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Björsell, J., Sternad, M. & Grieger, M. (2022). A Framework for Predictor Antennas in Practice. IEEE Transactions on Vehicular Technology, 71(7), 7503-7518
Open this publication in new window or tab >>A Framework for Predictor Antennas in Practice
2022 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 71, no 7, p. 7503-7518Article in journal (Refereed) Published
Abstract [en]

Channel predictions are important to achieve high spectral efficiency for high-mobility vehicles. Channel extrapolation, used by many prediction methods, suffers from a limited prediction horizon in difficult radio environments. The predictor antenna (PA) concept provides the prediction horizons required for efficient transmission to fast-moving vehicles by measuring the channel ahead of time with an extra antenna placed on the vehicle. This paper presents a general framework that addresses the practical signal processing challenges of the PA concept. It is adaptable to a vast variety of vehicular deployment, mobility, and communication scenarios. A new theoretical prediction normalized mean-squared error (NMSE) expression is derived based on the presented framework. The framework is demonstrated by applying it to extensive channel measurements and comparing the PA predictions to Kalman-based channel predictions and outdated channel estimates. By studying the impact of vehicular velocity and radio environment on the prediction performance, it is shown that PA prediction is weaker at low velocities, where Kalman prediction methods are sufficient, but is uncontested at high velocities in environments without a dominating path. At high velocities in dominating path environments, the Kalman predictor provides usable predictions, but it is still outperformed by the PA predictions. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
Channel state information (CSI), High-mobility, Predictor antenna
National Category
Telecommunications Signal Processing
Research subject
Electrical Engineering with specialization in Signal Processing
Identifiers
urn:nbn:se:uu:diva-470620 (URN)10.1109/TVT.2022.3168225 (DOI)000876768200052 ()
Available from: 2022-03-27 Created: 2022-03-27 Last updated: 2022-11-25Bibliographically approved
Björsell, J., Sternad, M. & Phan-Huy, D.-T. (2022). Enabling Multi-User M-MIMO for High-Mobility Users with Predictor Antennas: A Deep Analysis Based on Experimental NLOS Measurements. IEEE Transactions on Vehicular Technology, 71(7), 7456-7471
Open this publication in new window or tab >>Enabling Multi-User M-MIMO for High-Mobility Users with Predictor Antennas: A Deep Analysis Based on Experimental NLOS Measurements
2022 (English)In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 71, no 7, p. 7456-7471Article in journal (Refereed) Published
Abstract [en]

Predictor antenna channel measurements from a 64-antenna base station are used to investigate the effects of channel aging on the precoder design for high-mobility users in a non-line-of-sight (NLOS) massive multiple-input multiple-output (M-MIMO) environment. The effects are evaluated in terms of received downlink (DL) signal-to-interference-and-noise ratio (SINR) and the corresponding ergodic capacity bound. A simulated velocity of 150 km/h is used with a carrier frequency of 2.18 GHz. Maximum ratio (MR) and a codebook-based precoders are used to evaluate single-user transmission and zero-forcing (ZF), regularized zero-forcing (RZF), and minimum mean-squared error (MMSE) precoders are used to evaluate multi-user transmission with up to nine active users in a cell. Furthermore, predictor antenna predictions are evaluated as a mean of combating channel aging. It is also investigated how the predictor antenna can be used during data reception. Simulations show that outdated channel estimates significantly reduce the SINR and consequently the capacity for all investigated transmission techniques. Basic predictor antenna predictions outperform the use of outdated channel estimates for delays larger than 0.6 ms. In single-user transmission, channel prediction can improve the capacity by 6–14%. The gain from multi-user transmission typically disappears when using outdated channel estimates older than 1 ms. In contrast, the use of predictor antennas enables multi-user MIMO for these high-mobility users, which is demonstrated to increase the capacity bound by 100% compared to 1 ms old channel estimates. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
Channel prediction, High-mobility, M-MIMO, Outdated channel state information (CSI), Predictor antenna
National Category
Telecommunications Signal Processing
Research subject
Electrical Engineering with specialization in Signal Processing
Identifiers
urn:nbn:se:uu:diva-470622 (URN)10.1109/TVT.2022.3167630 (DOI)000876768200049 ()
Funder
Uppsala University
Available from: 2022-03-27 Created: 2022-03-27 Last updated: 2022-11-24Bibliographically approved
Gunnarsson, V. & Sternad, M. (2021). Binaural Auralization of Microphone Array Room Impulse Responses Using Causal Wiener Filtering. IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 29, 2899-2914
Open this publication in new window or tab >>Binaural Auralization of Microphone Array Room Impulse Responses Using Causal Wiener Filtering
2021 (English)In: IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, ISSN 2329-9290, Vol. 29, p. 2899-2914Article in journal (Refereed) Published
Abstract [en]

Binaural room auralization involves Binaural Room Impulse Responses (BRIRs). Dynamic binaural synthesis (i.e., head-tracked presentation) requires BRIRs for multiple head poses. Artificial heads can be used to measure BRIRs, but BRIR modeling from microphone array room impulse responses (RIRs) is becoming popular since personalized BRIRs can be obtained for any head pose with low extra effort. We present a novel framework for estimating a binaural signal from microphone array signals, using causal Wiener filtering and polynomial matrix formalism. The formulation places no explicit constraints on the geometry of the microphone array and enables directional weighting of the estimation error. A microphone noise model is used for regularization and to balance filter performance and noise gain. A complete procedure for BRIR modeling from microphone array RIRs is also presented, employing the proposed Wiener filtering framework. An application example illustrates the modeling procedure using a 19-channel spherical microphone array. Direct and reflected sound segments are modeled separately. The modeled BRIRs are compared to measured BRIRs and are shown to be waveform-accurate up to at least 1.5 kHz. At higher frequencies, correct statistical properties of diffuse sound field components are aimed for. A listening test indicates small perceptual differences to measured BRIRs. The presented method facilitates fast BRIR data set acquisition for use in dynamic binaural synthesis and is a viable alternative to Ambisonics-based binaural room auralization.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE)Institute of Electrical and Electronics Engineers (IEEE), 2021
Keywords
Microphone arrays, Estimation, Ear, Speech processing, Acoustics, Array signal processing, Magnetic heads, Beamforming, binaural recording, binaural room impulse response (BRIR), head-related transfer function (HRTF), interaural coherence, MIMO, virtual acoustic environment, virtual artificial head (VAH)
National Category
Signal Processing Fluid Mechanics and Acoustics
Identifiers
urn:nbn:se:uu:diva-456921 (URN)10.1109/TASLP.2021.3110340 (DOI)000697817100002 ()
Funder
Vinnova
Available from: 2021-10-25 Created: 2021-10-25 Last updated: 2024-01-15Bibliographically approved
Phan-Huy, D.-T., Björsell, J. & Sternad, M. (2021). Predictor Antenna for Robust Non Reciprocity based Beamforming at High Speed. In: : . Paper presented at 25th International ITG Workshop on Smart Antennas, WSA 2021, 10 – 12 November 2021, EURECOM, French Riviera.
Open this publication in new window or tab >>Predictor Antenna for Robust Non Reciprocity based Beamforming at High Speed
2021 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we show for the first time, based on channels from real urban environments, that although non reciprocity based beamformers (such as Discrete Fourier Transform beamforming) are more robust to high velocity than reciprocity based beamformers (such as maximum ratio transmission), they can still benefit from predictor antenna based channel prediction, in non line-of-sight propagation environments, due to the impact of small-scale fading within beams. The evaluation was conducted with channels from a massive multiple input multiple output antenna with 64 elements. 

National Category
Telecommunications Signal Processing
Research subject
Electrical Engineering with specialization in Signal Processing
Identifiers
urn:nbn:se:uu:diva-470508 (URN)978-3-8007-5686-5 (ISBN)
Conference
25th International ITG Workshop on Smart Antennas, WSA 2021, 10 – 12 November 2021, EURECOM, French Riviera
Available from: 2022-03-25 Created: 2022-03-25 Last updated: 2022-03-28Bibliographically approved
Zirwas, W. & Sternad, M. (2020). Profiling of mobile radio channels. In: ICC 2020: 2020 IEEE International Conference on Communications (ICC). Paper presented at 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 7-11 June (held virtually as on-line conference).
Open this publication in new window or tab >>Profiling of mobile radio channels
2020 (English)In: ICC 2020: 2020 IEEE International Conference on Communications (ICC), 2020Conference paper, Published paper (Refereed)
Abstract [en]

One of the essential challenges for MIMO or massive MIMO and cooperative multipoint systems is obtaining accurate channel state information (CSI) at the base station side, as the related closed loop MIMO precoders are sensitive to channel aging effects. For that reason, channel prediction is often seen as one of the main enablers to maintain a large part of the performance gains achievable with ideal CSI. It has been claimed that Kalman filtering provides an upper bound for channel prediction performance. In line with this, for real world radio channels alternative channel prediction methods based on parameter estimation achieved comparably worse prediction results. Here, we propose a so called profiling solution as a novel parameter estimation method, which promises to improve the prediction horizon by a factor of two to three compared to Kalman filtering based on autoregressive models. This is indicated by first evaluations based on a real world radio channel measurement in the NOKIA campus in Munich.

Series
IEEE International Conference on Communications, ISSN 1550-3607, E-ISSN 1938-1883
National Category
Signal Processing
Identifiers
urn:nbn:se:uu:diva-421337 (URN)10.1109/ICC40277.2020.9148839 (DOI)000606970301078 ()978-1-7281-5089-5 (ISBN)978-1-7281-5090-1 (ISBN)
Conference
2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 7-11 June (held virtually as on-line conference)
Available from: 2020-10-08 Created: 2020-10-08 Last updated: 2021-03-10Bibliographically approved
Apelfröjd, R., Zirwas, W. & Sternad, M. (2019). Low-Overhead Cyclic Reference Signals for Channel Estimation in FDD Massive MIMO. IEEE Transactions on Communications, 67(5), 3279-3291
Open this publication in new window or tab >>Low-Overhead Cyclic Reference Signals for Channel Estimation in FDD Massive MIMO
2019 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 5, p. 3279-3291Article in journal (Refereed) Published
Abstract [en]

Massive multiple input multiple output (MIMO) transmission and coordinated multipoint transmission are candidate technologies for increasing data throughput in evolving 5G standards. Frequency division duplex (FDD) is likely to remain predominant in large parts of the spectrum below 6 GHz for future 5G systems. Therefore, it is important to estimate the downlink FDD channels from a very large number of antennas, while avoiding an excessive downlink reference signal overhead. We here propose and investigate a three part solution. First, massive MIMO downlinks use a fixed grid of beams. For each user, only a subset of beams will then be relevant, and require estimation. Second, sets of coded reference signal sequences, with cyclic patterns over time, are used. Third, each terminal estimates its most relevant channels. We here propose and compare a linear mean square estimation and a Kalman estimation. Both utilize frequency and antenna correlation, and the later also utilizes temporal correlation. In extensive simulations, this scheme provides channel estimates that lead to an insignificant beamforming performance degradation as compared to full channel knowledge. The cyclic pattern of coded reference signals is found to be important for reliable channel estimation, without having to adjust the reference signals to specific users.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
Keywords
Radio channel estimation, frequency division duplex, antenna arrays
National Category
Signal Processing Telecommunications Communication Systems
Identifiers
urn:nbn:se:uu:diva-386180 (URN)10.1109/TCOMM.2019.2895059 (DOI)000468228900014 ()
Available from: 2019-06-19 Created: 2019-06-19 Last updated: 2019-06-19Bibliographically approved
Phan Huy, D.-T., Wesemann, S., Björsell, J. & Sternad, M. (2018). Adaptive massive MIMO for fast moving connected vehicles: It will work with predictor antennas!. In: : . Paper presented at 22nd International ITG Workshop on Smart Antennas (WSA 2018), Bochum, Tyskland.
Open this publication in new window or tab >>Adaptive massive MIMO for fast moving connected vehicles: It will work with predictor antennas!
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Predicting the channel between a massive multiple input multiple output antenna and a car is a challenge, due to the short-term fading. It becomes essentially impossible by conventional extrapolation from past estimates if the car has moved by half a wavelength or more in space at the time when the channel estimate will be needed. This problem would prevent us from using the best fifth generation adaptive antenna downlink precoding schemes for very fast moving connected vehicles. A potential solution is to add another vehicle antenna, a "predictor antenna", which senses the channel in advance. In this paper, based on drive tests and channel measurements from a 64- element antenna to a car, we for the first time show that this concept works for massive MIMO downlinks. Thanks to the use of a predictor antenna, the complex OFDM downlink channels can be predicted with an accuracy that enables maximum ratio transmit beamforming with close to ideal beamforming gain for non-line-of-sight channels. Zero forcing transmission to two users results in a signal-to-interference ratio of 20 dB to 30 dB when predicting non-line-of-sight channels up to three wavelengths ahead in space. These first experiment shows that the predictor antenna concept is a potential solution to make fifth generation adaptive antennas work for very fast moving connected vehicles.

National Category
Signal Processing
Identifiers
urn:nbn:se:uu:diva-363241 (URN)
Conference
22nd International ITG Workshop on Smart Antennas (WSA 2018), Bochum, Tyskland
Available from: 2018-10-15 Created: 2018-10-15 Last updated: 2019-01-03Bibliographically approved
Apelfröjd, R., Björsell, J., Sternad, M. & Phan Huy, D. T. (2018). Kalman Smoothing for Irregular Pilot Patterns: A Case Study for Predictor Antennas in TDD Systems. In: 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC): . Paper presented at 29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC'18), SEP 09-12, 2018, Bologna, Italy. IEEE
Open this publication in new window or tab >>Kalman Smoothing for Irregular Pilot Patterns: A Case Study for Predictor Antennas in TDD Systems
2018 (English)In: 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

For future large-scale multi-antenna systems, channel orthogonal downlink pilots are not feasible due to extensive overhead requirements. Instead, channel reciprocity can be utilized in time division duplex (TDD) systems so that the downlink channel estimates can be based on pilots transmitted during the uplink. User mobility affects the reciprocity and makes the channel state information outdated for high velocities and/or long downlink subframe durations. Channel extrapolation, e.g. through Kalman prediction, can reduce the problem but is also limited by high velocities and long downlink subframes. An alternative solution has been proposed where channel predictions are made with the help of an extra antenna, e.g. on the roof of a car, so called predictor antenna, with the primary objective to measure the channel at a position that is later encountered by the rearward antenna(s). The predictor antenna is not directly limited by high velocities and allows the channel in the downlinks to be interpolated rather than extrapolated. One remaining challenge here is to obtain a good interpolation of the uplink channel estimate, since a sequence of uplink reference signals (pilots) will be interrupted by downlink subframes. We here evaluate a Kalman smoothing estimate of the downlink channels and compare it to a cubic spline interpolation. These results are also compared to results where uplink channels are estimated through Kalman filters and predictors. Results are based on measured channels and show that with Kalman smoothing, predictor antennas can enable accurate channel estimates for a longer downlink period at vehicular velocities. The gaps in the uplink pilot stream, due to downlink subframes, can have durations that correspond to a vehicle movement of up to 0.75 carrier wavelengths in space, for Rayleigh-like non-line-of-sight fading.

Place, publisher, year, edition, pages
IEEE, 2018
National Category
Telecommunications
Identifiers
urn:nbn:se:uu:diva-344267 (URN)10.1109/PIMRC.2018.8581030 (DOI)000457761900206 ()978-1-5386-6009-6 (ISBN)
Conference
29th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC'18), SEP 09-12, 2018, Bologna, Italy
Note

Received a PIMRC2018 Best Paper Award

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2020-05-18Bibliographically approved
Zirwas, W., Sternad, M. & Apelfröjd, R. (2017). Key solutions for a massive MIMO FDD system. In: 2017 IEEE 28TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC): . Paper presented at IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), OCT 08-13, 2017, Montreal, Kanada. IEEE
Open this publication in new window or tab >>Key solutions for a massive MIMO FDD system
2017 (English)In: 2017 IEEE 28TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC), IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]

The ongoing standardization within 3GPP for the so called new radio (NR) system has identified massive multiple-input multiple output (MIMO) transmission, also called full dimension MIMO, as one of the main contributors to higher spectral efficiency for the mobile broadband case. In particular for radio frequencies below 6 GHz, channel estimation has to be supported in frequency division duplex (FDD) as well as time division duplex (TDD) operation. In TDD we may obtain downlink channels by estimating uplink channels, assuming reciprocity. For FDD, codebook based design as well as some type of explicit feedback is under discussion. Separately, there are also ongoing discussions of the question if massive MIMO in combination with FDD is a reasonable choice at all. Here we highlight some of our recent results obtained within several 5G research projects. To our understanding they overcome some of the inherent limitations of massive MIMO for FDD. As indicated by simulations, the resulting concept enables a grid of beam (GoB) and reference signal design with a reasonable downlink reference signal overhead of around 10 percent, together with reasonable feedback overhead of several hundred kbit/s per UE. Such a design attains around 90 percent of the massive MIMO system performance with ideal channel state information.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Signal Processing
Identifiers
urn:nbn:se:uu:diva-330698 (URN)10.1109/PIMRC.2017.8292395 (DOI)000426970901083 ()978-1-5386-3531-5 (ISBN)
Conference
IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), OCT 08-13, 2017, Montreal, Kanada
Funder
EU, European Research Council, ICT-671660
Available from: 2017-10-03 Created: 2017-10-03 Last updated: 2018-08-09Bibliographically approved
Björsell, J., Sternad, M. & Grieger, M. (2017). Predictor antennas in action. In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC): . Paper presented at IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 8-13 Oct. 2017, Montreal, Kanada. IEEE
Open this publication in new window or tab >>Predictor antennas in action
2017 (English)In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]

Connected vehicles in large numbers will be expensive in terms of power and bandwidth unless advanced transmit schemes are employed. These would rely on channel state information at transmitter (CSIT), which rapidly becomes outdated for fading vehicular channels. We here evaluate the predictor antenna concept, that solves this problem by using antennas on the outside of vehicles, with one extra antenna in front of the others. Its estimated channel is a scaled prediction for the channels encountered by rearward antennas when they reach that position. We evaluate this concept on a large set of channel sounding measurements from an urban environment. Recent investigations of the correlations of these measurements indicate that the average normalized mean squared errors (NMSEs) of the complex valued channel predictions should be around -10 dB for prediction horizons in space of up to 3 wavelengths. This represents an extension of the attainable prediction horizon by an order of magnitude, as compared to Kalman or Wiener extrapolation of past channel measurements. It represents an accuracy that would enable e.g. accurate massive multiple input multiple output (MIMO) downlink beamforming to vehicles. We here perform predictions on a subset of the measurements with good channel-to-estimation error power ratio (SNR). The approximate true channels are here available and we evaluate the performance on a validation data set. The results confirm that the distribution of the NMSE, over all investigated propagation environments, is close to that obtained by correlation-based models and outperforms the use of outdated channel measurements.

Place, publisher, year, edition, pages
IEEE, 2017
National Category
Signal Processing
Identifiers
urn:nbn:se:uu:diva-330699 (URN)10.1109/PIMRC.2017.8292235 (DOI)000426970900072 ()978-1-5386-3531-5 (ISBN)
Conference
IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 8-13 Oct. 2017, Montreal, Kanada
Available from: 2017-10-03 Created: 2017-10-03 Last updated: 2018-08-10Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0003-0981-2665

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