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Publications (10 of 459) Show all publications
Zhang, X., Nakhai, M. R., Zheng, G., Lambotharan, S. & Ottersten, B. (2019). Calibrated Learning for Online Distributed Power Allocation in Small-Cell Networks. IEEE Transactions on Communications, 67(11), 8124-8136
Open this publication in new window or tab >>Calibrated Learning for Online Distributed Power Allocation in Small-Cell Networks
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2019 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 11, p. 8124-8136Article in journal (Refereed) Published
Abstract [en]

This paper introduces a combined calibrated learning and bandit approach to online distributed power control in small cell networks operated under the same frequency bandwidth. Each small base station (SBS) is modelled as an intelligent agent who autonomously decides on its instantaneous transmit power level by predicting the transmitting policies of the other SBSs, namely the opponent SBSs, in the network, in real-time. The decision making process is based jointly on the past observations and the calibrated forecasts of the upcoming power allocation decisions of the opponent SBSs who inflict the dominant interferences on the agent. Furthermore, we integrate the proposed calibrated forecast process with a bandit policy to account for the wireless channel conditions unknown a priori, and develop an autonomous power allocation algorithm that is executable at individual SBSs to enhance the accuracy of the autonomous decision making. We evaluate the performance of the proposed algorithm in cases of maximizing the long-term sum-rate, the overall energy efficiency and the average minimum achievable data rate. Numerical simulation results demonstrate that the proposed design outperforms the benchmark scheme with limited amount of information exchange and rapidly approaches towards the optimal centralized solution for all case studies.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
small cell, distributed power control, online learning, calibration
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-258945 (URN)10.1109/TCOMM.2019.2938514 (DOI)2-s2.0-85075597856 (Scopus ID)
Note

QC 20191112

Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2020-01-09Bibliographically approved
Krivochiza, J., Duncan, J. M., Andrenacci, S., Chatzinotas, S. & Ottersten, B. (2019). FPGA Acceleration for Computationally Efficient Symbol-Level Precoding in Multi-User Multi-Antenna Communication Systems. IEEE Access, 7, 15509-15520
Open this publication in new window or tab >>FPGA Acceleration for Computationally Efficient Symbol-Level Precoding in Multi-User Multi-Antenna Communication Systems
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 15509-15520Article in journal (Refereed) Published
Keywords
Precoding;Field programmable gate arrays;Optimization;Interference;Logic gates;Hardware design languages;MIMO communication;Convex programming;field programmable gate arrays;hardware resources;multicast communication;MIMO;optimization;precoding;power minimization;interference;wireless channels
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-258954 (URN)10.1109/ACCESS.2019.2894181 (DOI)
Note

IEEE Access Best Multimedia Award. QC 20191105

Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2020-02-17Bibliographically approved
Mishra, K. V., Shankar, M. R., Koivunen, V., Ottersten, B. & Vorobyov, S. A. (2019). Toward Millimeter-Wave Joint Radar Communications A signal processing perspective. IEEE signal processing magazine (Print), 36(5), 100-114
Open this publication in new window or tab >>Toward Millimeter-Wave Joint Radar Communications A signal processing perspective
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2019 (English)In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 36, no 5, p. 100-114Article in journal (Refereed) Published
Abstract [en]

Synergistic design of communications and radar systems with common spectral and hardware resources is heralding a new era of efficiently utilizing a limited radio-frequency (RF) spectrum. Such a joint radar communications (JRC) model has advantages of low cost, compact size, less power consumption, spectrum sharing, improml performance, and safety due to enhanced information sharing. Today, millimeter-wave (mm-wave) communications have emerged as the preferred technology for short distance wireless links because they provide transmission bandwidth that is several gigahertz wide. This band is also promising for short-range radar applications, which benefit from the high-range resolution arising from large transmit signal bandwidths. Signal processing techniques are critical to the implementation of mm-wave JRC systems. Major challenges are joint waveform design and performance criteria that would optimally trade off between communications and radar functionalities. Novel multiple-input, multiple-output (MIMO) signal processing techniques are required because mm-wave JRC systems employ large antenna arrays. There are opportunities to exploit recent advances in cognition, compressed sensing, and machine learning to reduce required resources and dynamically allocate them with low overheads. This article provides a signal processing perspective of mm-wave JRC systems with an emphasis on waveform design.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-261328 (URN)10.1109/MSP.2019.2913173 (DOI)000485739200012 ()2-s2.0-85072215191 (Scopus ID)
Note

QC 20191007

Available from: 2019-10-07 Created: 2019-10-07 Last updated: 2019-10-07Bibliographically approved
He, S., Wang, J., Huang, Y., Ottersten, B. & Hong, W. (2017). Codebook-Based Hybrid Precoding for Millimeter Wave Multiuser Systems. IEEE Transactions on Signal Processing, 65(20), 5289-5304
Open this publication in new window or tab >>Codebook-Based Hybrid Precoding for Millimeter Wave Multiuser Systems
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2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 20, p. 5289-5304Article in journal (Refereed) Published
Abstract [en]

In millimeter-wave (mmWave) systems, antenna architecture limitations make it difficult to apply conventional fully digital precoding techniques but call for low-cost analog radio frequency (RF) and digital baseband hybrid precoding methods. This paper investigates joint RF-baseband hybrid precoding for the downlink of multiuser multiantenna mmWave systems with a limited number of RF chains. Two performance measures, maximizing the spectral efficiency and the energy efficiency of the system, are considered. We propose a codebook-based RF precoding design and obtain the channel state information via a beam sweep procedure. Via the codebook-based design, the original system is transformed into a virtual multiuser downlink system with the RF chain constraint. Consequently, we are able to simplify the complicated hybrid precoding optimization problems to joint codeword selection and precoder design (JWSPD) problems. Then, we propose efficient methods to address the JWSPD problems and jointly optimize the RF and baseband precoders under the two performance measures. Finally, extensive numerical results are provided to validate the effectiveness of the proposed hybrid precoders.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2017
Keywords
Hybrid precoding design, millimeter wave communication, energy efficient communication, successive convex approximation, power allocation
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-213755 (URN)10.1109/TSP.2017.2723353 (DOI)000407465900003 ()2-s2.0-85023200961 (Scopus ID)
Note

QC 20170920

Available from: 2017-09-20 Created: 2017-09-20 Last updated: 2018-09-19Bibliographically approved
Gharanjik, A., Shankar, M. R., Soltanalian, M. & Ottersten, B. (2017). Max-min transmit beamforming via iterative regularization. In: Conference Record - Asilomar Conference on Signals, Systems and Computers: . Paper presented at 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016, 6 November 2016 through 9 November 2016 (pp. 1437-1441). IEEE Computer Society
Open this publication in new window or tab >>Max-min transmit beamforming via iterative regularization
2017 (English)In: Conference Record - Asilomar Conference on Signals, Systems and Computers, IEEE Computer Society, 2017, p. 1437-1441Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces an iterative optimization framework to tackle the multi-group multicast Max-Min transmit beamforming problem. In each iteration, the optimization problem is decomposed into four sub-problems, all of which can be solved using computationally efficient algorithms. The advantage of proposed method lies in its ability to handle different types of signal constraints like total power and unimodularity; a feature not exhibited by other techniques. The proposed technique outperforms the well-known semidefinite relaxation method in terms of quality of solutions.

Place, publisher, year, edition, pages
IEEE Computer Society, 2017
Keywords
Beamforming, Optimization, Computationally efficient, Iterative Optimization, Iterative regularization, Optimization problems, Quality of solution, Semidefinite relaxation, Signal constraints, Transmit beamforming, Iterative methods
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-207984 (URN)10.1109/ACSSC.2016.7869614 (DOI)000406057400253 ()2-s2.0-85016242755 (Scopus ID)9781538639542 (ISBN)
Conference
50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016, 6 November 2016 through 9 November 2016
Note

QC 20170607

Available from: 2017-06-07 Created: 2017-06-07 Last updated: 2017-11-10Bibliographically approved
Gharanjik, A., Shankar, B., Soltanalian, M. & Ottersten, B. (2016). An iterative approach to nonconvex QCQP with applications in signal processing. In: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop: . Paper presented at 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016, 10 July 2016 through 13 July 2016. IEEE
Open this publication in new window or tab >>An iterative approach to nonconvex QCQP with applications in signal processing
2016 (English)In: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, IEEE, 2016Conference paper, Published paper (Refereed)
Abstract [en]

This paper introduces a new iterative approach to solve or to approximate the solutions of the nonconvex quadratically constrained quadratic programs (QCQP). First, this constrained problem is transformed to an unconstrained problem using a specialized penalty-based method. A tight upper-bound for the alternative unconstrained objective is introduced. Then an efficient minimization approach to the alternative unconstrained objective is proposed and further studied. The proposed approach involves power iterations and minimization of a convex scalar function in each iteration, which are computationally fast. The important design problem of multigroup multicast beamforming is formulated as a nonconvex QCQP and solved using the proposed method.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
Constraint theory, Iterative methods, Quadratic programming, Constrained problem, Design problems, Iterative approach, Multi-group, Quadratically-constrained quadratic programs, Scalar function, Unconstrained problems, Upper Bound, Signal processing
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-202884 (URN)10.1109/SAM.2016.7569622 (DOI)2-s2.0-84990829369 (Scopus ID)9781509021031 (ISBN)
Conference
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop, SAM 2016, 10 July 2016 through 13 July 2016
Note

QC 20170310

Available from: 2017-03-10 Created: 2017-03-10 Last updated: 2017-03-10Bibliographically approved
Naghsh, M. M., Soltanalian, M., Stoica, P., Masjedi, M. & Ottersten, B. (2016). Efficient Sum-Rate Maximization for Medium-Scale MIMO AF-Relay Networks. IEEE Transactions on Wireless Communications, 15(9), 6400-6411
Open this publication in new window or tab >>Efficient Sum-Rate Maximization for Medium-Scale MIMO AF-Relay Networks
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2016 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 9, p. 6400-6411Article in journal (Refereed) Published
Abstract [en]

We consider the problem of sum-rate maximization in multiple-input multiple-output (MIMO) amplify-and-forward relay networks with multi-operator. The aim is to design the MIMO relay amplification matrix (i.e., the relay beamformer) to maximize the achievable communication sum rate through the relay. The design problem for the case of single-antenna users can be cast as a non-convex optimization problem, which, in general, belongs to a class of NP-hard problems. We devise a method based on the minorization-maximization technique to obtain quality solutions to the problem. Each iteration of the proposed method consists of solving a strictly convex unconstrained quadratic program. This task can be done quite efficiently, such that the suggested algorithm can handle the beamformer design for relays with up to similar to 70 antennas within a few minutes on an ordinary personal computer. Such a performance lays the ground for the proposed method to be employed in medium-scale (or lower regime massive) MIMO scenarios.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keywords
Amplify and forward, beamforming, massive MIMO, medium-scale MIMO, minorization-maximization (majorization-minimization), relay networks, sum-rate
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-258999 (URN)10.1109/TWC.2016.2584039 (DOI)000384241400041 ()2-s2.0-84987896892 (Scopus ID)
Note

QC 20190916

Available from: 2019-09-11 Created: 2019-09-11 Last updated: 2019-09-16Bibliographically approved
He, S., Huang, Y., Yang, L., Ottersten, B. & Hong, W. (2015). Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition. IEEE Transactions on Communications, 63(12), 4920-4935
Open this publication in new window or tab >>Energy Efficient Coordinated Beamforming for Multicell System: Duality-Based Algorithm Design and Massive MIMO Transition
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2015 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 63, no 12, p. 4920-4935Article in journal (Refereed) Published
Abstract [en]

In this paper, we investigate joint beamforming and power allocation in multicell multiple-input single-output (MISO) downlink networks. Our goal is to maximize the utility function defined as the ratio between the system weighted sum rate and the total power consumption subject to the users' quality of service requirements and per-base-station (BS) power constraints. The considered problem is nonconvex and its objective is in a fractional form. To circumvent this problem, we first resort to an virtual uplink formulations of the the primal problem by introducing an auxiliary variable and applying the uplink-downlink duality theory. By exploiting the analytic structure of the optimal beamformers in the dual uplink problem, an efficient algorithm is then developed to solve the considered problem. Furthermore, to reduce further the exchange overhead between coordinated BSs in a large-scale antenna system, an effective coordinated power allocation solution only based on statistical channel state information is reached by deriving the asymptotic optimization problem, which is used to obtain the power allocation in a long-term timescale. Numerical results validate the effectiveness of our proposed schemes and show that both the spectral efficiency and the energy efficiency can be simultaneously improved over traditional downlink coordinated schemes, especially in the middle-high transmit power region.

Place, publisher, year, edition, pages
IEEE, 2015
Keywords
Coordinated energy-efficient transmission, uplink-downlink duality, massive multiple-input-single-output system, beamforming and power allocation
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-180995 (URN)10.1109/TCOMM.2015.2496948 (DOI)000366928600024 ()2-s2.0-84941620452 (Scopus ID)
Note

QC 20160127

Available from: 2016-01-27 Created: 2016-01-26 Last updated: 2020-03-10Bibliographically approved
Gharanjik, A., Shankar, B. M. R., Arapoglou, P.-D. & Ottersten, B. (2015). Multiple Gateway Transmit Diversity in Q/V Band Feeder Links. IEEE Transactions on Communications, 63(3), 916-926
Open this publication in new window or tab >>Multiple Gateway Transmit Diversity in Q/V Band Feeder Links
2015 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 63, no 3, p. 916-926Article in journal (Refereed) Published
Abstract [en]

Design of high bandwidth and reliable feeder links are central toward provisioning new services on the user link of a multibeam satellite communication system. Toward this, utilization of the Q/V band and an exploitation of multiple gateways (GWs) as a transmit diversity measure for overcoming severe propagation effects are being considered. In this context, this contribution deals with the design of a feeder link comprising N + P GWs (N active and P redundant GWs). Toward provisioning the desired availability, a novel switching scheme is analyzed and practical aspects such as prediction-based switching and switching rate are discussed. Unlike most relevant works, a dynamic rain attenuation model is used to analytically derive average outage probability in the fundamental 1 + 1 GW case. Building on this result, an analysis for the N + P scenario leading to a quantification of the end-to-end performance is provided. This analysis aids system sizing by illustrating the interplay between the number of active and redundant GWs on the chosen metrics: average outage and average switching rate.

National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-164469 (URN)10.1109/TCOMM.2014.2385703 (DOI)000351507600027 ()2-s2.0-84925071135 (Scopus ID)
Note

QC 20150422

Available from: 2015-04-22 Created: 2015-04-17 Last updated: 2017-12-04Bibliographically approved
Zenteno, E., Piazza, R., Shankar, M. R., Ronnow, D. & Ottersten, B. (2015). Multiple-input multiple-output symbol rate signal digital predistorter for non-linear multi-carrier satellite channels. IET Communications, 9(16), 2053-2059
Open this publication in new window or tab >>Multiple-input multiple-output symbol rate signal digital predistorter for non-linear multi-carrier satellite channels
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2015 (English)In: IET Communications, ISSN 1751-8628, E-ISSN 1751-8636, Vol. 9, no 16, p. 2053-2059Article in journal (Refereed) Published
Abstract [en]

A digital predistortion (DPD) scheme is presented for non-linear distortion mitigation in multi-carrier satellite communication channels. The proposed DPD has a multiple-input multiple-output architecture similar to data DPD schemes. However, it enhances the mitigation performance of data DPDs using a multi-rate processing algorithm to achieve spectrum broadening of non-linear operators. Compared to single carrier (single-input single-output) signal (waveform) DPD schemes, the proposed DPD has lower digital processing rate reducing the required hardware cost of the predistorter. The proposed DPD outperforms, in total degradation, both data and signal DPD schemes. Further, it performs closest to a channel bound described by an ideally mitigated channel with limited maximum output power.

Place, publisher, year, edition, pages
Institution of Engineering and Technology, 2015
Keywords
satellite communication, signal processing, MIMO communication, multiple-input multiple-output symbol rate signal digital predistorter, nonlinear multicarrier satellite communication channels, digital predistortion scheme, data DPD schemes, multirate processing algorithm
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-177938 (URN)10.1049/iet-com.2015.0176 (DOI)000364208600015 ()2-s2.0-84946706060 (Scopus ID)
Note

QC 20151203

Available from: 2015-12-03 Created: 2015-11-30 Last updated: 2019-09-12Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-2298-6774

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