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doi: 10.1049/cje.2020.00.125
Abstract:
2022, 31(3): 397-407.
doi: 10.1049/cje.2021.00.314
Abstract:
With flexibility, convenience and mobility, unmanned aerial vehicles (UAVS) can provide wireless communication networks with lower costs, easier deployment, higher network scalability and larger coverage. This paper proposes the deep deterministic policy gradient algorithm to jointly optimize the power allocation and flight trajectory of UAV with constrained effective energy to maximize the downlink throughput to ground users. To validate the proposed algorithm, we compare with the random algorithm, Q-learning algorithm and deep Q network algorithm. The simulation results show that the proposed algorithm can effectively improve the communication quality and significantly extend the service time of UAV. In addition, the downlink throughput increases with the number of ground users.
With flexibility, convenience and mobility, unmanned aerial vehicles (UAVS) can provide wireless communication networks with lower costs, easier deployment, higher network scalability and larger coverage. This paper proposes the deep deterministic policy gradient algorithm to jointly optimize the power allocation and flight trajectory of UAV with constrained effective energy to maximize the downlink throughput to ground users. To validate the proposed algorithm, we compare with the random algorithm, Q-learning algorithm and deep Q network algorithm. The simulation results show that the proposed algorithm can effectively improve the communication quality and significantly extend the service time of UAV. In addition, the downlink throughput increases with the number of ground users.
2022, 31(3): 408-415.
doi: 10.1049/cje.2021.00.278
Abstract:
Unmanned aerial vehicle (UAV) as a powerful tool has found its applicability in assisting mobile users to deal with computation-intensive and delay-sensitive applications (e.g., edge computing, high-speed Internet access, and local caching). However, deployment of UAV-aided mobile services (UMS) faces challenges due to the UAV limitation in wireless coverage and energy storage. Aware of such physical limitations, a future UMS system should be intelligent enough to self-plan trajectories and best offer computational capabilities to mobile users. There are important issues regarding the UAV-user interaction, UAV-UAV cooperation for sustainable service provision, and dynamic UMS pricing. These networking and resource management issues are largely overlooked in the literature and this article presents intelligent solutions for cooperative UMS deployment and operation. Mobile users’ locations are generally private information and changing over time. How to learn on-demand users’ truthful location reporting is important for determining optimal UAV deployment in serving all the users fairly. After addressing the truthful UAV-user interaction issue via game theory, we further study the UAV network sustainability for UMS provision by minimizing the energy consumption cost during deployment and seeking UAV-UAV cooperation. Finally, for profit-maximizing purpose, we analyze the cooperative UAVs’ deployment, capacity allocation, and dynamic service pricing.
Unmanned aerial vehicle (UAV) as a powerful tool has found its applicability in assisting mobile users to deal with computation-intensive and delay-sensitive applications (e.g., edge computing, high-speed Internet access, and local caching). However, deployment of UAV-aided mobile services (UMS) faces challenges due to the UAV limitation in wireless coverage and energy storage. Aware of such physical limitations, a future UMS system should be intelligent enough to self-plan trajectories and best offer computational capabilities to mobile users. There are important issues regarding the UAV-user interaction, UAV-UAV cooperation for sustainable service provision, and dynamic UMS pricing. These networking and resource management issues are largely overlooked in the literature and this article presents intelligent solutions for cooperative UMS deployment and operation. Mobile users’ locations are generally private information and changing over time. How to learn on-demand users’ truthful location reporting is important for determining optimal UAV deployment in serving all the users fairly. After addressing the truthful UAV-user interaction issue via game theory, we further study the UAV network sustainability for UMS provision by minimizing the energy consumption cost during deployment and seeking UAV-UAV cooperation. Finally, for profit-maximizing purpose, we analyze the cooperative UAVs’ deployment, capacity allocation, and dynamic service pricing.
2022, 31(3): 416-429.
doi: 10.1049/cje.2021.00.305
Abstract:
Unmanned aerial vehicles (UAVs) have recently been regarded as a promising technology in Internet of things (IoT). UAVs functioned as intermediate relay nodes are capable of establishing uninterrupted and high-quality communication links between remotely deployed IoT devices and the destination. Multiple UAVs are required to be deployed due to their limited onboard energy. We study a UAV pair-supported relaying in unknown IoT systems, which consists of transmitter and receiver. Our goal is that transmitter gathers the data from each device then transfers the information to receiver, and receiver finally transmits the information to the destination, while meeting the constraint that the amount of information received from each device reaches a certain threshold. This is an optimization problem with highly coupled variables, such as trajectories of transmitter and receiver. On account of no prior knowledge of the environment, a dueling double deep Q network (dueling DDQN) algorithm is proposed to solve the problem. Whether it is in the phase of transmitter’s receiving information or the phase of transmitter’s forwarding information to receiver, the effectiveness and superiority of the proposed algorithm is demonstrated by extensive simulationsin in comparison to some base schemes under different scenarios.
Unmanned aerial vehicles (UAVs) have recently been regarded as a promising technology in Internet of things (IoT). UAVs functioned as intermediate relay nodes are capable of establishing uninterrupted and high-quality communication links between remotely deployed IoT devices and the destination. Multiple UAVs are required to be deployed due to their limited onboard energy. We study a UAV pair-supported relaying in unknown IoT systems, which consists of transmitter and receiver. Our goal is that transmitter gathers the data from each device then transfers the information to receiver, and receiver finally transmits the information to the destination, while meeting the constraint that the amount of information received from each device reaches a certain threshold. This is an optimization problem with highly coupled variables, such as trajectories of transmitter and receiver. On account of no prior knowledge of the environment, a dueling double deep Q network (dueling DDQN) algorithm is proposed to solve the problem. Whether it is in the phase of transmitter’s receiving information or the phase of transmitter’s forwarding information to receiver, the effectiveness and superiority of the proposed algorithm is demonstrated by extensive simulationsin in comparison to some base schemes under different scenarios.
2022, 31(3): 430-441.
doi: 10.1049/cje.2021.00.285
Abstract:
To improve the time-varying channel estimation accuracy of orthogonal frequency division multiplexing air-ground datalink in complex environment, this paper proposes a time-varying air-ground channel estimation algorithm based on the modulated learning networks, termed as MB-ChanEst-TV. The algorithm integrates the modulated convolutional neural networks (MCNN) with the bidirectional long short term memory (Bi-LSTM), where the MCNN subnetworks accomplish channel interpolation in frequency domain and compress the network model while the Bi-LSTM subnetworks achieve channel prediction in time domain. Considering the unique characteristics of airframe shadowing for unmanned aircraft systems, we propose to combine the classical 2-ray channel model with the tapped delay line model and present a more realistic channel impulse response samples generation approach, whose code and dataset have been made publicly available. We demonstrate the effectiveness of our proposed approach on the generated dataset, where experimental results indicate that the MB-ChanEst-TV model outperforms existing state-of-the-art methods with a lower estimation error and better bit error ratio performance under different signal to noise ratio conditions. We also analyze the effect of roll angle of the aircraft and the duration percentage of the airframe shadow on the channel estimation.
To improve the time-varying channel estimation accuracy of orthogonal frequency division multiplexing air-ground datalink in complex environment, this paper proposes a time-varying air-ground channel estimation algorithm based on the modulated learning networks, termed as MB-ChanEst-TV. The algorithm integrates the modulated convolutional neural networks (MCNN) with the bidirectional long short term memory (Bi-LSTM), where the MCNN subnetworks accomplish channel interpolation in frequency domain and compress the network model while the Bi-LSTM subnetworks achieve channel prediction in time domain. Considering the unique characteristics of airframe shadowing for unmanned aircraft systems, we propose to combine the classical 2-ray channel model with the tapped delay line model and present a more realistic channel impulse response samples generation approach, whose code and dataset have been made publicly available. We demonstrate the effectiveness of our proposed approach on the generated dataset, where experimental results indicate that the MB-ChanEst-TV model outperforms existing state-of-the-art methods with a lower estimation error and better bit error ratio performance under different signal to noise ratio conditions. We also analyze the effect of roll angle of the aircraft and the duration percentage of the airframe shadow on the channel estimation.
2022, 31(3): 442-455.
doi: 10.1049/cje.2021.00.310
Abstract:
Interference source localization with high accuracy and time efficiency is of crucial importance for protecting spectrum resources. Due to the flexibility of unmanned aerial vehicles (UAVs), exploiting UAVs to locate the interference source has attracted intensive research interests. The off-the-shelf UAV-based interference source localization schemes locate the interference sources by employing the UAV to keep searching until it arrives at the target. This obviously degrades time efficiency of localization. To balance the accuracy and the efficiency of searching and localization, this paper proposes a multi-UAV-based cooperative framework alone with its detailed scheme, where search and remote localization are iteratively performed with a swarm of UAVs. For searching, a low-complexity Q-learning algorithm is proposed to decide the direction of flight in every time interval for each UAV. In the following remote localization phase, a fast Fourier transformation based location prediction algorithm is proposed to estimate the location of the interference source by fusing the searching result of different UAVs in different time intervals. Numerical results reveal that in the proposed scheme outperforms the state-of-the-art schemes, in terms of the accuracy, the robustness and time efficiency of localization.
Interference source localization with high accuracy and time efficiency is of crucial importance for protecting spectrum resources. Due to the flexibility of unmanned aerial vehicles (UAVs), exploiting UAVs to locate the interference source has attracted intensive research interests. The off-the-shelf UAV-based interference source localization schemes locate the interference sources by employing the UAV to keep searching until it arrives at the target. This obviously degrades time efficiency of localization. To balance the accuracy and the efficiency of searching and localization, this paper proposes a multi-UAV-based cooperative framework alone with its detailed scheme, where search and remote localization are iteratively performed with a swarm of UAVs. For searching, a low-complexity Q-learning algorithm is proposed to decide the direction of flight in every time interval for each UAV. In the following remote localization phase, a fast Fourier transformation based location prediction algorithm is proposed to estimate the location of the interference source by fusing the searching result of different UAVs in different time intervals. Numerical results reveal that in the proposed scheme outperforms the state-of-the-art schemes, in terms of the accuracy, the robustness and time efficiency of localization.
2022, 31(3): 456-466.
doi: 10.1049/cje.2021.00.275
Abstract:
Space-air-ground integrated network is capable of providing seamless and ubiquitous services to cater for the increasing wireless communication demands of emerging applications. However, how to efficiently manage the heterogeneous resources and protect the privacy of connected devices is a very challenging issue, especially under the highly dynamic network topology and multiple trustless network operators. In this paper, we investigate blockchain-empowered dynamic spectrum management by reaping the advantages of blockchain and software defined network (SDN), where operators are incentive to share their resources in a common resourced pool. We first propose a blockchain enabled spectrum management framework for space-air-ground integrated network, with inter-slice spectrum sharing and intra-slice spectrum allocation. Specifically, the inter-slice spectrum sharing is realized through a consortium blockchain formed by the upper-tier SDN controllers, and then a graph coloring based channel assignment algorithm is proposed to manage the intra-slice spectrum assignment. A bilateral confirmation protocol and a consensus mechanism are also proposed for the consortium blockchain. The simulation results prove that our proposed consensus algorithm takes less time than practical Byzantine fault tolerance algorithm to reach a consensus, and the proposed channel assignment algorithm significantly improves the spectrum utilization and outperforms the baseline algorithm in both simulation and real-world scenarios.
Space-air-ground integrated network is capable of providing seamless and ubiquitous services to cater for the increasing wireless communication demands of emerging applications. However, how to efficiently manage the heterogeneous resources and protect the privacy of connected devices is a very challenging issue, especially under the highly dynamic network topology and multiple trustless network operators. In this paper, we investigate blockchain-empowered dynamic spectrum management by reaping the advantages of blockchain and software defined network (SDN), where operators are incentive to share their resources in a common resourced pool. We first propose a blockchain enabled spectrum management framework for space-air-ground integrated network, with inter-slice spectrum sharing and intra-slice spectrum allocation. Specifically, the inter-slice spectrum sharing is realized through a consortium blockchain formed by the upper-tier SDN controllers, and then a graph coloring based channel assignment algorithm is proposed to manage the intra-slice spectrum assignment. A bilateral confirmation protocol and a consensus mechanism are also proposed for the consortium blockchain. The simulation results prove that our proposed consensus algorithm takes less time than practical Byzantine fault tolerance algorithm to reach a consensus, and the proposed channel assignment algorithm significantly improves the spectrum utilization and outperforms the baseline algorithm in both simulation and real-world scenarios.
2022, 31(3): 467-487.
doi: 10.1049/cje.2021.00.302
Abstract:
The special position of terahertz wave in the electromagnetic spectrum makes it possess the characteristics of orientation, broadband, penetration and low energy, which promotes the extensive research of terahertz wave in the fields of communication, radar, imaging, sensing, security inspection and so on. The solid-state terahertz sources based on semiconductor devices have attracted extensive attention in the field of terahertz information technology due to their characteristics such as being able to work at room temperature, being small in size, being easy to integrate and having good frequency stability. Terahertz planar Schottky diode is a kind of low parasitic semiconductor device. Its high cutoff frequency makes it work well in the terahertz range. The frequency multiplier based on planar Schottky diode is an important part of terahertz solid state source. In this review, the development of Schottky diodes technology in recent years have been introduced, including the structures and preparation of Schottky diodes. In addition, the current situation and performance of different types of terahertz sources based on Schottky diodes are further introduced, and the future development trend is discussed.
The special position of terahertz wave in the electromagnetic spectrum makes it possess the characteristics of orientation, broadband, penetration and low energy, which promotes the extensive research of terahertz wave in the fields of communication, radar, imaging, sensing, security inspection and so on. The solid-state terahertz sources based on semiconductor devices have attracted extensive attention in the field of terahertz information technology due to their characteristics such as being able to work at room temperature, being small in size, being easy to integrate and having good frequency stability. Terahertz planar Schottky diode is a kind of low parasitic semiconductor device. Its high cutoff frequency makes it work well in the terahertz range. The frequency multiplier based on planar Schottky diode is an important part of terahertz solid state source. In this review, the development of Schottky diodes technology in recent years have been introduced, including the structures and preparation of Schottky diodes. In addition, the current situation and performance of different types of terahertz sources based on Schottky diodes are further introduced, and the future development trend is discussed.
2022, 31(3): 488-498.
doi: 10.1049/cje.2021.00.263
Abstract:
Terahertz (THz) communications are considered as very promising for the sixth-generation (6G) ultra-dense wireless networks. However, THz signals suffer from well-known severe path loss, which consequently shortens the coverage of THz communication systems. To deal with this issue, precoding technique is expected to be beneficial to extend the limited coverage by providing directional beams with ultra large number of antenna arrays. In this paper, we overview the state-of-the-art developments of THz precoding techniques such as reconfigurable intelligent surface based precoding, hybrid digital-analog precoding and delay-phase precoding. Based on the survey, we summarize several open issues remaining to be addressed, and discuss the prospects of a few potential research directions on THz precoding, such as one-bit precoding, precoding for hardware impairments and THz security precoding. This overview will be helpful for researchers to study innovative solutions of THz precoding in the future 6G wireless communications.
Terahertz (THz) communications are considered as very promising for the sixth-generation (6G) ultra-dense wireless networks. However, THz signals suffer from well-known severe path loss, which consequently shortens the coverage of THz communication systems. To deal with this issue, precoding technique is expected to be beneficial to extend the limited coverage by providing directional beams with ultra large number of antenna arrays. In this paper, we overview the state-of-the-art developments of THz precoding techniques such as reconfigurable intelligent surface based precoding, hybrid digital-analog precoding and delay-phase precoding. Based on the survey, we summarize several open issues remaining to be addressed, and discuss the prospects of a few potential research directions on THz precoding, such as one-bit precoding, precoding for hardware impairments and THz security precoding. This overview will be helpful for researchers to study innovative solutions of THz precoding in the future 6G wireless communications.
2017, 26(5): 1057-1063.
doi: 10.1049/cje.2017.08.024
摘要：
According to the standard for the GSM for railway (GSM-R) wireless systems in China train control system level 3 (CTCS-3), the control data transfer delay should be no larger than 500ms with greater than 99% probability. Coverage of both non-redundant networks and intercross redundant networks and cases of single Mobile terminals (MTs) and redundant MTs on one train are considered, and the corresponding vehicle-ground communication models, delay models, and fault models are constructed. The simulation results confirm that the transfer delay can meet the standard requirements under all cases. In particular, the probability is greater than 99.996% for redundant MTs and networks, and the standard of transfer delay in CTCS-3 will be improved inevitably.
According to the standard for the GSM for railway (GSM-R) wireless systems in China train control system level 3 (CTCS-3), the control data transfer delay should be no larger than 500ms with greater than 99% probability. Coverage of both non-redundant networks and intercross redundant networks and cases of single Mobile terminals (MTs) and redundant MTs on one train are considered, and the corresponding vehicle-ground communication models, delay models, and fault models are constructed. The simulation results confirm that the transfer delay can meet the standard requirements under all cases. In particular, the probability is greater than 99.996% for redundant MTs and networks, and the standard of transfer delay in CTCS-3 will be improved inevitably.
2017, 26(1): 1-12.
doi: 10.1049/cje.2016.11.016
摘要：
The explosive growth of data volume and the ever-increasing demands of data value extraction have driven us into the era of big data. The "5V" (Variety, Velocity, Volume, Value, and Veracity) characteristics of big data pose great challenges to traditional computing paradigms and motivate the emergence of new solutions. Cloud computing is one of the representative technologies that can perform massive-scale and complex data computing by taking advantages of virtualized resources, parallel processing and data service integration with scalable data storage. However, as we are also experiencing the revolution of Internet-of-things (IoT), the limitations of cloud computing on supporting lightweight end devices significantly impede the flourish of cloud computing at the intersection of big data and IoT era. It also promotes the urgency of proposing new computing paradigms. We provide an overview on the topic of big data, and a comprehensive survey on how cloud computing as well as its related technologies can address the challenges arisen by big data. Then, we analyze the disadvantages of cloud computing when big data encounters IoT, and introduce two promising computing paradigms, including fog computing and transparent computing, to support the big data services of IoT. Finally, some open challenges and future directions are summarized to foster continued research efforts into this evolving field of study.
The explosive growth of data volume and the ever-increasing demands of data value extraction have driven us into the era of big data. The "5V" (Variety, Velocity, Volume, Value, and Veracity) characteristics of big data pose great challenges to traditional computing paradigms and motivate the emergence of new solutions. Cloud computing is one of the representative technologies that can perform massive-scale and complex data computing by taking advantages of virtualized resources, parallel processing and data service integration with scalable data storage. However, as we are also experiencing the revolution of Internet-of-things (IoT), the limitations of cloud computing on supporting lightweight end devices significantly impede the flourish of cloud computing at the intersection of big data and IoT era. It also promotes the urgency of proposing new computing paradigms. We provide an overview on the topic of big data, and a comprehensive survey on how cloud computing as well as its related technologies can address the challenges arisen by big data. Then, we analyze the disadvantages of cloud computing when big data encounters IoT, and introduce two promising computing paradigms, including fog computing and transparent computing, to support the big data services of IoT. Finally, some open challenges and future directions are summarized to foster continued research efforts into this evolving field of study.
2016, 25(3): 397-402.
doi: 10.1049/cje.2016.05.001
摘要：
A clustering algorithm named "Clustering by fast search and find of density peaks" is for finding the centers of clusters quickly. Its accuracy excessively depended on the threshold, and no efficient way was given to select its suitable value, i.e., the value was suggested be estimated on the basis of empirical experience. A new way is proposed to automatically extract the optimal value of threshold by using the potential entropy of data field from the original dataset. For any dataset to be clustered, the threshold can be calculated from the dataset objectively instead of empirical estimation. The results of comparative experiments have shown the algorithm with the threshold from data field can get better clustering results than with the threshold from empirical experience.
A clustering algorithm named "Clustering by fast search and find of density peaks" is for finding the centers of clusters quickly. Its accuracy excessively depended on the threshold, and no efficient way was given to select its suitable value, i.e., the value was suggested be estimated on the basis of empirical experience. A new way is proposed to automatically extract the optimal value of threshold by using the potential entropy of data field from the original dataset. For any dataset to be clustered, the threshold can be calculated from the dataset objectively instead of empirical estimation. The results of comparative experiments have shown the algorithm with the threshold from data field can get better clustering results than with the threshold from empirical experience.
2018, 27(2): 439-444.
doi: 10.1049/cje.2017.10.009
摘要：
This research investigate the information interaction protocols for Cooperative vehicleinfrastructure systems (CVIS) safety-related services and optimizes them in three aspects. It puts forward a selfadaptive back-off algorithm. This algorithm considers retransmission times and network busy degree to choose a suitable contention window. A mathematical analysis model is developed to verify its performance improvement. Finally, different scenario models of Vehicle ad hoc network (VANET) are simulated through the network simulation tool and the influences of different access modes on Quality of Service (QoS) are investigated. The simulation results have verified the improvement of the proposed algorithm is obvious and RTS/CTS access mode can sacrifice slight delay for great improvement of packet lost rate when there are large amount of vehicle nodes.
This research investigate the information interaction protocols for Cooperative vehicleinfrastructure systems (CVIS) safety-related services and optimizes them in three aspects. It puts forward a selfadaptive back-off algorithm. This algorithm considers retransmission times and network busy degree to choose a suitable contention window. A mathematical analysis model is developed to verify its performance improvement. Finally, different scenario models of Vehicle ad hoc network (VANET) are simulated through the network simulation tool and the influences of different access modes on Quality of Service (QoS) are investigated. The simulation results have verified the improvement of the proposed algorithm is obvious and RTS/CTS access mode can sacrifice slight delay for great improvement of packet lost rate when there are large amount of vehicle nodes.
2018, 27(4): 704-717.
doi: 10.1049/cje.2018.05.008
摘要：
Network function virtualization (NFV) and Service function chaining (SFC) can fulfill the traditional network functions by simply running special softwares on general-purpose computer servers and switches. This not only provides significantly more agility and flexibility in network service deployment, but can also greatly reduce the capital and operating cost of networks. In this paper, a comprehensive survey on the motivations and state of the art efforts towards implementing the NFV and SFC is provided. In particular, the paper first presents the main concepts of these new emerging technologies; then discusses in details various stages of SFC, including the description, composition, placement and scheduling of service chains. Afterwards, existing approaches to SFC are reviewed according to their application environments, parameters used, and solution strategies. Finally, the paper points out a number of future research directions.
Network function virtualization (NFV) and Service function chaining (SFC) can fulfill the traditional network functions by simply running special softwares on general-purpose computer servers and switches. This not only provides significantly more agility and flexibility in network service deployment, but can also greatly reduce the capital and operating cost of networks. In this paper, a comprehensive survey on the motivations and state of the art efforts towards implementing the NFV and SFC is provided. In particular, the paper first presents the main concepts of these new emerging technologies; then discusses in details various stages of SFC, including the description, composition, placement and scheduling of service chains. Afterwards, existing approaches to SFC are reviewed according to their application environments, parameters used, and solution strategies. Finally, the paper points out a number of future research directions.
2017, 26(2): 377-384.
doi: 10.1049/cje.2017.01.013
摘要：
In the application of Wireless sensor networks (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality estimation mechanism is proposed, which is based on Support vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive signal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link quality is divided into five levels according to Packet reception rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial respectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reasonable. Compared with the recent published link quality estimation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.
In the application of Wireless sensor networks (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality estimation mechanism is proposed, which is based on Support vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive signal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link quality is divided into five levels according to Packet reception rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial respectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reasonable. Compared with the recent published link quality estimation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.
2019, 28(1): 120-126.
doi: 10.1049/cje.2018.11.004
摘要：
The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNNLSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of document. We used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional information. Experimental results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.
The major challenge that text sentiment classification modeling faces is how to capture the intrinsic semantic, emotional dependence information and the key part of the emotional expression of text. To solve this problem, we proposed a Coordinated CNNLSTM-Attention(CCLA) model. We learned the vector representations of sentence with CCLA unit. Semantic and emotional information of sentences and their relations are adaptively encoded to vector representations of document. We used softmax regression classifier to identify the sentiment tendencies in the text. Compared with other methods, the CCLA model can well capture the local and long distance semantic and emotional information. Experimental results demonstrated the effectiveness of CCLA model. It shows superior performances over several state-of-the-art baseline methods.
2016, 25(4): 601-607.
doi: 10.1049/cje.2016.07.002
摘要：
The sentiment classification of Chinese Microblog is a meaningful topic. Many studies has been done based on the methods of rule and word-bag, and to understand the structure information of a sentence will be the next target. We proposed a sentiment classification method based on Recurrent neural network (RNN). We adopted the technology of distributed word representation to construct a vector for each word in a sentence; then train sentence vectors with fixed dimension for different length sentences with RNN, so that the sentence vectors contain both word semantic features and word sequence features; at last use softmax regression classifier in the output layer to predict each sentence's sentiment orientation. Experiment results revealed that our method can understand the structure information of negative sentence and double negative sentence and achieve better accuracy. The way of calculating sentence vector can help to learn the deep structure of sentence and will be valuable for different research area.
The sentiment classification of Chinese Microblog is a meaningful topic. Many studies has been done based on the methods of rule and word-bag, and to understand the structure information of a sentence will be the next target. We proposed a sentiment classification method based on Recurrent neural network (RNN). We adopted the technology of distributed word representation to construct a vector for each word in a sentence; then train sentence vectors with fixed dimension for different length sentences with RNN, so that the sentence vectors contain both word semantic features and word sequence features; at last use softmax regression classifier in the output layer to predict each sentence's sentiment orientation. Experiment results revealed that our method can understand the structure information of negative sentence and double negative sentence and achieve better accuracy. The way of calculating sentence vector can help to learn the deep structure of sentence and will be valuable for different research area.
2017, 26(5): 1079-1085.
doi: 10.1049/cje.2017.07.018
摘要：
In the user selection phrase of the conventional Multiple-input-multiple-output (MIMO) scheduling schemes, the frequent user exchange deteriorates the Quality of user experience (QoE) of the bursty data service. And the channel vector orthogonalization computation results in a high time cost. To address these problems, we propose an inertial scheduling policy to reduce the number of noneffective user exchange, and substitute self-organization policy for channel vector orthogonalization computation to reduce computational complexity. The relationship between the scheduling effectiveness and the inertia of objective function is observed in the simulation. The simulation results show that the inertial scheduling policy effectively reduce the number of potential noneffective scheduling which is inversely proportional to the Mean opinion score (MOS) that quantifies the QoE. Our proposed scheduling scheme provides significant improvement in QoE performance in the simulation. Although the proposed scheduling scheme does not consider the channel vector orthogonalization in the user selection phrase, its throughput approaches the level of the throughput-oriented scheme because of its selforganization scheduling policy.
In the user selection phrase of the conventional Multiple-input-multiple-output (MIMO) scheduling schemes, the frequent user exchange deteriorates the Quality of user experience (QoE) of the bursty data service. And the channel vector orthogonalization computation results in a high time cost. To address these problems, we propose an inertial scheduling policy to reduce the number of noneffective user exchange, and substitute self-organization policy for channel vector orthogonalization computation to reduce computational complexity. The relationship between the scheduling effectiveness and the inertia of objective function is observed in the simulation. The simulation results show that the inertial scheduling policy effectively reduce the number of potential noneffective scheduling which is inversely proportional to the Mean opinion score (MOS) that quantifies the QoE. Our proposed scheduling scheme provides significant improvement in QoE performance in the simulation. Although the proposed scheduling scheme does not consider the channel vector orthogonalization in the user selection phrase, its throughput approaches the level of the throughput-oriented scheme because of its selforganization scheduling policy.
2016, 25(2): 372-378.
doi: 10.1049/cje.2016.03.026
摘要：
Joint transmission is one of the major transmission schemes in Coordinated multipoint (CoMP) transmission/reception systems for Long term evolutionadvanced (LTE-A). Due to different distances between User equipments (UE) and Base stations (BS), signals are not able to arrive at the receiver with perfect synchronization, which implies that the reception at UE is asynchronous. This paper presents an evaluation on asynchronous UE reception in multi-cell downlink joint transmission systems using our LTE-based CoMP simulator. Then, due to asynchronous reception, we propose an improved reception strategy to mitigate the interference which compensate for Rx timing difference on Joint transmission (JT) CoMP systems. Simulation results show that the per-subband global precoding scheme widely used in the CoMP system is considerably sensitive to asynchronous reception since the performance is dominated by the subcarrier used for precoding vector calculation. It is verified that our proposed solution is able to achieve significant improvements under asynchronous reception.
Joint transmission is one of the major transmission schemes in Coordinated multipoint (CoMP) transmission/reception systems for Long term evolutionadvanced (LTE-A). Due to different distances between User equipments (UE) and Base stations (BS), signals are not able to arrive at the receiver with perfect synchronization, which implies that the reception at UE is asynchronous. This paper presents an evaluation on asynchronous UE reception in multi-cell downlink joint transmission systems using our LTE-based CoMP simulator. Then, due to asynchronous reception, we propose an improved reception strategy to mitigate the interference which compensate for Rx timing difference on Joint transmission (JT) CoMP systems. Simulation results show that the per-subband global precoding scheme widely used in the CoMP system is considerably sensitive to asynchronous reception since the performance is dominated by the subcarrier used for precoding vector calculation. It is verified that our proposed solution is able to achieve significant improvements under asynchronous reception.
2009, 18(1): 13-19.
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2014, 23(4): 678-681.
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2019, 28(6): 1092-1098.
doi: 10.1049/cje.2019.07.012
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2012, 21(2): 254-259.
Abstract:
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Abstract:
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doi: 10.1049/cje.2019.09.001
Abstract:
