| 1. |
- Bertilsson, Erik, 1990-, et al.
(författare)
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Computation Limited Matrix Inversion Using Neumann Series Expansion for Massive MIMO
- 2017
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Ingår i: 2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS. - 9781538618233 ; , s. 466-469
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Konferensbidrag (refereegranskat)abstract
- Neumann series expansion is a method for performing matrix inversion that has received a lot of interest in the context of massive MIMO systems. However, the computational complexity of the Neumann methods is higher than for the lowest complexity exact matrix inversion algorithms, such as LDL, when the number of terms in the series is three or more. In this paper, the Neumann series expansion is analyzed from a computational perspective for cases when the complexity of performing exact matrix inversion is too high. By partially computing the third term of the Neumann series, the computational complexity can be reduced. Three different preconditioning matrices are considered. Simulation results show that when limiting the total number of operations performed, the BER performance of the tree different preconditioning matrices is the same.
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| 2. |
- Cavarec, Baptiste, et al.
(författare)
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Pulse Design for Spectrally efficient Transmissions assuming Maximum Likelihood Detection
- 2017
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Ingår i: 2017 Fifty-First Asilomar Conference on Signals, Systems, And Computers. - : IEEE Computer Society. - 9781538618233 ; , s. 1754-1758
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
- Elvander, Filip, et al.
(författare)
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Grid-less estimation of saturated signals
- 2017
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Ingår i: 2017 51st Asilomar Conference on Signals, Systems, and Computers. - 9781538618233 ; , s. 372-376
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Konferensbidrag (refereegranskat)abstract
- This work proposes a frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples.
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| 4. |
- Jacobsson, Sven, 1990, et al.
(författare)
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On Out-of-Band Emissions of Quantized Precoding in Massive MU-MIMO-OFDM
- 2017
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Ingår i: Conference Record of the Asilomar Conference on Signals Systems and Computers. - 1058-6393. - 9781538618233 ; 2017-October, s. 21-26
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Konferensbidrag (refereegranskat)abstract
- We analyze out-of-band (OOB) emissions in the massive multi-user (MU) multiple-input multiple-output (MIMO) downlink. We focus on systems in which the base station (BS) is equipped with low-resolution digital-to-analog converters (DACs) and orthogonal frequency-division multiplexing (OFDM) is used to communicate to the user equipments (UEs) over frequency- selective channels. We demonstrate that analog filtering in combination with simple frequency-domain digital predistortion (DPD) at the BS enables a significant reduction of OOB emissions, but degrades the signal-to-interference-noise-and-distortion ratio (SINDR) at the UEs and increases the peak-to-average power ratio (PAR) at the BS. We use Bussgang’s theorem to characterize the tradeoffs between OOB emissions, SINDR, and PAR, and to study the impact of analog filters and DPD on the error-rate perfor- mance of the massive MU-MIMO-OFDM downlink. Our results show that by carefully tuning the parameters of the analog filters, one can achieve a significant reduction in OOB emissions with only a moderate degradation of error-rate performance and PAR.
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| 5. |
- Kovalev, Anton, et al.
(författare)
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Implementation approaches for 512-tap 60 GSa/s chromatic dispersion FIR filters
- 2017
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Ingår i: Conference Record of The Fifty-First Asilomar Conference on Signals, Systems & Computers. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538618233 - 9781538606667 - 9781538618240 ; , s. 1779-1783
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Konferensbidrag (refereegranskat)abstract
- In optical communication the non-ideal properties of the fibers lead to pulse widening from chromatic dispersion. One way to compensate for this is through digital signal processing. In this work, two architectures for compensation are compared. Both are designed for 60 GSa/s and 512 filter taps and implemented in the frequency domain using FFTs. It is shown that the high-speed requirements introduce constraints on possible architectural choices. Furthermore, the theoretical multiplication complexity estimates are not good predictors for the energy consumption. The results show that the implementation with 10% more multiplications per sample has half the power consumption and one third of the area consumption. The best architecture for this specification results in a power consumption of 3.12 W in a 65 nm technology, corresponding to an energy per complex filter tap of 0.10 mW/GHz.
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| 6. |
- Kronvall, Ted, et al.
(författare)
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Hyperparameter-selection for sparse regression : A probablistic approach
- 2018
-
Ingår i: Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. - 9781538618233 ; 2017-October, s. 853-857
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Konferensbidrag (refereegranskat)abstract
- The choice of hyperparameter(s) notably affects the support recovery in LASSO-like sparse regression problems, acting as an implicit model order selection. Parameters are typically selected using cross-validation or various ad hoc approaches. These often overestimates the resulting model order, aiming to minimize the prediction error rather than maximizing the support recovery. In this work, we propose a probabilistic approach to selecting hyperparameters in order to maximize the support recovery, quantifying the type I error (false positive rate) using extreme value analysis, such that the regularization level is selected as an appropriate quantile. By instead solving the scaled LASSO problem, the proposed choice of hyperparameter becomes almost independent of the noise variance. Simulation examples illustrate how the proposed method outperforms both cross-validation and the Bayesian Information Criterion in terms of computational complexity and support recovery.
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| 7. |
- Malkowsky, Steffen, et al.
(författare)
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Building and operating a real-time massive MIMO testbed - Lessons learned
- 2018
-
Ingår i: Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. - 9781538618233 ; 2017-October, s. 603-607
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Konferensbidrag (refereegranskat)abstract
- Massive multiple-input multiple-output (MIMO) is one of the key candidates for the upcoming 5G wireless generation. It offers a multitude of advantages over traditional techniques, such as reduced latency, reduced interference among user equipments (UEs) and increased spectrum and energy efficiencies. However, to verify the theoretically promised gains in real-life, prototype systems are inevitable. This paper discusses the many experiences gathered during designing, building and operating the Lund University Massive MIMO (LuMaMi) testbed. We discuss the six main lessons learned including practical issues, such as the mechanical setup or driver issues but also implementation challenges, such as increasing operation count compared to traditional wireless systems, complicated data shuffling and low-processing latency and detail their specific requirements.
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| 8. |
- Mollén, Christopher, et al.
(författare)
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Analysis of nonlinear low-noise amplifiers in massive MIMO base stations
- 2017
-
Ingår i: 2017 51st Asilomar Conference on Signals, Systems, and Computers. - 1058-6393. - 9781538618233 - 9781538618240 ; , s. 285-289
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Konferensbidrag (refereegranskat)abstract
- Because of the large number of antennas at the base station, the power consumption and cost of the low-noise amplifiers (LNAs) can be substantial. Therefore, we investigate the feasibility of inexpensive, power efficient LNAs, which inherently are less linear. To characterize the nonlinear distortion, we describe the LNAs using a polynomial model, which allows for the derivation of the second-order statistics of the received signal and the distortion. A massive MIMO system that serves one user in line-of-sight is studied. It is shown that the distortion from the LNAs combines coherently and that the SINR of the symbol estimates therefore is limited by the linearity of the LNAs. Furthermore, the impact of a strong transmitter in the adjacent frequency band is investigated. The second-order statistics show how the power from that transmission leaks into the main band and interferes with the symbol estimates.
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| 9. |
- Swärd, Johan, et al.
(författare)
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Designing optimal sampling schemes for multi-dimensional data
- 2017
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Ingår i: 2017 51st Asilomar Conference on Signals, Systems, and Computers. - 9781538618233 ; , s. 850-852
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Konferensbidrag (refereegranskat)abstract
- In this work, we propose a method for determining an optimal, non-uniform, sampling scheme for multi-dimensional signals by solving a convex optimization problem reminiscent of the sensor selection problem. The optimal sampling scheme is determined given a suitable estimation bound on the parameters of interest, as well as incorporating any imprecise a priori knowledge of the locations of the parameters. Numerical examples illustrate the efficiency of the proposed scheme.
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| 10. |
- Verenzuela, Daniel, 1988-, et al.
(författare)
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Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO
- 2017
-
Ingår i: Conference Record of The Fifty-FirstAsilomar Conference on Signals, Systems & Computers. - : IEEE conference proceedings. - 9781538618233 - 9781538606667 - 9781538618240 ; , s. 27-31
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Konferensbidrag (refereegranskat)abstract
- Massive multiple-input multiple-output (MIMO) is a key technology for next generation wireless networks that deploys many antennas at the base stations (BSs). This requires low-complexity hardware at each antenna branch that, in turn, increases distortions. This work studies the selection of per-antenna hardware quality in terms of analog-to-digital converters (ADCs) resolution. A new achievable spectral efficiency (SE) expression is derived and majorization theory is used to analyze the order preserving properties of the SE and the power consumption with respect to the per-antenna ADC resolutions. That is, given a fixed sum of ADC resolutions across the antenna array, is it preferable to use an equal-ADC over a mixed-ADC approach? The results show that having equal-resolution ADCs across the antenna array maximizes the SE and minimizes the power consumption.
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| 11. |
- Wu, Hanwei, et al.
(författare)
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Transform-based compression for quadratic similarity queries
- 2018
-
Ingår i: Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781538618233 ; , s. 377-381
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Konferensbidrag (refereegranskat)abstract
- This paper considers the problem of compression for similarity queries [1] and discusses transform-based compression schemes. Here, the focus is on the tradeoff between the rate of the compressed data and the reliability of the answers to a given query. We consider compression schemes that do not allow false negatives when answering queries. Hence, classical compression techniques need to be modified. We propose transform-based compression schemes which decorrelate original data and regard each transform component as a distinct D-admissible system. Both compression and retrieval will be performed in the transform domain. The transform-based schemes show advantages in terms of encoding speed and the ability of handling high-dimensional correlated data. In particular, we discuss component-based and vector-based schemes. We use P{maybe}, a probability that is related to the occurrence of false positives to assess our scheme. Our experiments show that component-based schemes offer both good performance and low search complexity.
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