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Shokri-Ghadikolaei, HosseinORCID iD iconorcid.org/0000-0001-6737-0266
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Publications (10 of 36) Show all publications
Jiang, X., Shokri-Ghadikolaei, H., Fischione, C. & Pang, Z. (2019). A Simplified Interference Model for Outdoor Millimeter-waveNetworks. Mobile Networks and Applications, 24(3), 983-990
Open this publication in new window or tab >>A Simplified Interference Model for Outdoor Millimeter-waveNetworks
2019 (English)In: Mobile Networks and Applications, ISSN 1383-469X, Vol. 24, no 3, p. 983-990Article in journal (Refereed) Published
Abstract [en]

Industry 4.0 is the emerging trend of the industrial automation. Millimeter-wave (mmWave) communication is a prominent technology for wireless networks to support the Industry 4.0 requirements. The availability of tractable accurate interference models would greatly facilitate performance analysis and protocol development for these networks. In this paper, we investigate the accuracy of an interference model that assumes impenetrable obstacles and neglects the sidelobes. We quantify the error of such a model in terms of statistical distribution of the signal to noise plus interference ratio and of the user rate for outdoor mmWave networks under different carrier frequencies and antenna array settings. The results show that assuming impenetrable obstacle comes at almost no accuracy penalty, and the accuracy of neglecting antenna sidelobes can be guaranteed with sufficiently large number of antenna elements. The comprehensive discussions of this paper provide useful insights for the performance analysis and protocol design of outdoor mmWave networks.

Place, publisher, year, edition, pages
Springer, 2019
Keywords
Millimeter-wave networks, Interference model, Simplicity-accuracy tradeoff, Interference model accuracy index
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-223696 (URN)10.1007/s11036-018-1030-2 (DOI)000469238500022 ()2-s2.0-85041910774 (Scopus ID)
Note

QC 20180319

Available from: 2018-02-28 Created: 2018-02-28 Last updated: 2019-06-25Bibliographically approved
Xu, Y., Shokri Ghadikolaei, H. & Fischione, C. (2019). Adaptive Distributed Association in Time-Variant Millimeter Wave Networks. IEEE Transactions on Wireless Communications, 18(1), 459-472
Open this publication in new window or tab >>Adaptive Distributed Association in Time-Variant Millimeter Wave Networks
2019 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 18, no 1, p. 459-472Article in journal (Refereed) Published
Abstract [en]

The underutilized millimeter-wave (mm-wave) band is a promising candidate to enable extremely high data rate communications in future wireless networks. However, the special characteristics of the mm-wave systems such as high vulnerability to obstacles (due to high penetration loss) and to mobility (due to directional communications) demand a careful design of the association between the clients and access points (APs). This challenge can be addressed by distributed association techniques that gracefully adapt to wireless channel variations and client mobilities. We formulated the association problem as a mixed-integer optimization aiming to maximize the network throughput with proportional fairness guarantees. This optimization problem is solved first by a distributed dual decomposition algorithm, and then by a novel distributed auction algorithm where the clients act asynchronously to achieve near-to-optimal association between the clients and APs. The latter algorithm has a faster convergence with a negligible drop in the resulting network throughput. A distinguishing novel feature of the proposed algorithms is that the resulting optimal association does not have to be re-computed every time the network changes (e.g., due to mobility). Instead, the algorithms continuously adapt to the network variations and are thus very efficient. We discuss the implementation of the proposed algorithms on top of existing communication standards. The numerical analysis verifies the ability of the proposed algorithms to optimize the association and to maintain optimality in the time-variant environments of the mm-wave networks.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
mm-wave communication, load management, distributed algorithms, user association
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-243963 (URN)10.1109/TWC.2018.2881705 (DOI)000456139200032 ()2-s2.0-85057776988 (Scopus ID)
Note

QC 20190301

Available from: 2019-03-01 Created: 2019-03-01 Last updated: 2019-03-01Bibliographically approved
Khosravi, S., Shokri-Ghadikolaei, H. & Petrova, M. (2019). Efficient Beamforming for Mobile mmWave Networks. In: : . Paper presented at The International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks WiOpt 2019. Avignon France: IFIP
Open this publication in new window or tab >>Efficient Beamforming for Mobile mmWave Networks
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We design a lightweight beam-searching algorithmfor mobile millimeter-wave systems. We construct and maintaina set of path skeletons, i.e., potential paths between a user and theserving base station to substantially expedite the beam-searchingprocess. To exploit the spatial correlations of the channels, wepropose an efficient algorithm that measures the similarity ofthe skeletons and re-executes the beam-searching procedure onlywhen the old one becomes obsolete. We identify and optimizeseveral tradeoffs between: i) the beam-searching overhead andthe instantaneous rate of the users, and ii) the number of usersand the update overhead of the path skeletons. Simulation resultsin an outdoor environment with real building map data show thatthe proposed method can significantly improve the performanceof beam-searching in terms of latency, energy consumption andachievable throughout.

Place, publisher, year, edition, pages
Avignon France: IFIP, 2019
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-249492 (URN)
Conference
The International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks WiOpt 2019
Note

QC 20190617

Available from: 2019-04-12 Created: 2019-04-12 Last updated: 2019-06-17Bibliographically approved
Shokri-Ghadikolaei, H., Ghauch, H., Fischione, C. & Skoglund, M. (2019). Learning and Data Selection in Big Datasets. In: Proceedings of the 36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019.: . Paper presented at 36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019..
Open this publication in new window or tab >>Learning and Data Selection in Big Datasets
2019 (English)In: Proceedings of the 36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019., 2019Conference paper, Published paper (Refereed)
Abstract [en]

Finding a dataset of minimal cardinality to characterize the optimal parameters of a model is of paramount importance in machine learning and distributed optimization over a network. This paper investigates the compressibility of large datasets. More specifically, we propose a framework that jointly learns the input-output mapping as well as the most representative samples of the dataset (sufficient dataset). Our analytical results show that the cardinality of the sufficient dataset increases sub-linearly with respect to the original dataset size. Numerical evaluations of real datasets reveal a large compressibility, up to 95%, without a noticeable drop in the learnability performance, measured by the generalization error.

Keywords
machine learning, optimization, non-convex, data compression
National Category
Computer Sciences
Research subject
Applied and Computational Mathematics, Optimization and Systems Theory; Information and Communication Technology; Computer Science
Identifiers
urn:nbn:se:kth:diva-260389 (URN)
Conference
36th International Conference on MachineLearning, Long Beach, California, PMLR 97, 2019.
Funder
Swedish Research Council
Note

QC 20191008

Available from: 2019-09-29 Created: 2019-09-29 Last updated: 2019-10-08Bibliographically approved
Shokri-Ghadikolaei, H., Yang, Y., Petrova, M., Sung, K. W. & Fischione, C. (2018). Fast and Reliable Initial Cell-search for mmWave Networks. In: : . Paper presented at 2nd ACM Workshop on Millimeter-Wave Networks and Sensing Systems 2018 (mmNets’18) (pp. 57-62). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Fast and Reliable Initial Cell-search for mmWave Networks
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2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In millimeter-wave wireless networks, the use of narrow beams, required to compensate for the severe path-loss, complicates the cell-discovery and initial access. In this paper, we investigate the feasibility of random beam forming and enhanced exhaustive search for cell-discovery by analyzing the latency and detection failure probability in the control-plane and the user throughput in the data-plane. We show that, under realistic propagation model and antenna patterns, both approaches are suitable for 3GPP New Radio cellular networks. The performance gain, compared to the heavily used exhaustive and iterative search schemes, is more prominent in dense networks and large antenna regimes and can be further improved by optimizing the beam forming code-books.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-239140 (URN)10.1145/3264492.3264502 (DOI)000480467200011 ()2-s2.0-85061490095 (Scopus ID)978-1-4503-5928-3 (ISBN)
Conference
2nd ACM Workshop on Millimeter-Wave Networks and Sensing Systems 2018 (mmNets’18)
Note

QC 20181119

Available from: 2018-11-16 Created: 2018-11-16 Last updated: 2019-09-03Bibliographically approved
Shokri-Ghadikolaei, H., Fischione, C. & Modiano, E. (2018). Interference Model Similarity Index and Its Applications to Millimeter-Wave Networks. IEEE Transactions on Wireless Communications, 17(1), 71-85
Open this publication in new window or tab >>Interference Model Similarity Index and Its Applications to Millimeter-Wave Networks
2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 1, p. 71-85Article in journal (Refereed) Published
Abstract [en]

In wireless communication networks, interference models are routinely used for tasks, such as performance analysis, optimization, and protocol design. These tasks are heavily affected by the accuracy and tractability of the interference models. Yet, quantifying the accuracy of these models remains a major challenge. In this paper, we propose a new index for assessing the accuracy of any interference model under any network scenario. Specifically, it is based on a new index that quantifies the ability of any interference model in correctly predicting harmful interference events, that is, link outages. We consider specific wireless scenario of both conventional sub-6 GHz and millimeter-wave networks and demonstrate how our index yields insights into the possibility of simplifying the set of dominant interferers, replacing a Nakagami or Rayleigh random fading by an equivalent deterministic channel, and ignoring antenna sidelobes. Our analysis reveals that in highly directional antenna settings with obstructions, even simple interference models (such as the classical protocol model) are accurate, while with omnidirectional antennas, more sophisticated and complex interference models (such as the classical physical model) are necessary. Our new approach makes it possible to adopt the simplest interference model of adequate accuracy for every wireless network.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Wireless communications, interference model, performance analysis, millimeter-wave networks
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-222454 (URN)10.1109/TWC.2017.2762667 (DOI)000422945400006 ()2-s2.0-85032305190 (Scopus ID)
Note

QC 20180209

Available from: 2018-02-09 Created: 2018-02-09 Last updated: 2018-02-20Bibliographically approved
Shokri-Ghadikolaei, H., Ghauch, H. & Fischione, C. (2018). Learning-based tracking of AoAs and AoDs in mmWave networks. In: Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM: . Paper presented at 2nd ACM Workshop on Millimeter Wave Networks and Sensing Systems, mmNets 2018, , Co-located with MobiCom 2018, 29 October 2018 (pp. 45-50). Association for Computing Machinery
Open this publication in new window or tab >>Learning-based tracking of AoAs and AoDs in mmWave networks
2018 (English)In: Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM, Association for Computing Machinery , 2018, p. 45-50Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers a millimeter-wave communication system and proposes an efficient channel estimation scheme with a minimum number of pilots. We model the dynamics of the channel’s second-order statistics by a Markov process and develop a learning framework to obtain these dynamics from an unlabeled set of measured angles of arrival and departure. We then find the optimal precoding and combining vectors for pilot signals. Using these vectors, the transmitter and receiver will sequentially estimate the corresponding angles of departure and arrival, and then refine the pilot precoding and combining vectors to minimize the error of estimating the channel gains.

Place, publisher, year, edition, pages
Association for Computing Machinery, 2018
Keywords
Channel estimation, Machine learning, Markov decision process, Millimeter-wave, Tracking, Learning algorithms, Learning systems, Markov processes, Surface discharges, Angles of arrival, Channel gains, Learning frameworks, Markov Decision Processes, Millimeter-wave communication, Pilot signals, Second order statistics, Transmitter and receiver, Millimeter waves
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-247151 (URN)10.1145/3264492.3264500 (DOI)000480467200009 ()2-s2.0-85061507133 (Scopus ID)9781450359283 (ISBN)
Conference
2nd ACM Workshop on Millimeter Wave Networks and Sensing Systems, mmNets 2018, , Co-located with MobiCom 2018, 29 October 2018
Note

QC 20190507

Available from: 2019-05-07 Created: 2019-05-07 Last updated: 2019-09-03Bibliographically approved
Jiang, X., Shokri-Ghadikolaei, H., Fodor, G., Modiano, E., Pang, Z., Zorzi, M. & Fischione, C. (2018). Low-Latency Networking: Where Latency Lurks and How to Tame It. Proceedings of the IEEE, 1-27
Open this publication in new window or tab >>Low-Latency Networking: Where Latency Lurks and How to Tame It
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2018 (English)In: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, p. 1-27Article in journal (Refereed) Published
Abstract [en]

While the current generation of mobile and fixed communication networks has been standardized for mobile broadband services, the next generation is driven by the vision of the Internet of Things and mission-critical communication services requiring latency in the order of milliseconds or submilliseconds. However, these new stringent requirements have a large technical impact on the design of all layers of the communication protocol stack. The cross-layer interactions are complex due to the multiple design principles and technologies that contribute to the layers' design and fundamental performance limitations. We will be able to develop low-latency networks only if we address the problem of these complex interactions from the new point of view of submilliseconds latency. In this paper, we propose a holistic analysis and classification of the main design principles and enabling technologies that will make it possible to deploy low-latency wireless communication networks. We argue that these design principles and enabling technologies must be carefully orchestrated to meet the stringent requirements and to manage the inherent tradeoffs between low latency and traditional performance metrics. We also review currently ongoing standardization activities in prominent standards associations, and discuss open problems for future research.

National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-239002 (URN)10.1109/JPROC.2018.2863960 (DOI)000460669300004 ()2-s2.0-85052809127 (Scopus ID)
Note

QC 20181115

Available from: 2018-11-14 Created: 2018-11-14 Last updated: 2019-05-07Bibliographically approved
Olfat, E., Shokri-Ghadikolaei, H., Moghadam, N. N., Bengtsson, M. & Fischione, C. (2017). Learning-based Pilot Precoding and Combining for Wideband Millimeter-wave Networks. In: 2017 IEEE 7TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP): . Paper presented at CAMSAP 2017) 2017 17th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, December 10-13, 2017 Curacao, Dutch Antilles. IEEE
Open this publication in new window or tab >>Learning-based Pilot Precoding and Combining for Wideband Millimeter-wave Networks
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2017 (English)In: 2017 IEEE 7TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING (CAMSAP), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes an efficient channel estimation scheme with a minimum number of pilots for a frequency-selective millimeter-wave communication system. We model the dynamics of the channel's second-order statistics by a Markov process and develop a learning framework that finds the optimal precoding and combining vectors for pilot signals, given the channel dynamics. Using these vectors, the transmitter and receiver will sequentially estimate the corresponding angles of departure and arrival, and then refine the pilot precoding and combining vectors to minimize the error of estimating the small-scale fading of all subcarriers. Numerical results demonstrate near-optimality of our approach, compared to the oracle wherein the second-order statistics (not the dynamics) are perfectly known a priori.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-226260 (URN)10.1109/CAMSAP.2017.8313146 (DOI)000428438100090 ()2-s2.0-85050724648 (Scopus ID)
Conference
CAMSAP 2017) 2017 17th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, December 10-13, 2017 Curacao, Dutch Antilles
Note

QC 20180504

Available from: 2018-05-04 Created: 2018-05-04 Last updated: 2018-11-20Bibliographically approved
Moghadam, N. N., Shokri-Ghadikolaei, H., Fodor, G., Bengtsson, M. & Fischione, C. (2017). Pilot precoding and combining in multiuser MIMO networks. In: 2017 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP (ICASSP): . Paper presented at IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), MAR 05-09, 2017, New Orleans, LA (pp. 3544-3548). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Pilot precoding and combining in multiuser MIMO networks
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2017 (English)In: 2017 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 3544-3548Conference paper (Refereed)
Abstract [en]

Although the benefits of precoding and combining of data streams are widely recognized, the potential of precoding the pilot signals at the user equipment (UE) side and combining them at the base station (BS) side has not received adequate attention. This paper considers a multiuser multiple input multiple output (MU-MIMO) cellular system in which the BS acquires channel state information (CSI) by means of uplink pilot signals and proposes pilot precoding and combining to improve the CSI quality. We first evaluate the channel estimation performance of a baseline scenario in which CSI is acquired with no pilot precoding. Next, we characterize the channel estimation error when the pilot signals are precoded by spatial filters that asymptotically maximize the channel estimation quality. Finally, we study the case when, in addition to pilot precoding at the UE side, the BS utilizes the second order statistics of the channels to further improve the channel estimation performance. The analytical and numerical results show that, specially in scenarios with large number of antennas at the BS and UEs, pilot precoding and combining has a great potential to improve the channel estimation quality in MU-MIMO systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords
multiuser MIMO, channel estimation, minimum mean squared error, transceiver design
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-221043 (URN)10.1109/ICASSP.2017.7952816 (DOI)000414286203142 ()2-s2.0-85023764713 (Scopus ID)978-1-5090-4117-6 (ISBN)
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), MAR 05-09, 2017, New Orleans, LA
Note

QC 20180112

Available from: 2018-01-12 Created: 2018-01-12 Last updated: 2018-01-12Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-6737-0266

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