Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) ...Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.展开更多
Cellular-based Machine-Type Communication (MTC) will become more and more important in the near future for the advantage of the long-distance wireless communication.However,a large number of MTC applications introduce...Cellular-based Machine-Type Communication (MTC) will become more and more important in the near future for the advantage of the long-distance wireless communication.However,a large number of MTC applications introduce heavy load to cellular network.MTC traffic scheduling schemes are proposed to avoid congestion in this paper.Our approaches are based on the delay-tolerance of MTC traffic.Some MTC traffic is postponed until the network load becomes light.Moreover,our scheme efficiently utilizes the bandwidth resources reserved for handover in traditional cellular network.Simulation results show that the utility usage of radio resources is improved and the congestion probability is reduced.展开更多
Mission critical Machine-type Communication(mcMTC),also referred to as Ultra-reliable Low Latency Communication(URLLC),has become a research hotspot.It is primarily characterized by communication that provides ultra-h...Mission critical Machine-type Communication(mcMTC),also referred to as Ultra-reliable Low Latency Communication(URLLC),has become a research hotspot.It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices.While the reduction in physical(PHY)layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability,the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers.The mcMTC has a significant technical impact on the design of all layers of the communication protocol stack.In this paper,an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission system.To achieve this aim,we analyzed and compared the channel coding performance of convolutional codes(CCs),low-density parity-check(LDPC)codes,and polar codes in wireless network on the condition of short data packet transmission.The Viterbi decoding algorithm(VA),logarithmic belief propagation(Log-BP)algorithm,and cyclic redundancy check(CRC)successive cancellation list(SCL)(CRC-SCL)decoding algorithm were adopted to CC,LDPC codes,and polar codes,respectively.Consequently,a new PHY layer for mcMTC has been proposed.The reliability of the proposed approach has been validated by simulation in terms of Bit error rate(BER)and packet error rate(PER)vs.signal-to-noise ratio(SNR).The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER=10−5 or even better with the implementation of polar codes.The results also show that the general-purpose wireless networks are prominent inproviding short packet mcMTC with the modification needed.展开更多
Sparsity-based joint active user detection and channel estimation(JADCE)algorithms are crucial in grant-free massive machine-type communication(mMTC)systems.The conventional compressed sensing algorithms are tailored ...Sparsity-based joint active user detection and channel estimation(JADCE)algorithms are crucial in grant-free massive machine-type communication(mMTC)systems.The conventional compressed sensing algorithms are tailored for noncoherent communication systems,where the correlation between any two measurements is as minimal as possible.However,existing sparsity-based JADCE approaches may not achieve optimal performance in strongly coherent systems,especially with a small number of pilot subcarriers.To tackle this challenge,we formulate JADCE as a joint sparse signal recovery problem,leveraging the block-type row-sparse structure of millimeter-wave(mmWave)channels in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMOOFDM)systems.Then,we propose an efficient difference-of-convex function algorithm(DCA)based JADCE algorithm with multiple measurement vector(MMV)frameworks,promoting the row-sparsity of the channel matrix.To mitigate the computational complexity further,we introduce a fast DCA-based JADCE algorithm via a proximal operator,which allows a low-complexity alternating direction multiplier method(ADMM)to resolve the optimization problem directly.Finally,simulation results demonstrate that the two proposed difference-of-convex(DC)algorithms achieve effective active user detection and accurate channel estimation compared with state-of-the-art compressed sensing based JADCE techniques.展开更多
The sporadic communication character of massive machine-type communication systems provides natural advantages to utilize the principle of compressive sensing(CS).However,due to the high computational complexity of CS...The sporadic communication character of massive machine-type communication systems provides natural advantages to utilize the principle of compressive sensing(CS).However,due to the high computational complexity of CS algorithms,CS-based contention-free access schemes have limited scalability and high computational complexity for massive access with user-specific pilots.To address these problems,in this paper,we propose a new contention-based scheme for CSbased massive access,which can support the sporadic access of massive devices(more than one million devices)with limited resources.Furthermore,an advanced receiver algorithm is designed to solve the optimal solutions for the proposed scheme,which utilizes various prior information to enhance the performance.In specific,the joint sparsity between the channel and data is used to improve the accuracy of pilot detection,and the information of modulation and cyclic redundancy check is exploited for channel correction to improve the performance of data recovery.The simulation results show that the proposed scheme can achieve improved active user detection performance and data recovery accuracy than existing methods.展开更多
Massive machine-type communication(m MTC)is a typical application scenario of the fifth generation(5G)mobile communications.To keep the m MTC reliable and minimize the energy consumption of the m MTC devices,this pape...Massive machine-type communication(m MTC)is a typical application scenario of the fifth generation(5G)mobile communications.To keep the m MTC reliable and minimize the energy consumption of the m MTC devices,this paper proposes an enhanced power choice barring(EPCB)scheme based on the distributed layered grant-free non-orthogonal multiple access(NOMA)framework,where the cell is divided into different layers according to a predetermined power levels.The proposed EPCB scheme not only combines the grant-free strategy with the sleep mode to reduce the energy consumption,but also designs a power level choosing strategy to increase the access success probability.Simulation results show that when compared with existing schemes,the proposed EPCB scheme has better performance in the aspects of the access success probability and energy efficiency.展开更多
As the Internet of Things(IoT)advances,machine-type devices are densely deployed and massive networks such as ultra-dense networks(UDNs)are formed.Various devices attend to the network to transmit data using machine-t...As the Internet of Things(IoT)advances,machine-type devices are densely deployed and massive networks such as ultra-dense networks(UDNs)are formed.Various devices attend to the network to transmit data using machine-type communication(MTC),whereby numerous,various are generated.MTC devices generally have resource constraints and use wireless communication.In this kind of network,data aggregation is a key function to provide transmission efficiency.It can reduce the number of transmitted data in the network,and this leads to energy saving and reducing transmission delays.In order to effectively operate data aggregation in UDNs,it is important to select an aggregation point well.The total number of transmitted data may vary,depending on the aggregation point to which the data are delivered.Therefore,in this paper,we propose a novel data aggregation scheme to select the appropriate aggregation point and describe the data transmission method applying the proposed aggregation scheme.In addition,we evaluate the proposed scheme with extensive computer simulations.Better performances in the proposed scheme are achieved compared to the conventional approach.展开更多
Machine-type communication (MTC) devices provide a broad range of data collection especially on the massive data generated environments such as urban, industrials and event-enabled areas. In dense deployments, the dat...Machine-type communication (MTC) devices provide a broad range of data collection especially on the massive data generated environments such as urban, industrials and event-enabled areas. In dense deployments, the data collected at the closest locations between the MTC devices are spatially correlated. In this paper, we propose a k-means grouping technique to combine all MTC devices based on spatially correlated. The MTC devices collect the data on the event-based area and then transmit to the centralized aggregator for processing and computing. With the limitation of computational resources at the centralized aggregator, some grouped MTC devices data offloaded to the nearby base station collocated with the mobile edge-computing server. As a sensing capability adopted on MTC devices, we use a power exponential function model to compute a correlation coefficient existing between the MTC devices. Based on this framework, we compare the energy consumption when all data processed locally at centralized aggregator or offloaded at mobile edge computing server with optimal solution obtained by the brute force method. Then, the simulation results revealed that the proposed k-means grouping technique reduce the energy consumption at centralized aggregator while satisfying the required completion time.展开更多
Unsourced random access(URA)is a new perspective of massive access which aims at supporting numerous machine-type users.With the appearance of carrier frequency offset(CFO),joint activity detection and channel estimat...Unsourced random access(URA)is a new perspective of massive access which aims at supporting numerous machine-type users.With the appearance of carrier frequency offset(CFO),joint activity detection and channel estimation,which is vital for multiple-input and multiple-output URA,is a challenging task.To handle the phase corruption of channel measurements under CFO,a novel compressed sensing algorithm is proposed,leveraging the parametric bilinear generalized approximate message passing framework with a Markov chain support model that captures the block sparsity structure of the considered angular domain channel.An uncoupled transmission scheme is proposed to reduce system complexity,where slot-emitted messages are reorganized relying on clustering unique user channels.Simulation results reveal that the proposed transmission design for URA under CFO outperforms other potential methods.展开更多
Massive machine-type communications(mMTC)is envisioned to be one of the pivotal scenarios in the fifth-generation(5G)wireless communication,where the explosively emerging Internet-of-Things(IoT)applications have trigg...Massive machine-type communications(mMTC)is envisioned to be one of the pivotal scenarios in the fifth-generation(5G)wireless communication,where the explosively emerging Internet-of-Things(IoT)applications have triggered the demand for services with low-latency and high-reliability.To this end,grant-free random access paradigm has been proposed as a promising enabler in simplifying the connection procedure and significantly reducing access latency.In this paper,we propose to leverage the burgeoning reconfigurable intelligent surface(RIS)for grant-free massive access working at millimeter-wave(mmWave)frequency to further boost access reliability.By attaching independently controllable phase shifts,reconfiguring,and refracting the propagation of incident electromagnetic waves,the deployed RISs could provide additional diversity gain and enhance the access channel conditions.On this basis,to address the challenging active device detection(ADD)and channel estimation(CE)problem,we develop a joint-ADDCE(JADDCE)method by resorting to the existing approximate message passing(AMP)algorithm with expectation maximization(EM)to extract the structured common sparsity in traffic behaviors and cascaded channel matrices.Finally,simulations are carried out to demonstrate the superiority of our proposed scheme.展开更多
基金the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia(Grant No.GRANT5,208).
文摘Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.
基金supported by the National Science Foundation(60972047,60972048,60832001)National S&T Major Project(2011ZX03005-003-03,2008ZX03005-001,2010ZX03005-003)+4 种基金National Science Fund for Distinguished Young Scholars(60725105)National Basic Research Program of China(No.2009CB320404)Program for Changjiang Scholars and Innovative Research Team in University(IRT0852)the 111 Project(B08038)State Key Laboratory Foundation(ISN090305,ISN1002005)
文摘Cellular-based Machine-Type Communication (MTC) will become more and more important in the near future for the advantage of the long-distance wireless communication.However,a large number of MTC applications introduce heavy load to cellular network.MTC traffic scheduling schemes are proposed to avoid congestion in this paper.Our approaches are based on the delay-tolerance of MTC traffic.Some MTC traffic is postponed until the network load becomes light.Moreover,our scheme efficiently utilizes the bandwidth resources reserved for handover in traditional cellular network.Simulation results show that the utility usage of radio resources is improved and the congestion probability is reduced.
文摘Mission critical Machine-type Communication(mcMTC),also referred to as Ultra-reliable Low Latency Communication(URLLC),has become a research hotspot.It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices.While the reduction in physical(PHY)layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability,the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers.The mcMTC has a significant technical impact on the design of all layers of the communication protocol stack.In this paper,an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission system.To achieve this aim,we analyzed and compared the channel coding performance of convolutional codes(CCs),low-density parity-check(LDPC)codes,and polar codes in wireless network on the condition of short data packet transmission.The Viterbi decoding algorithm(VA),logarithmic belief propagation(Log-BP)algorithm,and cyclic redundancy check(CRC)successive cancellation list(SCL)(CRC-SCL)decoding algorithm were adopted to CC,LDPC codes,and polar codes,respectively.Consequently,a new PHY layer for mcMTC has been proposed.The reliability of the proposed approach has been validated by simulation in terms of Bit error rate(BER)and packet error rate(PER)vs.signal-to-noise ratio(SNR).The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER=10−5 or even better with the implementation of polar codes.The results also show that the general-purpose wireless networks are prominent inproviding short packet mcMTC with the modification needed.
基金supported by the Guangdong Basic and Applied Basic Research Foundation,China(No.2022A1515140074)and the Natural Science Foundation of Liaoning Province,China(No.2023-MS-108)。
文摘Sparsity-based joint active user detection and channel estimation(JADCE)algorithms are crucial in grant-free massive machine-type communication(mMTC)systems.The conventional compressed sensing algorithms are tailored for noncoherent communication systems,where the correlation between any two measurements is as minimal as possible.However,existing sparsity-based JADCE approaches may not achieve optimal performance in strongly coherent systems,especially with a small number of pilot subcarriers.To tackle this challenge,we formulate JADCE as a joint sparse signal recovery problem,leveraging the block-type row-sparse structure of millimeter-wave(mmWave)channels in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMOOFDM)systems.Then,we propose an efficient difference-of-convex function algorithm(DCA)based JADCE algorithm with multiple measurement vector(MMV)frameworks,promoting the row-sparsity of the channel matrix.To mitigate the computational complexity further,we introduce a fast DCA-based JADCE algorithm via a proximal operator,which allows a low-complexity alternating direction multiplier method(ADMM)to resolve the optimization problem directly.Finally,simulation results demonstrate that the two proposed difference-of-convex(DC)algorithms achieve effective active user detection and accurate channel estimation compared with state-of-the-art compressed sensing based JADCE techniques.
基金supported by the Key-Area Research and Development Program of Guangdong Province under Grant 2019B010157002the Natural Science Foundation of China(61671046,61911530216,61725101,6196113039,U1834210)+4 种基金the Beijing Natural Science Foundation(4182050)the State Key Laboratory of Rail Traffic Control and Safety(RCS2020ZT010)of Beijing Jiaotong Universitythe Fundamental Research Funds for the Central Universities 2020JBM090the Royal Society Newton Advanced Fellowship under Grant NA191006NSFC Outstanding Youth Foundation under Grant 61725101。
文摘The sporadic communication character of massive machine-type communication systems provides natural advantages to utilize the principle of compressive sensing(CS).However,due to the high computational complexity of CS algorithms,CS-based contention-free access schemes have limited scalability and high computational complexity for massive access with user-specific pilots.To address these problems,in this paper,we propose a new contention-based scheme for CSbased massive access,which can support the sporadic access of massive devices(more than one million devices)with limited resources.Furthermore,an advanced receiver algorithm is designed to solve the optimal solutions for the proposed scheme,which utilizes various prior information to enhance the performance.In specific,the joint sparsity between the channel and data is used to improve the accuracy of pilot detection,and the information of modulation and cyclic redundancy check is exploited for channel correction to improve the performance of data recovery.The simulation results show that the proposed scheme can achieve improved active user detection performance and data recovery accuracy than existing methods.
基金supported by the NSFC projects(6217011870,and 61971136)Zhishan Youth Scholar Program of SEU,the Fundamental Research Funds for the Central UniversitiesYoung Elite Scientist Sponsorship Program by CAST(YESS20160042)。
文摘Massive machine-type communication(m MTC)is a typical application scenario of the fifth generation(5G)mobile communications.To keep the m MTC reliable and minimize the energy consumption of the m MTC devices,this paper proposes an enhanced power choice barring(EPCB)scheme based on the distributed layered grant-free non-orthogonal multiple access(NOMA)framework,where the cell is divided into different layers according to a predetermined power levels.The proposed EPCB scheme not only combines the grant-free strategy with the sleep mode to reduce the energy consumption,but also designs a power level choosing strategy to increase the access success probability.Simulation results show that when compared with existing schemes,the proposed EPCB scheme has better performance in the aspects of the access success probability and energy efficiency.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea Government(MSIT)(No.2021R1C1C1013133)this work was supported by the Soonchunhyang University Research Fund(No.20210442).
文摘As the Internet of Things(IoT)advances,machine-type devices are densely deployed and massive networks such as ultra-dense networks(UDNs)are formed.Various devices attend to the network to transmit data using machine-type communication(MTC),whereby numerous,various are generated.MTC devices generally have resource constraints and use wireless communication.In this kind of network,data aggregation is a key function to provide transmission efficiency.It can reduce the number of transmitted data in the network,and this leads to energy saving and reducing transmission delays.In order to effectively operate data aggregation in UDNs,it is important to select an aggregation point well.The total number of transmitted data may vary,depending on the aggregation point to which the data are delivered.Therefore,in this paper,we propose a novel data aggregation scheme to select the appropriate aggregation point and describe the data transmission method applying the proposed aggregation scheme.In addition,we evaluate the proposed scheme with extensive computer simulations.Better performances in the proposed scheme are achieved compared to the conventional approach.
文摘Machine-type communication (MTC) devices provide a broad range of data collection especially on the massive data generated environments such as urban, industrials and event-enabled areas. In dense deployments, the data collected at the closest locations between the MTC devices are spatially correlated. In this paper, we propose a k-means grouping technique to combine all MTC devices based on spatially correlated. The MTC devices collect the data on the event-based area and then transmit to the centralized aggregator for processing and computing. With the limitation of computational resources at the centralized aggregator, some grouped MTC devices data offloaded to the nearby base station collocated with the mobile edge-computing server. As a sensing capability adopted on MTC devices, we use a power exponential function model to compute a correlation coefficient existing between the MTC devices. Based on this framework, we compare the energy consumption when all data processed locally at centralized aggregator or offloaded at mobile edge computing server with optimal solution obtained by the brute force method. Then, the simulation results revealed that the proposed k-means grouping technique reduce the energy consumption at centralized aggregator while satisfying the required completion time.
基金supported by the ZTE Industry⁃University⁃Institute Cooperation Funds under Grant No.HC⁃CN⁃20201116001.
文摘Unsourced random access(URA)is a new perspective of massive access which aims at supporting numerous machine-type users.With the appearance of carrier frequency offset(CFO),joint activity detection and channel estimation,which is vital for multiple-input and multiple-output URA,is a challenging task.To handle the phase corruption of channel measurements under CFO,a novel compressed sensing algorithm is proposed,leveraging the parametric bilinear generalized approximate message passing framework with a Markov chain support model that captures the block sparsity structure of the considered angular domain channel.An uncoupled transmission scheme is proposed to reduce system complexity,where slot-emitted messages are reorganized relying on clustering unique user channels.Simulation results reveal that the proposed transmission design for URA under CFO outperforms other potential methods.
基金supported by the National Natural Science Foundation of China(NSFC)(No.62071044)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2022D09)+1 种基金Beijing Institute of Technology Research Fund Program for Young Scholars(No.XSQD-202121009)Ensan Foundation(No.2022006).
文摘Massive machine-type communications(mMTC)is envisioned to be one of the pivotal scenarios in the fifth-generation(5G)wireless communication,where the explosively emerging Internet-of-Things(IoT)applications have triggered the demand for services with low-latency and high-reliability.To this end,grant-free random access paradigm has been proposed as a promising enabler in simplifying the connection procedure and significantly reducing access latency.In this paper,we propose to leverage the burgeoning reconfigurable intelligent surface(RIS)for grant-free massive access working at millimeter-wave(mmWave)frequency to further boost access reliability.By attaching independently controllable phase shifts,reconfiguring,and refracting the propagation of incident electromagnetic waves,the deployed RISs could provide additional diversity gain and enhance the access channel conditions.On this basis,to address the challenging active device detection(ADD)and channel estimation(CE)problem,we develop a joint-ADDCE(JADDCE)method by resorting to the existing approximate message passing(AMP)algorithm with expectation maximization(EM)to extract the structured common sparsity in traffic behaviors and cascaded channel matrices.Finally,simulations are carried out to demonstrate the superiority of our proposed scheme.
