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Publications (10 of 179) Show all publications
Saxena, V., Jaldén, J., Gonzalez, J. E., Bengtsson, M., Tullberg, H. & Stoica, I. (2019). Contextual multi-armed bandits for link adaptation in cellular networks. In: NetAI 2019 - Proceedings of the 2019 ACM SIGCOMM Workshop on Network Meets AI and ML, Part of SIGCOMM 2019: . Paper presented at 2019 ACM SIGCOMM Workshop on Network Meets AI and ML, NetAI 2019, Part of SIGCOMM 2019, 23 August 2019 (pp. 44-49). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Contextual multi-armed bandits for link adaptation in cellular networks
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2019 (English)In: NetAI 2019 - Proceedings of the 2019 ACM SIGCOMM Workshop on Network Meets AI and ML, Part of SIGCOMM 2019, Association for Computing Machinery (ACM), 2019, p. 44-49Conference paper, Published paper (Refereed)
Abstract [en]

Cellular networks dynamically adjust the transmission parameters for a wireless link in response to its time-varying channel state. This is known as link adaptation, where the typical goal is to maximize the link throughput. State-of-the-art outer loop link adaptation (OLLA) selects the optimal transmission parameters based on an approximate, offline, model of the wireless link. Further, OLLA refines the offline model by dynamically compensating any deviations from the observed link performance. However, in practice, OLLA suffers from slow convergence and a sub-optimal link throughput. In this paper, we propose a link adaptation approach that overcomes the shortcomings of OLLA through a novel learning scheme. Our approach relies on contextual multi-armed bandits (MAB), where the context vector is composed of the instantaneous wireless channel state along with side information about the link. For a given context, our approach learns the success probability for each of the available transmission parameters, which is then exploited to select the throughput-maximizing parameters. Through numerical experiments, we show that our approach converges faster than OLLA and achieves a higher steady-state link throughput. For frequent and infrequent channel reports respectively, our scheme outperforms OLLA by 15% and 25% in terms of the steady-state link throughpu.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2019
Keywords
Artificial neural networks, Cellular networks, Contextual multiarmed bandits, Outer loop link adaptation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-262526 (URN)10.1145/3341216.3342212 (DOI)2-s2.0-85072036655 (Scopus ID)9781450368728 (ISBN)
Conference
2019 ACM SIGCOMM Workshop on Network Meets AI and ML, NetAI 2019, Part of SIGCOMM 2019, 23 August 2019
Note

QC 20191028

Available from: 2019-10-28 Created: 2019-10-28 Last updated: 2019-10-28Bibliographically approved
Panigrahi, S. R., Björsell, N. & Bengtsson, M. (2019). Data Fusion in the Air With Non-Identical Wireless Sensors. IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 5(4), 646-656
Open this publication in new window or tab >>Data Fusion in the Air With Non-Identical Wireless Sensors
2019 (English)In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, ISSN 2373-776X, Vol. 5, no 4, p. 646-656Article in journal (Refereed) Published
Abstract [en]

In this paper, a multi-hypothesis distributed detection technique with non-identical local detectors is investigated. Here, for a global event, some of the sensors/detectors can observe the whole set of hypotheses, whereas the remaining sensors can either see only some aspects of the global event or infer more than one hypothesis as a single hypothesis. Another possible option is that different sensors provide complementary information. The local decisions are sent over a multiple access radio channel so that the data fusion is formed in the air before reaching the decision fusion center (DFC). An optimal energy fusion rule is formulated by considering the radio channel effects and the reliability of the sensors together, and a closed-form solution is derived. A receive beamforming algorithm, based on a modification of Lozano & x0027;s algorithm, is proposed to equalize the channel gains from different sensors. Sensors with limited detection capabilities are found to boost the overall system performance when they are used along with fully capable sensors. The additional transmit power used by these sensors is compensated by the designed fusion rule and the antenna array gain. Additionally, the DFC, equipped with a large antenna array, can reduce the overall transmit energy consumption without sacrificing the detection performance.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Temperature sensors, Manganese, Wireless sensor networks, Antenna arrays, Sensor fusion, Data integration, Wireless Sensor Network, Multiple hypotheses, Non-identical local detector, MAC, Data Fusion in the air, Optimal power fusion rule, Large antenna array
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-264156 (URN)10.1109/TSIPN.2019.2928175 (DOI)000492993200003 ()2-s2.0-85074191069 (Scopus ID)
Note

QC 20191210

Available from: 2019-12-10 Created: 2019-12-10 Last updated: 2019-12-10Bibliographically approved
Tolli, A., Ghauch, H., Kaleva, J., Komulainen, P., Bengtsson, M., Skoglund, M., . . . Pajukoski, K. (2019). Distributed Coordinated Transmission with Forward-Backward Training for 5G Radio Access. IEEE Communications Magazine, 57(1), 58-64
Open this publication in new window or tab >>Distributed Coordinated Transmission with Forward-Backward Training for 5G Radio Access
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2019 (English)In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 57, no 1, p. 58-64Article in journal (Refereed) Published
Abstract [en]

CoMP transmission and reception have been considered in cellular networks for enabling larger coverage, improved rates, and interference mitigation. To harness the gains of coordinated beamforming, fast information exchange over a backhaul connecting the cooperating BSs is required. In practice, the bandwidth and delay limitations of the backhaul may not be able to meet such stringent demands. These impairments motivate the study of cooperative approaches based only on local CSI that require minimal or no information exchange between the BSs. To this end, several distributed approaches are introduced for CB-CoMP. The proposed methods rely on the channel reciprocity and iterative spatially precoded over-the-air pilot signaling. We elaborate how F-B training facilitates distributed CB by allowing BSs and UEs to iteratively optimize their respective transmitters/receivers based on only locally measured CSI. The trade-off due to the overhead from the F-B iterations is discussed. We also consider the challenge of dynamic TDD where the UE-UE channel knowledge cannot be acquired at the BSs by exploiting channel reciprocity. Finally, standardization activities and practical requirements for enabling the proposed F-B training schemes in 5G radio access are discussed.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
National Category
Communication Systems
Identifiers
urn:nbn:se:kth:diva-244555 (URN)10.1109/MCOM.2018.1700199 (DOI)000457640200011 ()2-s2.0-85060522227 (Scopus ID)
Note

QC 20190313

Available from: 2019-03-13 Created: 2019-03-13 Last updated: 2019-03-13Bibliographically approved
Kant, S., Fodor, G., Bengtsson, M., Göransson, B. & Fischione, C. (2019). Low-Complexity OFDM Spectral Precoding. In: 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019: . Paper presented at 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019; Cannes; France; 2 July 2019 through 5 July 2019. , Article ID 8815554.
Open this publication in new window or tab >>Low-Complexity OFDM Spectral Precoding
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2019 (English)In: 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, 2019, article id 8815554Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a new large-scale mask compliant spectral precoder (LS-MSP) for orthogonal frequency division multiplexing systems. In this paper, we first consider a previously proposed mask-compliant spectral precoding scheme that utilizes a generic convex optimization solver which suffers from high computational complexity, notably in large-scale systems. To mitigate the complexity of computing the LS-MSP, we propose a divide-and-conquer approach that breaks the original problem into smaller rank 1 quadratic-constraint problems and each small problem yields closed-form solution. Based on these solutions, we develop three specialized first-order low-complexity algorithms, based on 1) projection on convex sets and 2) the alternating direction method of multipliers. We also develop an algorithm that capitalizes on the closed-form solutions for the rank 1 quadratic constraints, which is referred to as 3) semianalytical spectral precoding. Numerical results show that the proposed LS-MSP techniques outperform previously proposed techniques in terms of the computational burden while complying with the spectrum mask. The results also indicate that 3) typically needs 3 iterations to achieve similar results as 1) and 2) at the expense of a slightly increased computational complexity.

Keywords
Spectral Precoding, OFDM, 5G, mmWave
National Category
Signal Processing
Research subject
Telecommunication
Identifiers
urn:nbn:se:kth:diva-258067 (URN)10.1109/SPAWC.2019.8815554 (DOI)2-s2.0-85072337396 (Scopus ID)9781538665282 (ISBN)
Conference
20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2019; Cannes; France; 2 July 2019 through 5 July 2019
Funder
Swedish Foundation for Strategic Research , ID17-0114
Note

QC 20190923

Available from: 2019-09-09 Created: 2019-09-09 Last updated: 2019-10-22Bibliographically approved
Charalambous, T., Kim, S. M., Nomikos, N., Bengtsson, M. & Johansson, M. (2019). Relay-pair selection in buffer-aided successive opportunistic relaying using a multi-antenna source. Ad hoc networks, 84, 29-41
Open this publication in new window or tab >>Relay-pair selection in buffer-aided successive opportunistic relaying using a multi-antenna source
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2019 (English)In: Ad hoc networks, ISSN 1570-8705, E-ISSN 1570-8713, Vol. 84, p. 29-41Article in journal (Refereed) Published
Abstract [en]

We study a cooperative network with a buffer-aided multi-antenna source, multiple half-duplex (HD) buffer-aided relays and a single destination. Such a setup could represent a cellular downlink scenario, in which the source can be a more powerful wireless device with a buffer and multiple antennas, while a set of intermediate less powerful devices are used as relays to reach the destination. The main target is to recover the multiplexing loss of the network by having the source and a relay to simultaneously transmit their information to another relay and the destination, respectively. Successive transmissions in such a cooperative network, however, cause inter-relay interference (IRI). First, by assuming global channel state information (CSI), we show that the detrimental effect of IRI can be alleviated by precoding at the source, mitigating or even fully cancelling the interference. A cooperative relaying policy is proposed that employs a joint precoding design and relay-pair selection. Note that both fixed rate and adaptive rate transmissions can be considered. For the case when channel state information is only available at the receiver side (CSIR), we propose a relay selection policy that employs a phase alignment technique to reduce the IRI. The performance of the two proposed relay pair selection policies are evaluated and compared with other state-of-the-art relaying schemes in terms of outage and throughput. The results show that the use of a powerful source can provide considerable performance improvements.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV, 2019
Keywords
Opportunistic relaying, Buffer-aided relays, Precoding, Phase-alignment, Interference cancellation, Interference mitigation
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-243930 (URN)10.1016/j.adhoc.2018.09.002 (DOI)000456751400005 ()2-s2.0-85054687404 (Scopus ID)
Note

QC 20190313

Available from: 2019-03-13 Created: 2019-03-13 Last updated: 2019-03-13Bibliographically approved
Shariati, N., Zachariah, D., Karlsson, J. & Bengtsson, M. (2019). Robust Optimal Power Distribution for Hyperthermia Cancer Treatment. In: Hamed Farhadi (Ed.), Medical Internet of Things (m-IoT): (pp. 55-70). IntechOpen
Open this publication in new window or tab >>Robust Optimal Power Distribution for Hyperthermia Cancer Treatment
2019 (English)In: Medical Internet of Things (m-IoT) / [ed] Hamed Farhadi, IntechOpen , 2019, p. 55-70Chapter in book (Other academic)
Abstract [en]

We consider an optimization problem for spatial power distribution generated by an array of transmitting elements. Using ultrasound hyperthermia cancer treatment as a motivating example, the signal design problem consists of optimizing the power distribution across the tumor and healthy tissue regions, respectively. The models used in the optimization problem are, however, invariably subject to errors. To combat such unknown model errors, we formulate a robust signal design framework that can take the uncertainty into account using a worst-case approach. This leads to a semi-infinite programming (SIP) robust design problem, which we reformulate as a tractable convex problem that potentially has a wider range of applications.

Place, publisher, year, edition, pages
IntechOpen, 2019
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-259526 (URN)10.5772/intechopen.73281 (DOI)978-1-78985-092-5 (ISBN)978-1-78985-091-8 (ISBN)
Note

QC 20191015

Available from: 2019-09-17 Created: 2019-09-17 Last updated: 2019-10-15Bibliographically approved
Saxena, V., Cavarec, B., Jaldén, J., Bengtsson, M. & Tullberg, H. (2018). A Learning Approach for Optimal Codebook Selection in Spatial Modulation Systems. In: Matthews, M B (Ed.), 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS: . Paper presented at 52nd Asilomar Conference on Signals, Systems, and Computers, OCT 28-NOV 01, 2018, Pacific Grove, CA (pp. 1800-1804). IEEE
Open this publication in new window or tab >>A Learning Approach for Optimal Codebook Selection in Spatial Modulation Systems
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2018 (English)In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS / [ed] Matthews, M B, IEEE , 2018, p. 1800-1804Conference paper, Published paper (Refereed)
Abstract [en]

For spatial modulation (SNI) systems that utilize multiple transmit antennas/patterns with a single radio front-end, we propose a learning approach to predict the average symbol error rate (SER) conditioned on the instantaneous channel state. We show that the predicted SER can he used to lower the average SER over Rayleigh fading channels by selecting the optimal codebook in each transmission instance. Further by exploiting that feedforward artificial neural networks (ANNs) trained with a mean squared error (MSE) criterion estimate the conditional a posteriori probabilities, we maximize the expected rate for each transmission instance and thereby improve the link spectral efficiency.

Place, publisher, year, edition, pages
IEEE, 2018
Series
Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-252674 (URN)000467845100317 ()2-s2.0-85062983648 (Scopus ID)978-1-5386-9218-9 (ISBN)
Conference
52nd Asilomar Conference on Signals, Systems, and Computers, OCT 28-NOV 01, 2018, Pacific Grove, CA
Note

QC 20190603

Available from: 2019-06-03 Created: 2019-06-03 Last updated: 2019-07-31Bibliographically approved
Olfat, E. & Bengtsson, M. (2018). Channel and Clipping Level Estimation in OFDMSystems. In: : . Paper presented at IEEE Wireless Communications and Networking Conference (WCNC). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Channel and Clipping Level Estimation in OFDMSystems
2018 (English)Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-235353 (URN)
Conference
IEEE Wireless Communications and Networking Conference (WCNC)
Note

QC 20180926

Available from: 2018-09-24 Created: 2018-09-24 Last updated: 2018-09-26Bibliographically approved
Cavarec, B. & Bengtsson, M. (2018). CHANNEL DEPENDENT CODEBOOK DESIGN IN SPATIAL MODULATION. In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 6413-6417). IEEE
Open this publication in new window or tab >>CHANNEL DEPENDENT CODEBOOK DESIGN IN SPATIAL MODULATION
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 6413-6417Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we present a modulation design based on Spatial Modulation for the uplink in IoT applications. The proposed modulation design uses a Tabu search based deterministic heuristic to adapt the modulation link based on channel information fed back by the receiver. Our approach allows adaptivity to rate and energy constraints. We numerically validate the proposed method on a scenario with full channel state information available at the transceiver, showing clear performance gains compared to simpler heuristics and channel independent codebook designs.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Energy efficiency, Spatial Modulation, Code-book design
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-237155 (URN)10.1109/ICASSP.2018.8461968 (DOI)000446384606114 ()2-s2.0-85054266538 (Scopus ID)
Conference
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Note

QC 20181024

Available from: 2018-10-24 Created: 2018-10-24 Last updated: 2019-08-20Bibliographically approved
Saxena, V., Jaldén, J., Bengtsson, M. & Tullberg, H. (2018). DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS. In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 6658-6662). IEEE
Open this publication in new window or tab >>DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE, 2018, p. 6658-6662Conference paper, Published paper (Refereed)
Abstract [en]

In the context of wireless communications, we propose a deep learning approach to learn the mapping from the instantaneous state of a frequency selective fading channel to the corresponding frame error probability (FEP) for an arbitrary set of transmission parameters. We propose an abstract model of a bit interleaved coded modulation (BICM) orthogonal frequency division multiplexing (OFDM) link chain and show that the maximum likelihood (ML) estimator of the model parameters estimates the true FEP distribution. Further, we exploit deep neural networks as a general purpose tool to implement our model and propose a training scheme for which, even while training with the binary frame error events (i.e., ACKs/NACKs), the network outputs converge to the FEP conditioned on the input channel state. We provide simulation results that demonstrate gains in the FEP prediction accuracy with our approach as compared to the traditional effective exponential SIR metric (EESM) approach for a range of channel code rates, and show that these gains can be exploited to increase the link throughput.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
FEP, BICM-OFDM, Deep Learning, Neural Networks, Link Adaptation
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-237157 (URN)10.1109/ICASSP.2018.8461864 (DOI)000446384606163 ()2-s2.0-85054259851 (Scopus ID)
Conference
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Funder
Wallenberg Foundations
Note

QC 20181025

Available from: 2018-10-25 Created: 2018-10-25 Last updated: 2018-10-25Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3599-5584

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