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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 ()
Note

QC 20180524

Available from: 2018-05-24 Created: 2018-05-24 Last updated: 2018-05-24Bibliographically 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 ()
Note

QC 20170815

Available from: 2017-08-15 Created: 2017-08-15 Last updated: 2017-08-15Bibliographically 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
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
Brandt, R., Rami, M. & Bengtsson, M. (2016). Distributed Long-Term Base Station Clustering in Cellular Networks using Coalition Formation. IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 2(3)
Open this publication in new window or tab >>Distributed Long-Term Base Station Clustering in Cellular Networks using Coalition Formation
2016 (English)In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, ISSN 2373-776X, Vol. 2, no 3Article in journal (Refereed) Published
Abstract [en]

Interference alignment (IA) is a promising technique for interference mitigation in multicell networks due to its ability to completely cancel the intercell interference through linear precoding and receive filtering. In small networks, the amount of required channel state information (CSI) is modest and IA is therefore typically applied jointly over all base stations. In large networks, where the channel coherence time is short in comparison to the time needed to obtain the required CSI, base station clustering must be applied however. We model such clustered multicell networks as a set of coalitions, where CSI acquisition and IA precoding is performed independently within each coalition. We develop a long-term throughput model which includes both CSI acquisition overhead and the level of interference mitigation ability as a function of the coalition structure. Given the throughput model, we formulate a coalitional game where the involved base stations are the rational players. Allowing for individual deviations by the players, we formulate a distributed coalition formation algorithm with low complexity and low communication overhead that leads to an individually stable coalition structure. The dynamic clustering is performed using only long-term CSI, but we also provide a robust short-term precoding algorithm which accounts for the intercoalition interference when spectrum sharing is applied between coalitions. Numerical simulations show that the distributed coalition formation is generally able to reach long-term sum throughputs within 10 % of the global optimum.

Place, publisher, year, edition, pages
IEEE, 2016
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-184178 (URN)10.1109/TSIPN.2016.2548781 (DOI)000384248200010 ()
Note

QC 20161021

Available from: 2016-03-30 Created: 2016-03-30 Last updated: 2016-10-21Bibliographically approved
Brandt, R., Rami, M. & Bengtsson, M. (2016). Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks. IEEE Signal Processing Letters, 23(4), 512-516
Open this publication in new window or tab >>Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks
2016 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 23, no 4, p. 512-516Article in journal (Refereed) Published
Abstract [en]

Coordinated precoding based on interference alignment is a promising technique for improving the throughputs in future wireless multicell networks. In small networks, all base stations can typically jointly coordinate their precoding. In large networks however, base station clustering is necessary due to the otherwise overwhelmingly high channel state information (CSI) acquisition overhead. In this work, we provide a branch and bound algorithm for finding the globally optimal base station clustering. The algorithm is mainly intended for benchmarking existing suboptimal clustering schemes. We propose a general model for the user throughputs, which only depends on the long-term CSI statistics. The model assumes intracluster interference alignment and is able to account for the CSI acquisition overhead. By enumerating a search tree using a best-first search and pruning sub-trees in which the optimal solution provably cannot be, the proposed method converges to the optimal solution. The pruning is done using specifically derived bounds, which exploit some assumed structure in the throughput model. It is empirically shown that the proposed method has an average complexity which is orders of magnitude lower than that of exhaustive search.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
Base station clustering, branch and bound, interference alignment
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-184176 (URN)10.1109/LSP.2016.2536159 (DOI)000373023600002 ()2-s2.0-84964389846 (Scopus ID)
Note

QC 20160405

Available from: 2016-03-30 Created: 2016-03-30 Last updated: 2017-11-30Bibliographically approved
Ghauch, H., Kim, T., Bengtsson, M. & Skoglund, M. (2016). Subspace Estimation and Decomposition for Large Millimeter-Wave MIMO Systems. IEEE Journal on Selected Topics in Signal Processing, 10(3), 528-542
Open this publication in new window or tab >>Subspace Estimation and Decomposition for Large Millimeter-Wave MIMO Systems
2016 (English)In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 10, no 3, p. 528-542Article in journal (Refereed) Published
Abstract [en]

Channel estimation and precoding in hybrid analog-digital millimeter-wave (mmWave) MIMO systems is a fundamental problem that has yet to be addressed, before any of the promised gains can be harnessed. For that matter, we propose a method (based on the well-known Arnoldi iteration) exploiting channel reciprocity in TDD systems and the sparsity of the channel's eigenmodes, to estimate the right (resp. left) singular subspaces of the channel, at the BS (resp. MS). We first describe the algorithm in the context of conventional MIMO systems, and derive bounds on the estimation error in the presence of distortions at both BS and MS. We later identify obstacles that hinder the application of such an algorithm to the hybrid analog-digital architecture, and address them individually. In view of fulfilling the constraints imposed by the hybrid analog-digital architecture, we further propose an iterative algorithm for subspace decomposition, whereby the above estimated subspaces, are approximated by a cascade of analog and digital precoder/combiner. Finally, we evaluate the performance of our scheme against the perfect CSI, fully digital case (i.e., an equivalent conventional MIMO system), and conclude that similar performance can be achieved, especially at medium-to-high SNR (where the performance gap is less than 5%), however, with a drastically lower number of RF chains (similar to 4 to 8 times less).

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keywords
Millimeter wave MIMO systems, sparse channel estimation, hybrid architecture, hybrid precoding, subspace decomposition, Arnoldi iteration, subspace estimation, echo-based channel estimation
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-187827 (URN)10.1109/JSTSP.2016.2538178 (DOI)000375114900008 ()2-s2.0-84964975000 (Scopus ID)
Note

QC 20160531

Available from: 2016-05-31 Created: 2016-05-30 Last updated: 2017-11-30Bibliographically approved
Kim, S. M. & Bengtsson, M. (2016). Virtual Full-Duplex Buffer-Aided Relaying in the Presence of Inter-Relay Interference. IEEE Transactions on Wireless Communications, 15(4), 2966-2980
Open this publication in new window or tab >>Virtual Full-Duplex Buffer-Aided Relaying in the Presence of Inter-Relay Interference
2016 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 4, p. 2966-2980Article in journal (Refereed) Published
Abstract [en]

In this paper, we study virtual full-duplex (FD) buffer-aided relaying to recover the loss of multiplexing gain caused by half-duplex (HD) relaying in a multiple relay network, where each relay is equipped with a buffer and multiple antennas, through joint opportunistic relay selection (RS) and beamforming (BF) design. The main idea behind virtual FD buffer-aided relaying is that the source and one of the relays simultaneously transmit their own information to another relay and the destination, respectively. In such networks, interrelay interference (IRI) is a crucial problem, which has to be resolved like self-interference in the FD relaying. In contrast to previous work that neglected IRI, we propose joint RS and BF schemes taking IRI into consideration by using multiple antennas at the relays. To maximize average end-to-end rate, we propose a weighted sum-rate maximization strategy assuming that adaptive rate transmission is employed in both the source to relay and relay to destination links. Then, we propose several BF schemes cancelling or suppressing IRI in order to maximize the weighted sum-rate. Numerical results show that our proposed optimal, zero-forcing, and minimum mean square error BF-based RS schemes asymptotically approach the ideal FD relaying upper bound when increasing the number of antennas and/or the number of relays.

Place, publisher, year, edition, pages
IEEE, 2016
Keywords
Full-duplex, buffer-aided relaying, inter-relay interference, relay selection, beamforming
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-186561 (URN)10.1109/TWC.2015.2514103 (DOI)000374240500040 ()2-s2.0-84963800686 (Scopus ID)
Note

QC 20160513

Available from: 2016-05-13 Created: 2016-05-13 Last updated: 2017-11-30Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-3599-5584

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