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Publications (10 of 170) Show all publications
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
Ainomae, A., Bengtsson, M. & Trump, T. (2018). Distributed Largest Eigenvalue-Based Spectrum Sensing Using Diffusion LMS. IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 4(2), 362-377
Open this publication in new window or tab >>Distributed Largest Eigenvalue-Based Spectrum Sensing Using Diffusion LMS
2018 (English)In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, ISSN 2373-776X, Vol. 4, no 2, p. 362-377Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a distributed detection scheme for cognitive radio (CR) networks, based on the largest eigenvalues (LEs) of adaptively estimated correlation matrices (CMs), assuming that the primary user signal is temporally correlated. The proposed algorithm is fully distributed, there by avoiding the potential single point of failure that a fusion center would imply. Different forms of diffusion least mean square algorithms are used for estimating and averaging the CMs over the CR network for the LE detection and the resulting estimation performance is analyzed using a common framework. In order to obtain analytic results on the detection performance, the exact distribution of the CM estimates are approximated by a Wishart distribution, by matching the moments. The theoretical findings are verified through simulations.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Cognitive radio, distributed estimation, diffusion LMS, diffusion networks, distributed detection, spectrum sensing, random matrix
National Category
Probability Theory and Statistics
Identifiers
urn:nbn:se:kth:diva-228258 (URN)10.1109/TSIPN.2017.2705483 (DOI)000431400000008 ()2-s2.0-85049504421 (Scopus ID)
Note

QC 20180524

Available from: 2018-05-24 Created: 2018-05-24 Last updated: 2018-10-16Bibliographically approved
Olfat, E. & Bengtsson, M. (2018). Joint Channel and Clipping Level Estimationfor SIMO-OFDM Systems. In: : . Paper presented at IEEE Wireless Communications and Networking Conference (WCNC).
Open this publication in new window or tab >>Joint Channel and Clipping Level Estimationfor SIMO-OFDM Systems
2018 (English)Conference paper, Published paper (Refereed)
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-235354 (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
Olfat, E. & Bengtsson, M. (2017). Joint Channel and Clipping Level Estimation for OFDM in IoT-based Networks. IEEE Transactions on Signal Processing, 65(18), 4902-4911
Open this publication in new window or tab >>Joint Channel and Clipping Level Estimation for OFDM in IoT-based Networks
2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 18, p. 4902-4911Article in journal (Refereed) Published
Abstract [en]

We consider scenarios such as IoT-based 5G or IoTbased machine type communication, where a low-cost low-power transmitter communicates with a high-quality receiver. Then, digital predistortion of the nonlinear power amplifier may be too expensive. In order to investigate the feasibility of receiver-side compensation of the transmitter RF impairments, we study joint maximum-likelihood estimation of channel and clipping level in multipath fading OFDM systems. In particular, we propose an alternative optimization algorithm, which uses frequency-domain block-type training symbols, and prove that this algorithm always converges, at least to a local optimum point. Then, we calculate the Cramer-Rao lower bound, and show that the proposed estimator attains it for high signal-to-noise ratios. Finally, we perform numerical evaluations to illustrate the performance of the estimator, and show that iterative decoding can be done using the estimated channel and clipping level with almost the same performance as a genie-aided scenario, where the channel and clipping level are perfectly known.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
OFDM, clipping, channel, estimation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-211582 (URN)10.1109/TSP.2017.2713765 (DOI)000405705900016 ()2-s2.0-85029210880 (Scopus ID)
Note

QC 20170815

Available from: 2017-08-15 Created: 2017-08-15 Last updated: 2018-09-26Bibliographically approved
Olfat, E. (2017). Joint Channel and Clipping Level Estimation for OFDM in IoT-based Networks. IEEE Transactions on Signal Processing
Open this publication in new window or tab >>Joint Channel and Clipping Level Estimation for OFDM in IoT-based Networks
2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476Article in journal (Refereed) Published
Place, publisher, year, edition, pages
IEEE, 2017
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-235350 (URN)10.1109/TSP.2017.2713765 (DOI)000405705900016 ()2-s2.0-85029210880 (Scopus ID)
Note

QC 20181002

Available from: 2018-09-24 Created: 2018-09-24 Last updated: 2018-10-02Bibliographically 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)000428438100090 ()
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: 2018-05-04Bibliographically 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
Cavarec, B. & Bengtsson, M. (2017). Pulse Design for Spectrally efficient Transmissions assuming Maximum Likelihood Detection. In: Matthews, M B (Ed.), 2017 Fifty-First Asilomar Conference on Signals, Systems, And Computers: . Paper presented at 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Asilomar Hotel and Conference GroundsPacific Grove; United States; 2 October 2017 through 1 November 2017; (pp. 1754-1758). IEEE Computer Society
Open this publication in new window or tab >>Pulse Design for Spectrally efficient Transmissions assuming Maximum Likelihood Detection
2017 (English)In: 2017 Fifty-First Asilomar Conference on Signals, Systems, And Computers / [ed] Matthews, M B, IEEE Computer Society, 2017, p. 1754-1758Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we analyse different spectrally efficient waveforming modulations under the framework of Gabor analysis. We derive a channel adaptive pulse design paradigm for such modulations under Maximum Likelihood (ML) detection at the receiver. The proposed pulse design is tested on a simulation scenario with high self-interference and compared with existing pulses at different spectral densities.

Place, publisher, year, edition, pages
IEEE Computer Society, 2017
Series
Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-235166 (URN)10.1109/ACSSC.2017.8335662 (DOI)000442659900311 ()2-s2.0-85050967023 (Scopus ID)978-1-5386-1823-3 (ISBN)
Conference
51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Asilomar Hotel and Conference GroundsPacific Grove; United States; 2 October 2017 through 1 November 2017;
Note

QC 20180917

Available from: 2018-09-17 Created: 2018-09-17 Last updated: 2018-09-17Bibliographically approved
Ghauch, H., Kim, T., Bengtsson, M. & Skoglund, M. (2017). Sum-Rate Maximization in Sub-28-GHz Millimeter-Wave MIMO Interfering Networks. IEEE Journal on Selected Areas in Communications, 35(7), 1649-1662
Open this publication in new window or tab >>Sum-Rate Maximization in Sub-28-GHz Millimeter-Wave MIMO Interfering Networks
2017 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 35, no 7, p. 1649-1662Article in journal (Refereed) Published
Abstract [en]

MIMO systems in the lower part of the millimetre-wave (mmWave) spectrum band (i.e., below 28 GHz) do not exhibit enough directivity and selectively, as compared to their counterparts in higher bands of the spectrum (i.e., above 60 GHz), and thus still suffer from the detrimental effect of interference, on the system sum rate. As such systems exhibit large numbers of antennas and short coherence times for the channel, traditional methods of distributed coordination are ill-suited, and the resulting communication overhead would offset the gains of coordination. In this paper, we propose algorithms for tackling the sum-rate maximization problem that are designed to address the above-mentioned limitations. We derive a lower bound on the sum rate, a so-called difference of log and trace (DLT) bound, shed light on its tightness, and highlight its decoupled nature at both the transmitters and receivers. Moreover, we derive the solution to each of the subproblems that we dub non-homogeneous waterfilling (a variation on the MIMO waterfilling solution), and underline an inherent desirable feature: its ability to turn-OFF streams exhibiting low SINR, and contribute to greatly speeding up the convergence of the proposed algorithm. We then show the convergence of the resulting algorithm, max-DLT, to a stationary point of the DLT bound. Finally, we rely on extensive simulations of various network configurations, to establish the fast-converging nature of our proposed schemes, and thus their suitability for addressing the short coherence interval, as well as the increased system dimensions, arising when managing interference in lower bands of the mmWave spectrum. Moreover, our results suggest that interference management still brings about significant performance gains, especially in dense deployments.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
Sub-28 GHz millimeter-wave, interference management, fast-converging algorithms, distributed optimization, difference of log and trace (DLT), non-homogeneous waterfilling, max-DLT, alternating iterative maximal separation (AIMS)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-210997 (URN)10.1109/JSAC.2017.2698779 (DOI)000404242600018 ()2-s2.0-85021337121 (Scopus ID)
Note

QC 20170807

Available from: 2017-08-07 Created: 2017-08-07 Last updated: 2017-08-07Bibliographically approved
Brandt, R. & Bengtsson, M. (2016). Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems. IEEE Transactions on Vehicular Technology, 65(5), 2890-2906
Open this publication in new window or tab >>Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems
2016 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 65, no 5, p. 2890-2906Article in journal (Refereed) Published
Abstract [en]

Several distributed coordinated precoding methods exist in the downlink multicell MIMO literature, many of which assume perfect knowledge of received signal covariance and local effective channels. In this work, we let the notion of channel state information (CSI) encompass this knowledge of covariances and effective channels. We analyze what local CSI is required in the WMMSE algorithm for distributed coordinated precoding, and study how this required CSI can be obtained in a distributed fashion. Based on pilot-assisted channel estimation, we propose three CSI acquisition methods with different tradeoffs between feedback and signaling, backhaul use, and computational complexity. One of the proposed methods is fully distributed, meaning that it only depends on over-the-air signaling but requires no backhaul, and results in a fully distributed joint system when coupled with the WMMSE algorithm. Naively applying the WMMSE algorithm together with the fully distributed CSI acquisition results in catastrophic performance however, and therefore we propose a robustified WMMSE algorithm based on the well known diagonal loading framework. By enforcing properties of the WMMSE solutions with perfect CSI onto the problem with imperfect CSI, the resulting diagonally loaded spatial filters are shown to perform significantly better than the naive filters. The proposed robust and distributed system is evaluated using numerical simulations, and shown to perform well compared with benchmarks. Under centralized CSI acquisition, the proposed algorithm performs on par with other existing centralized robust WMMSE algorithms. When evaluated in a large scale fading environment, the performance of the proposed system is promising.

Place, publisher, year, edition, pages
IEEE Press, 2016
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-166426 (URN)10.1109/TVT.2015.2432051 (DOI)000376094500005 ()2-s2.0-84969915743 (Scopus ID)
Funder
Swedish Research Council, 621-2012-4134
Note

QC 20150521

Available from: 2015-05-09 Created: 2015-05-09 Last updated: 2017-12-04Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3599-5584

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