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Publications (10 of 201) Show all publications
Yue, J. & Xiao, M. (2020). Coded Decentralized Learning With Gradient Descent for Big Data Analytics. IEEE Communications Letters, 24(2), 362-366
Open this publication in new window or tab >>Coded Decentralized Learning With Gradient Descent for Big Data Analytics
2020 (English)In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 24, no 2, p. 362-366Article in journal (Refereed) Published
Abstract [en]

Machine learning is an effective technique for big data analytics. We focus on the study of big data analytics with decentralized learning in large-scale networks. Fountain codes are applied to the decentralized learning process to reduce communication load for exchanging intermediate learning parameters among fog nodes. Two scenarios, i.e., disjoint datasets and overlapping datasets, are analyzed. Comparison results show that communication load can be reduced significantly by the Fountain-based scheme for large-scale networks, especially when the quality of communication links is relatively bad and/or the number of fog nodes is large.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020
Keywords
Big Data, Encoding, Decoding, 1, f noise, Task analysis, Generators, Machine learning, decentralized learning, gradient descent, Fountain codes, communication load
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-271740 (URN)10.1109/LCOMM.2019.2930513 (DOI)000519909600028 ()2-s2.0-85079817129 (Scopus ID)
Note

QC 20200408

Available from: 2020-04-08 Created: 2020-04-08 Last updated: 2020-04-08Bibliographically approved
Dai, B., Ma, Z., Luo, Y., Liu, X., Zhuang, Z. & Xiao, M. (2020). Enhancing Physical Layer Security in Internet of Things via Feedback: A General Framework. IEEE Internet of Things Journal, 7(1), 99-115, Article ID 8856252.
Open this publication in new window or tab >>Enhancing Physical Layer Security in Internet of Things via Feedback: A General Framework
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2020 (English)In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 7, no 1, p. 99-115, article id 8856252Article in journal (Refereed) Published
Abstract [en]

In this article, a general framework for enhancing the physical layer security (PLS) in the Internet of Things (IoT) systems via channel feedback is established. To be specific, first, we study the compound wiretap channel (WTC) with feedback, which can be viewed as an ideal model for enhancing the PLS in the downlink transmission of IoT systems via feedback. A novel feedback strategy is proposed and a corresponding lower bound on the secrecy capacity is constructed for this ideal model. Next, we generalize the ideal model (i.e., the compound WTC with feedback) by considering channel states and feedback delay, and this generalized model is called the finite state compound WTC with delayed feedback. The lower bounds on the secrecy capacities of this generalized model with or without delayed channel output feedback are provided, and they are constructed according to variations of the previously proposed feedback scheme for the ideal model. Finally, from a Gaussian fading example, we show that the delayed channel output feedback enhances the achievable secrecy rate of the finite state compound WTC with only delayed state feedback, which implies that feedback helps to enhance the PLS in the downlink transmission of the IoT systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2020
Keywords
Compound channel, feedback, secrecy capacity, wiretap channel (WTC)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-267861 (URN)10.1109/JIOT.2019.2945503 (DOI)000508181000007 ()2-s2.0-85075688452 (Scopus ID)
Note

QC 20200220

Available from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-20Bibliographically approved
Ye, Y., Xiao, M. & Skoglund, M. (2020). Mobility-Aware Content Preference Learning in Decentralized Caching Networks. IEEE Transactions on Cognitive Communications and Networking, 6(1), 62-73
Open this publication in new window or tab >>Mobility-Aware Content Preference Learning in Decentralized Caching Networks
2020 (English)In: IEEE Transactions on Cognitive Communications and Networking, ISSN 2332-7731, Vol. 6, no 1, p. 62-73Article in journal (Refereed) Published
Abstract [en]

Due to the drastic increase of mobile traffic, wireless caching is proposed to serve repeated requests for content download. To determine the caching scheme for decentralized caching networks, the content preference learning problem based on mobility prediction is studied. We first formulate preference prediction as a decentralized regularized multi-task learning (DRMTL) problem without considering the mobility of mobile terminals (MTs). The problem is solved by a hybrid Jacobian and Gauss-Seidel proximal multi-block alternating direction method (ADMM) based algorithm, which is proven to conditionally converge to the optimal solution with a rate ${O}$ (1/ ${k}$ ). Then we use the tool of Markov renewal process to predict the moving path and sojourn time for MTs, and integrate the mobility pattern with the DRMTL model by reweighting the training samples and introducing a transfer penalty in the objective. We solve the problem and prove that the developed algorithm has the same convergence property but with different conditions. Through simulation we show the convergence analysis on proposed algorithms. Our real trace driven experiments illustrate that the mobility-aware DRMTL model can provide a more accurate prediction on geography preference than DRMTL model. Besides, the hit ratio achieved by most popular proactive caching (MPC) policy with preference predicted by mobility-aware DRMTL outperforms the MPC with preference from DRMTL and random caching (RC) schemes.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2020
Keywords
Proactive caching, distributed machine learning, multi-task learning
National Category
Computer Systems
Identifiers
urn:nbn:se:kth:diva-271719 (URN)10.1109/TCCN.2019.2937519 (DOI)000519951500006 ()2-s2.0-85071667216 (Scopus ID)
Note

QC 20200416

Available from: 2020-04-16 Created: 2020-04-16 Last updated: 2020-04-16Bibliographically approved
Zhang, Z., Xiao, Y., Ma, Z., Xiao, M., Ding, Z., Lei, X., . . . Fan, P. (2019). 6G WIRELESS NETWORKS Vision, Requirements, Architecture, and Key Technologies. IEEE Vehicular Technology Magazine, 14(3), 28-41
Open this publication in new window or tab >>6G WIRELESS NETWORKS Vision, Requirements, Architecture, and Key Technologies
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2019 (English)In: IEEE Vehicular Technology Magazine, ISSN 1556-6072, E-ISSN 1556-6080, Vol. 14, no 3, p. 28-41Article in journal (Refereed) Published
Abstract [en]

A key enabler for the intelligent information society of 2030, 6G networks are expected to provide performance superior to 5G and satisfy emerging services and applications. In this article, we present our vision of what 6G will be and describe usage scenarios and requirements for multi-terabyte per second (Tb/s) and intelligent 6G networks. We present a large-dimensional and autonomous network architecture that integrates space, air, ground, and underwater networks to provide ubiquitous and unlimited wireless connectivity. We also discuss artificial intelligence (AI) and machine learning [1], [2] for autonomous networks and innovative air-interface design. Finally, we identify several promising technologies for the 6G ecosystem, including terahertz (THz) communications, very-large-scale antenna arrays [i.e., supermassive (SM) multiple-input, multiple-output (MIMO)], large intelligent surfaces (LISs) and holographic beamforming (HBF), orbital angular momentum (OAM) multiplexing, laser and visible-light communications (VLC), blockchain-based spectrum sharing, quantum communications and computing, molecular communications, and the Internet of Nano-Things.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-257800 (URN)10.1109/MVT.2019.2921208 (DOI)000481980100006 ()2-s2.0-85069918860 (Scopus ID)
Note

QC 20190912

Available from: 2019-09-12 Created: 2019-09-12 Last updated: 2019-09-12Bibliographically approved
Huang, S. & Xiao, M. (2019). Achievable Rate Analysis of Millimeter Wave Channels with Random Coding Error Exponent. In: IEEE International Conference on Communications: . Paper presented at 2019 IEEE International Conference on Communications, ICC 2019; Shanghai International Convention Center, Shanghai; China; 20-24 May 2019. Institute of Electrical and Electronics Engineers (IEEE), 2019, Article ID 8761470.
Open this publication in new window or tab >>Achievable Rate Analysis of Millimeter Wave Channels with Random Coding Error Exponent
2019 (English)In: IEEE International Conference on Communications, Institute of Electrical and Electronics Engineers (IEEE), 2019, Vol. 2019, article id 8761470Conference paper, Published paper (Refereed)
Abstract [en]

Millimeter Wave (mmWave) communication has attracted massive attentions, since the abundant available bandwidth can potentially provide reliable communication with orders of magnitude capacity improvements relative to microwave. However, the achievable rate of mmWave channels under latency and reliability constraints is still not quite clear. We investigate the achievable rates of mmWave channels by random coding error exponent (RCEE) with finite blocklength. With imperfect channel state information at the receiver, the exact and approximate analytical expressions of the training based maximum achievable rate are derived to capture the relationship among rate-latency-reliability. Additionally, the relationship between the training based maximum achievable rate and bandwidth is investigated. We show that there exists critical bandwidth to maximize the training based maximum achievable rate for the non-line-of-sight (NLoS) propagation. Numerical results show that the approximate expression of the training based maximum achievable rate are tight and can capture the tendency at low SNRs. In addition, results show that for a given rate, one can reduce both packet duration and decoding error probability by increasing bandwidth. Results also suggest that in some mmWave bands, e.g. 57-64 GHz band, the performance, i.e., Gallager function, is significantly affected by frequency selective power absorption.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2019
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-257932 (URN)10.1109/ICC.2019.8761470 (DOI)000492038802108 ()2-s2.0-85070225516 (Scopus ID)9781538680889 (ISBN)
Conference
2019 IEEE International Conference on Communications, ICC 2019; Shanghai International Convention Center, Shanghai; China; 20-24 May 2019
Note

QC 20190909

Available from: 2019-09-09 Created: 2019-09-09 Last updated: 2019-12-09Bibliographically approved
Yang, P., Xiao, Y., Xiao, M., Guan, Y. L., Li, S. & Xiang, W. (2019). Adaptive Spatial Modulation MIMO Based on Machine Learning. IEEE Journal on Selected Areas in Communications, 37(9), 2117-2131
Open this publication in new window or tab >>Adaptive Spatial Modulation MIMO Based on Machine Learning
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2019 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 37, no 9, p. 2117-2131Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a novel framework of low-cost link adaptation for spatial modulation multiple-input multiple-output (SM-MIMO) systems-based upon the machine learning paradigm. Specifically, we first convert the problems of transmit antenna selection (TAS) and power allocation (PA) in SM-MIMO to ones-based upon data-driven prediction rather than conventional optimization-driven decisions. Then, supervised-learning classifiers (SLC), such as the K-nearest neighbors (KNN) and support vector machine (SVM) algorithms, are developed to obtain their statistically-consistent solutions. Moreover, for further comparison we integrate deep neural networks (DNN) with these adaptive SM-MIMO schemes, and propose a novel DNN-based multi-label classifier for TAS and PA parameter evaluation. Furthermore, we investigate the design of feature vectors for the SLC and DNN approaches and propose a novel feature vector generator to match the specific transmission mode of SM. As a further advance, our proposed approaches are extended to other adaptive index modulation (IM) schemes, e.g., adaptive modulation (AM) aided orthogonal frequency division multiplexing with IM (OFDM-IM). Our simulation results show that the SLC and DNN-based adaptive SM-MIMO systems outperform many conventional optimization-driven designs and are capable of achieving a near-optimal performance with a significantly lower complexity.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Index modulation, SM-MIMO, machine learning, neural network, link adaptation
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-257802 (URN)10.1109/JSAC.2019.2929404 (DOI)000481983100013 ()2-s2.0-85071016115 (Scopus ID)
Note

QC 20190912

Available from: 2019-09-12 Created: 2019-09-12 Last updated: 2019-09-12Bibliographically approved
Yu, H., Fei, Z., Cao, C., Xiao, M., Jia, D. & Ye, N. (2019). Analysis of irregular repetition spatially-coupled slotted ALOHA. Science China Information Sciences, 62(8), Article ID 080302.
Open this publication in new window or tab >>Analysis of irregular repetition spatially-coupled slotted ALOHA
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2019 (English)In: Science China Information Sciences, ISSN 1674-733X, E-ISSN 1869-1919, Vol. 62, no 8, article id 080302Article in journal (Refereed) Published
Abstract [en]

Contention-based access is a promising technology for massive and sporadic transmissions. In this paper, we propose a novel contention-based multiple access scheme, named irregular repetition spatiallycoupled slotted ALOHA (IRSC-SA), motivated by the spatial coupling and irregular repetition techniques. There are different classes of users and slots in IRSC-SA, which result in unequal protection for different users. Considering that, we derive a novel density evolution (DE) method, which deals with unequal packet protection and introduces Bayesian reasoning to analyze the throughput threshold of the proposed IRSC-SA. Theoretical analysis and simulation results show that the proposed scheme achieves better asymptotic threshold and system packet throughput performance than the conventional spatially-coupled slotted ALOHA.

Place, publisher, year, edition, pages
SCIENCE PRESS, 2019
Keywords
spatial coupling, coded slotted ALOHA, contention-based access, density evolution, irregular repetition
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-257820 (URN)10.1007/s11432-018-9837-9 (DOI)000482203000002 ()2-s2.0-85068870924 (Scopus ID)
Note

QC 20190906

Available from: 2019-09-06 Created: 2019-09-06 Last updated: 2019-09-06Bibliographically approved
Xue, Q., Fang, X., Xiao, M., Mumtaz, S. & Rodriguez, J. (2019). Beam Management for Millimeter-Wave Beamspace MU-MIMO Systems. IEEE Transactions on Communications, 67(1), 205-217
Open this publication in new window or tab >>Beam Management for Millimeter-Wave Beamspace MU-MIMO Systems
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2019 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 1, p. 205-217Article in journal (Refereed) Published
Abstract [en]

Millimeter-wave (mm-wave) communication has attracted increasing attention as a promising technology for 5G networks. One of the key architectural features of mm-wave is the possibility of using large antenna arrays at both the transmitter and receiver sides. Therefore, by employing directional beamforming, both mm-wave base stations (MBSs) and mm-wave user equipments (MUEs) are capable of supporting multi-beam simultaneous transmissions. However, most of the existing research results have only considered a single beam. Thus, the potentials of mm-wave have not been fully exploited yet. In this context, in order to improve the performance of short-range indoor mm-wave networks with multiple reflections, we investigate the challenges and potential solutions of downlink multi-user multi-beam transmission, which can be described as a beamspace multi-user multiple-input multiple-output (MU-MIMO) technique. We first exploit the characteristic of MBS/MUEs supporting multiple beams simultaneously to improve the efficiency of multi-user BF training. Then, we analyze the inter-user interference to avoid beam selection conflicts. Furthermore, we propose blockage control strategies and multi-user multi-beam power allocation solutions for the beamspace MU-MIMO. The theoretical and numerical results demonstrate that the beamspace MU-MIMO compared with single beam transmission can largely improve the rate performance and robustness of mm-wave networks.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Millimeter wave (mm-wave), beamspace MIMO, beamforming (BF) training, inter-user/beam interference, blockage, power allocation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-244129 (URN)10.1109/TCOMM.2018.2867487 (DOI)000457304400017 ()2-s2.0-85052661803 (Scopus ID)
Note

QC 20190218

Available from: 2019-02-18 Created: 2019-02-18 Last updated: 2019-02-18Bibliographically approved
Pan, F., Pang, Z., Xiao, M., Wen, H. & Liao, R.-F. (2019). Clone Detection Based on Physical Layer Reputation for Proximity Service. IEEE Access, 7, 3948-3957
Open this publication in new window or tab >>Clone Detection Based on Physical Layer Reputation for Proximity Service
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 3948-3957Article in journal (Refereed) Published
Abstract [en]

Proximity-based service (ProSe) provides direct communications among smart sensor nodes in proximity which aims at reserving resource consumption and alleviating the load in base stations, which is a promising solution for smart sensor systems that possess limited computing and energy resources. During the ProSe direct communications, most of the prior art security methods are usually provided by the ProSe function and are based on complex cryptography. However, despite the computing complexity, it is difficult for cryptographic methods to detect clone attack which is a common kind of attack in sensor systems. Clone nodes feature different physical positions but claim colliding IDs with captured nodes. Thus, clone nodes can be detected by spatial differences, in particular, by the surveillance of physical layer channel state information (CSI). However, CSI is not absolute static due to the random noise in wireless propagation environment. Accordingly, the detection accuracy varies with the stability of CSI. To address this challenge, we take the first attempt to introduce physical layer reputation and then elaborate the physical layer reputation based clone detection protocol to detect clone attack in multiple scenarios. The proposed protocol significantly improves the detection rate and false alarm rate and it is validated both by simulations and realizations.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Clone detection, proximity service, reputation based detection, smart sensor network
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-243966 (URN)10.1109/ACCESS.2018.2888693 (DOI)000456189100001 ()2-s2.0-85058903715 (Scopus ID)
Note

QC 20190301

Available from: 2019-03-01 Created: 2019-03-01 Last updated: 2019-03-01Bibliographically approved
Yue, J. & Xiao, M. (2019). Coding for Distributed Fog Computing in Internet of Mobile Things. IEEE Transactions on Mobile Computing
Open this publication in new window or tab >>Coding for Distributed Fog Computing in Internet of Mobile Things
2019 (English)In: IEEE Transactions on Mobile ComputingArticle in journal (Refereed) Published
Abstract [en]

Internet of Mobile Things (IoMTs) refers to the interconnection of mobile devices, for example, mobile phones, vehicles, robots, etc. For mobile data, strong extra processing resources are normally required due to the limited physical resources of the mobile devices in IoMTs. Due to latency or bandwidth limitations, it may be infeasible to transfer a large amounts of mobile data to remote server for processing. Thus, distributed computing is one of the potential solutions to overcome these limitations. We consider the device mobility in IoMTs. Two situations of the movement position of the mobile devices, i.e., unpredictable and predictable, are considered. In addition, three possible relative positions between the two server sets which respectively correspond to the positions of a mobile device for computation tasks offloading and for output results receiving, i.e., within the same server sets, with two different server sets and with two adjacent server sets, are studied. Coded schemes with high flexibility and low complexity are proposed based on Fountain codes to reduce the total processing time and latency of the distributed fog computing process in IoMTs for the above different situations. The latency related performance, i.e., the computation, the communication and the transmission loads, is analyzed. We also compare of the Fountain code-based and the uncoded schemes and numerical results demonstrate that shorter total processing time and lower latency can be achieved by the Fountain code-based schemes.

National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-268271 (URN)10.1109/TMC.2019.2963668 (DOI)2-s2.0-85077383243 (Scopus ID)
Note

QC 20200325

Available from: 2020-03-25 Created: 2020-03-25 Last updated: 2020-03-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-5407-0835

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