,not only has a good schedulable ratio and load balancing but also has the lowest runtime overhead.In a 4-core processor,compared with available algorithms of the same schedulability ratio,the load balancing is improved by 73.9%,and the runtime overhead is reduced by 38.3%.In addition,we also develop a visual multi-core mixed task scheduling simulator RT-MCSS(open source)to facilitate the design and verification of multi-core scheduling for users.As the high performance,VU-WF can be widely used in resource-constrained and safety-critical real-time systems,such as spacecraft,self-driving cars,industrial robots,etc.
基金supported in part by the National Key R&D Program of China(2020YFB1807100)in part by the National Natural Science Foundation of China(61971454)in part by the Guangdong Basic and Applied Basic Research Foundation(2023A1515011056).
文摘In this paper,based on the block Markov superposition transmission(BMST)technique,we present a new class of coupled low-density parity-check(LDPC)codes for the transport block(TB)-based transmission to improve the error-correcting performance.For encoding,the previous LDPC codewords corresponding to a TB(at prior time slot)are interleaved and superimposed onto the current LDPC codewords,resulting in the transmitted codewords.For decoding,the sliding window decoding algorithm with sum-product or min-sum implementations can be employed,inheriting a relatively low-latency decoding.A distinguished advantage of the proposed coded transmission over spatially coupled LDPC(SC-LDPC)codes is that the encoder/decoder of the proposed codes can be designed by reusing the encoder/decoder architecture of component block LDPC codes.To analyze the waterfall performance of BMST-LDPC code ensembles,we present the protograph-based EXIT chart analysis,which can efficiently predict the error-correcting performance in waterfall region.To analyze the error-floor performance of BMST-LDPC codes,we employ the genie-aided(GA)lower bound,which can efficiently predict the error-correcting performance in error-floor region.For ease of implementation,the BMST-LDPC codes are constructed by taking the(2,4)-raptor-like LDPC codes or the 5G LDPC codes as the basic components.The numerical results reveal that the proposed codes can have capacity-approaching performance,exhibiting a gap of 0.007 dB away from the corresponding Shannon limit.They also reveal that,by using the proposed BMST construction,the error-correcting performance of the original 5G block LDPC codes can be significantly improved,achieving coding gains up to one dB over the AWGN channels and two dB over the fast fading channels.
基金National Natural Science Foundation of China(62288101,62001342)National Key Research and Development Program of China(2021YFA1401001)+1 种基金Key Research and Development Program of Shaanxi(2021TD-07)Fundamental Research Funds for the Central Universities(20103224952).
文摘A novel broadband metasurface (MTS) antenna array with high front-to-back ratio (FBR) is proposed for 28 GHz millimeter-wave applications. With slot pairs loaded on patch cells, an aperturecoupled slotted-mushroom MTS antenna is designed to obtain broadband radiation characteristicswith a compact size. To suppress the backward radiation of this antenna, the printed ridge gapwaveguide (PRGW) technology with a perfect magnetic conductor (PMC) shielding made ofmushroom unit-cells underneath the microstrip feeding line is applied. On this basis, a 4×4 MTSantenna array with the PRGW feed network is developed. Simulated results show that the FBR canbe highly improved by over 16 dB within the entire bandwidth. To validate the design, a prototypeof the proposed antenna is fabricated. Measured results show that an FBR greater than 28 dB canbe obtained over a 24% impedance bandwidth (from 24.9 GHz to 31.7 GHz) with the reflectioncoefficient less than 10 dB. The measured antenna gain ranges from 17 dBi to 19.2 dBi and thecorresponding measured aperture efficiencies are 35% and 45.6%. The measured results alsosuggest that the proposed MTS antenna possesses -35 dB cross-polarization level and stable radiation patterns. In addition, the proposed antenna remains a very low profile of 1.7 mm (0.17λ_(0) at28 GHz). All the achieved features indicate that the proposed MTS antenna is an importantcandidate for B5G and 6G wireless communication.
基金supported in part by the National Natural Science Foundation of China(62171354)the key R&D plan of Shaanxi Province(2019ZDLGY07-02)+1 种基金the Fundamental Research Funds for the Central Universities,the National Natural Science Foundation of China(61501347)the“111”project(B08038).
文摘Satellite communications and reconfigurable intelligent surface (RIS) are considered as twopromising technologies that can significantly improve the coverage and energy efficiency of futurewireless communication networks. The satellite communications security is often threatened dueto its broadcasting nature. To enhance the physical layer security (PLS) of satellite communications with channel similarity, an aerial RIS-aided dual full-duplex (DFD-ARIS) cooperative jamming method is presented in this paper. Specifically, unlike the existing works that relied onchannel difference, DFD-ARIS utilizes the channel similarity against the eavesdroppers with thehelp of ARIS. In addition, the power allocation is further studied in conjunction with the phasedesign of RIS to minimize the total power under the constraints of data rate, satellite powerlimitation and secrecy rate. Then, the closed-form solutions are achieved. Simulation results showthat the performance of the proposed scheme is superior to the traditional method.
基金supported in part by the Shaanxi Provincial Key Research and Development Program(2023-ZDLGY-33,2022ZDLGY05-03,2022ZDLGY05-04)in part by the Guangzhou Basic and Applied Basic Research Foundation(2023A04J1740)+1 种基金in part by the Innovation Fund of Xidian University(YJSJ23012)in part by the Fundamental Research Funds for the Central Universities(XJS220116).
文摘With the increasing popularity of civilian unmanned aerial vehicles(UAVs),safety issues arising from unsafe operations and terrorist activities have received growing attention.To address this problem,an accurate classification and positioning system is needed.Considering that UAVs usually use radio frequency(RF)signals for video transmission,in this paper,we design a passive distributed monitoring system that can classify and locate UAVs according to their RF signals.Specifically,three passive receivers are arranged in different locations to receive RF signals.Due to the noncooperation between a UAV and receivers,it is necessary to detect whether there is a UAV signal from the received signals.Hence,convolutional neural network(CNN)is proposed to not only detect the presence of the UAV,but also classify its type.After the UAV signal is detected,the time difference of arrival(TDOA)of the UAV signal arriving at the receiver is estimated by the cross-correlation method to obtain the corresponding distance difference.Finally,the Chan algorithm is used to calculate the location of the UAV.We deploy a distributed system constructed by three software defined radio(SDR)receivers on the campus playground,and conduct extensive experiments in a real wireless environment.The experimental results have successfully validated the proposed system.
文摘In this paper,we introduce a new concept,namelyε-arithmetics,for real vectors of any fixed dimension.The basic idea is to use vectors of rational values(called rational vectors)to approximate vectors of real values of the same dimension withinεrange.For rational vectors of a fixed dimension m,they can form a field that is an mth order extension Q(α)of the rational field Q whereαhas its minimal polynomial of degree m over Q.Then,the arithmetics,such as addition,subtraction,multiplication,and division,of real vectors can be defined by using that of their approximated rational vectors withinεrange.We also define complex conjugate of a real vector and then inner product and convolutions of two real vectors and two real vector sequences(signals)of finite length.With these newly defined concepts for real vectors,linear processing,such as linear filtering,ARMA modeling,and least squares fitting,can be implemented to real vectorvalued signals with real vector-valued coefficients,which will broaden the existing linear processing to scalar-valued signals.
基金supported by Joint Fund of Ministry of Education of China(8091B022149)Key Research and Development Program of Shaanxi(2021ZDLGY01-03)+1 种基金National Natural Science Foundation of China(62132016,62171343,62071361 and 62201436)Fundamental Research Funds for the Central Universities(ZDRC2102 and ZYTS23135).
文摘Graph convolutional networks(GCNs)have been successfully applied to node representation learning in various real-world applications.However,the performance of GCNs drops rapidly when the labeled data are severely scarce,and the node features are prone to being indistinguishable with stacking more layers,causing over-fitting and over-smoothing problems.In this paper,we propose a simple yet effective contrastive semantic calibration for graph convolution network(CSC-GCN),which integrates stochastic identity aggregation and semantic calibration to overcome these weaknesses.The basic idea is the node features obtained from different aggregation operations should be similar.Toward that end,identity aggregation is utilized to extract semantic features from labeled nodes,while stochastic label noise is adopted to alleviate the over-fitting problem.Then,contrastive learning is employed to improve the discriminative ability of the node features,and the features from different aggregation operations are calibrated according to the class center similarity.In this way,the similarity between unlabeled features and labeled ones from the same class is enhanced while effectively reducing the over-smoothing problem.Experimental results on eight popular datasets show that the proposed CSC-GCN outperforms state-ofthe-art methods on various classification tasks.
基金supported by National Natural Science Foundation of China(62071215,62271243,91963128)National Key Research and Development Program of China(2017YFA0700201)the Joint Fund of Ministry of Education for Equipment Pre-research(8091B032112),Priority Academic Program Development of Jiangsu Higher Education Institutions,Fundamental Research Funds for the Central Universities and Jiangsu Provincial Key Laboratory of Advanced Manipulating Technique of Electromagnetic Wave.
文摘Reconfigurable intelligent surface(RIS)is emerged as a promising technique to solve the challenges faced by future wireless communication networks.Although the most commonly used electrically-controlled RISs can achieve millisecond-scale speed of dynamic switch,they have a large number of microwave circuit elements(such as PIN diodes or varactors)which will bring non-negligible insertion loss,and the complicity of the bias network to electrically addressing each element will increase with the expansion of the RIS aperture.Aiming at further reducing the fabrication cost and power consumption,herein an electromechanical RIS used for sub-6G wireless communication is proposed.The electromechanical RIS is designed with a passive metasurface and step-motor driver modules,providing simultaneous high-efficiency reflection(over 80%)and continuous reflection phase coverage of 360.Through electromechanical control,the RIS system can realize different reflective wavefront shaping,and has been employed in the indoor sub-6G wireless environment demonstrating a maximum signal improvement of 8.3 dB.The proposed electromechanical RIS is particularly useful for wireless signal enhancement in static blind area,and has the obvious advantage of not requiring continuous power supply after the RIS being regulated.Therefore,it greatly reduces the overall cost and power consumption which may have potentials in indoor application scenarios for improving wireless communication performance.
基金supported by National Natural Science Foundation of China(62288101 and 62001342)National Key Research and Development Program of China(2021YFA1401001)+1 种基金Key Research and Development Program of Shaanxi(2021TD-07)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University。
文摘This paper proposes a new method to generate a two-dimensional(2D)Airy beam and Airy autofocusing beam by using the scalar holographic metasurface with amplitude-phase modulation in the microwave band.The proposed holographic metasurface comprises subwavelength patch unit cells with a period of fewer than 1/8 wavelengths,which means that it has the finer sampling for electromagnetic waves and can simultaneously achieve precise modulations for the amplitude and phase of electromagnetic waves.Firstly,the 2D-Airy beam with quasi-non-diffraction and selfbending characteristics is generated,from which the holographic metasurface is designed to realize four different 2D-Airy beams with the same focus,achieving the 2D-Airy autofocusing beam in the microwave frequency.The holographic metasurface for Airy beam generation has high efficiency and an ultra-lower profile.Meanwhile,for applying the Airy beam in wireless power transfer(WPT),the efficiency of the generated Airy beam and Airy autofocusing beam is calculated for the first time in the microwave field.The simulation results show that the efficiency of the 2D-Airy beam can reach 66%at 150 mm away from the metasurface,while the efficiency of the 2D-Airy autofocusing beam at the focus,which is 280 mm from the metasurface,can reach 35%.The theoretical,simulated,and measured results show that the proposed method and holographic metasurfaces can flexibly achieve the special characteristics of self-autofocusing and self-bending Airy beams in the microwave domain,providing an effective path for wireless power transfer(WPT)scenario with radial obstructions.
基金supported in part by the National Key R&D Program of China(2018YFE0100500)by the National Natural Science Foundation of China(61871387,61861041,and 62171354)by the Natural Science Basic Research Program of Shaanxi(2019JM-019).
文摘The joint adoption of sub-6GHz and millimeter wave(mmWave)technology can prevent the blind spots of coverage,enabling comprehensive coverage while realizing high-speed communication rate.According to the sensitivity of mmWave,base stations should be more densely deployed,which is not well described by existing Poisson hole process(PHP)and the Poisson point process(PPP)models.This paper establishes a sub-6GHz and mmWave hybrid heterogeneous cellular network based on the modified Poisson hole process(MPHP).In our proposed model,the sub-6GHz base stations follow the PPP,and the mmWave base stations(MBSs)follow MPHP distribution.The expressions of the coverage probability are derived by using the interference calculation method of integrating the nearest sector exclusion area.Our theoretical analysis has been verified through simulation results,suggesting that the increase in the cell radius decreases the coverage probability of signal-to-interference-plus-noise ratio(SINR),whereas the increase in the sector parameter has the opposite effect.The variation of sub-6GHz base stations(SBSs)density imposes more significant impact than the MBSs on the SINR coverage probability.In addition,the decrease in MBSs density will reduce the average bandwidth allocated to the user equipment(UE),thus reducing the rate coverage probability.
基金supported by the National Key R&D Program of China(2022YFB3102100)Shenzhen Fundamental Research Program(JCYJ20220818102414030)+2 种基金the Major Key Project of PCL(PCL2022A03)Shenzhen Science and Technology Program(ZDSYS20210623091809029)Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies(2022B1212010005).
文摘To solve the data island problem,federated learning(FL)provides a solution paradigm where each client sends the model parameters but not the data to a server for model aggregation.Peer-to-peer(P2P)federated learning further improves the robustness of the system,in which there is no server and each client communicates directly with the other.For secure aggregation,secure multi-party computing(SMPC)protocols have been utilized in peer-to-peer manner.However,the ideal SMPC protocols could fail when some clients drop out.In this paper,we propose a robust peer-to-peer learning(RP2PL)algorithm via SMPC to resist clients dropping out.We improve the segmentbased SMPC protocol by adding a check and designing the generation method of random segments.In RP2PL,each client aggregates their models by the improved robust secure multi-part computation protocol when finishes the local training.Experimental results demonstrate that the RP2PL paradigm can mitigate clients dropping out with no significant degradation in performance.
基金supported in part by the National Key R&D Program of China(2021YFA1000500)by the National Natural Science Foundation of China(62171356).
文摘In this paper,we propose a new class of nonbinary polar codes,where the symbol-level polarization is achieved by using a 2×2 q-ary matrix[10β1]as the kernel.Under bit-level code construction,some partially-frozen symbols exist,where the frozen bits in these symbols can be used as activecheck bits to facilitate the decoder.The encoder/decoder of the proposed codes has a similar structure to the original binary polar codes,admitting an easily configurable and flexible implementation,which is an obvious advantage over the existing nonbinary polar codes based on ReedSolomon(RS)codes.A low-complexity decoding method is also introduced,in which only more competitive symbols are considered rather than the whole q symbols in the finite field.To support high spectral efficiency,we also present,in addition to the single level coded modulation scheme with field-matched modulation order,a mixed multilevel coded modulation scheme with arbitrary modulation in order to trade off the latency against complexity.Simulation results show that our proposed nonbinary polar codes exhibit comparable performance with the RS4-based polar codes and outperform binary polar codes with low decoding latency,suggesting a potential application for future ultra-reliable and low-latency communications(URLLC).
基金supported by the National Natural Science Foundation of China(62171165)。
文摘In this paper,we proposed an active metasurface in reflection manner that can generate reconfigurable OAM vortex beams with high purity in the X-band.The metasurface has a high reflectance of 0.94 and achieves a phase coverage of 320between 9.8 GHz and 11 GHz.Then,by encoding the phase distribution of the meta-atoms,various OAM vortex beams including 1,2,3,and 4 orders are generated,where the purity of all modes can be above 70%.Moreover,the metasurface can also deflect the OAM beam with a certain angle while maintaining high purity,which can be applied to reduce the influence of the alignment deviation between transmitting and receiving antennas during the communication processes.As a validation,the metasurface composed of 30×30 meta-atoms is fabricated and measured.Both simulation and measurement results demonstrate the capability of the proposed metasurface to generate reconfigurable OAM beams with high purity,indicating the application potentials of proposed meta-devices in future OAM communications.
基金supported in part by the Shaanxi Provincial Key Research and Development Programs(2023-ZDLGY-33,2022ZDLGY05-03,2022ZDLGY05-04,2021ZDLGY04-08).
文摘In view of the difficulty of obtaining downlink channel state information,partial reciprocity based channel covariance matrix(CCM)reconstruction has attracted a lot of attention in frequency division duplex(FDD)multi-antenna systems.Taking both the impact of CCM reconstruction on system performance and design complexity,we investigate an adaptive CCM reconstruction in this paper.Specifically,to effectively evaluate the validity of the reciprocity,we firstly analyze the characteristics of the partial reciprocity and define a reciprocity evaluation criterion.Then,we propose a partial antenna based angular power spectrum(APS)estimating algorithm to further reduce the complexity of the CCM reconstruction.Finally,simulation results demonstrate the superiority of our proposed schemes.
基金supported in part by National Natural Science Foundation of China(U21B2015,61972300)in part by Young Scientists Fund of the National Natural Science Foundation of China(62202356)+1 种基金in part by Young Talent Fund of Association for Science and Technology in Shaanxi(20220113)in part by Intelligent Financial Software Engineering New Technology Joint Laboratory Project(99901220858)。
文摘Autoencoder-based rating prediction methods with external attributes have received wide attention due to their ability to accurately capture users'preferences.However,existing methods still have two significant limitations:i)External attributes are often unavailable in the real world due to privacy issues,leading to low quality of representations;and ii)existing methods lack considering complex associations in users'rating behaviors during the encoding process.To meet these challenges,this paper innovatively proposes an inherent-attribute-aware dual-graph autoencoder,named IADGAE,for rating prediction.To address the low quality of representations due to the unavailability of external attributes,we propose an inherent attribute perception module that mines inductive user active patterns and item popularity patterns from users'rating behaviors to strengthen user and item representations.To exploit the complex associations hidden in users’rating behaviors,we design an encoder on the item-item co-occurrence graph to capture the co-occurrence frequency features among items.Moreover,we propose a dual-graph feature encoder framework to simultaneously encode and fuse the high-order representations learned from the user-item rating graph and item-item co-occurrence graph.Extensive experiments on three real datasets demonstrate that IADGAE is effective and outperforms existing rating prediction methods,which achieves a significant improvement of 4.51%~41.63%in the RMSE metric.
基金supported by the European Commission through the H2020 ARIADNE project(871464)the H2020 RISE-6G project(101017011)+2 种基金the H2020 MetaWireless project(956256)the H2020 PAINLESS project(812991)the Fulbright Foundation under the“Programme National Chercheurs 2021”funding scheme,and the Agence Nationale de la Recherche(ANR)through the PEPR-5G project.
文摘Reconfigurable intelligent surfaces(RISs)are a promising technology for wireless communication applications,but their performance is often optimized using simplified electromagnetic reradiation models.In this study,we explore the impact on the RIS performance of more realistic assumptions,including the(possibly imperfect)quantization of the reflection coefficients,subwavelength inter-element spacing,near-field location,and presence of electromagnetic interference.We find that design constraints can cause an RIS to reradiate power in unwanted directions.Therefore,it is important to optimize an RIS by considering the entire reradiation pattern.Overall,our study indicates that a 2-bit digitally controllable RIS with a nearly constant reflection amplitude and RIS elements with a size and inter-element spacing between(1/8)th and(1/4)th of the signal wavelength may offer a reasonable tradeoff between performance,complexity,and cost.
文摘Information metamaterials and metasurfaces are artificial structures composed of meta-atoms integrated with active tunable devices,which can tightly combine the physical and digital spaces.The digital coding representation of the information metamaterials and metasurfaces can also introduce the concepts,theories,and signal processing methods in information science to the physical metamaterials and metasurfaces,thereby realizing effective controls of electromagnetic waves.In addition to manipulating the electromagnetic waves,the information metamaterials and metasurfaces can also process and modulate digital information.Hence,this concept has been emerging as an entirely new system of metamaterials and metasurfaces,which can provide unprecedented opportunities for achieving theoretical breakthroughs and new research methodologies,and building up novel electronic information platforms to revolutionize the traditional methods and functionalities in the applications of wireless communication,sensing,imaging,and radar systems.
基金supported by FDCT under its General R&D Subsidy Program Fund(0038/2022/A)。
文摘The sharding technique enables blockchain to process transactions in parallel by dividing blockchain nodes into small groups,each of which handles a subset of all transactions.One of the issues with blockchain sharding is generating a large number of cross-shard transactions that need to be checked on the output shard as well as the destination shard.Our analysis suggests that the processing efficiency of cross-shard transactions is consistent with the barrel effect,i.e.,that efficiency is more dependent on slower processing shard.Most of the existing studies focus on how to deal with cross-shard transactions,but neglecting the fact that the relative independence between sharding results in different incentive costs between sharding.We perform a sharding analysis on 100,000 real transactions data on Ethereum,and the results show that there is a large difference in gas prices between different shards indeed.In this paper,we propose an Adaptive Weight Incentive(AWI)for Blockchain Sharding,which uses adaptive weight in place of traditional incentive,to address the problem of differing incentive costs for each shard.Take Ethereum as an example,AWI-BS computes the weight of a transaction as a function of a combination of the underlying gas price,the latency of the transaction,and the urgency of the transaction.Then the node chooses which transaction to pack based on the AWI-BS.Lastly,we also perform an in-depth analysis of AWI-BS's security and effectiveness.The evaluation indicates that AWI-BS outperforms the other alternatives in terms of transaction confirmation latency,transaction hit rate,and system throughput.
