Coding the Beams: Improving Beamforming Training in mmWave Communication System

Tsang, Y. Ming; Poon, Ada S. Y.; Addepalli, Sateesh

doi:10.1109/glocom.2011.6134486

Cited by 163 publications

(128 citation statements)

References 11 publications

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“…Among these challenges, the severe path loss at those high carrier frequencies stands out. The resulting loss in signal-to-noise ratio (SNR) must be countered through sophisticated beamforming at the transmitter and/or receiver side, leading to highly directional links [3]- [5]. However, this in turn requires knowledge of the propagation channel.…”

Section: Introductionmentioning

confidence: 99%

5G Position and Orientation Estimation through Millimeter Wave MIMO

Shahmansoori

Garcia

Destino

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

103

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Abstract-Millimeter wave and massive MIMO are considered enabling technologies for future 5G networks. While their benefits for achieving high-data rate communications are wellknown, their potential advantages for accurate positioning are largely undiscovered. We derive sufficient conditions under which transmission from a single mm-wave base station leads to a nonsingular Fisher information matrix associated with the position and orientation of a user terminal equipped with multiple antennas, which is in turn a prerequisite for joint estimation of the position and orientation.

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Section: Introductionmentioning

confidence: 99%

5G Position and Orientation Estimation through Millimeter Wave MIMO

Shahmansoori

Garcia

Destino

et al. 2015

2015 IEEE Globecom Workshops (GC Wkshps)

103

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show abstract

“…Contrary to prior work in [5][6][7][8][9][10], the training overhead of the proposed channel estimation solution does not scale with the number of users. Hence, it is of special interest for multi-user mmWave systems.…”

Section: Introductionmentioning

confidence: 64%

“…To overcome the hardware limitations, analog beamforming solutions were proposed in [6][7][8][9][10], which rely on controlThis work is supported in part by the National Science Foundation under Grant No. 1218338 and 1319556, and by a gift from Huawei Technologies, Inc. ling the phase of the signal transmitted by each antenna via a network of analog phase shifters.…”

Section: Introductionmentioning

confidence: 99%

“…1218338 and 1319556, and by a gift from Huawei Technologies, Inc. ling the phase of the signal transmitted by each antenna via a network of analog phase shifters. To avoid the need for explicit channel knowledge, the algorithms in [6][7][8][9][10] depend on beam training which iteratively designs the analog beamforming coefficients at the transmitter and receiver. These solutions, however, have two main disadvantages: (i) they support only single-stream transmissions (2) their training overhead scales linearly with the number of users.…”

Section: Introductionmentioning

confidence: 99%

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Compressed sensing based multi-user millimeter wave systems: How many measurements are needed?

Alkhateeby

Leusz

Heath

2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

265

210

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Millimeter wave (mmWave) systems will likely employ directional beamforming with large antenna arrays at both the transmitters and receivers. Acquiring channel knowledge to design these beamformers, however, is challenging due to the large antenna arrays and small signal-to-noise ratio before beamforming. In this paper, we propose and evaluate a downlink system operation for multi-user mmWave systems based on compressed sensing channel estimation and conjugate analog beamforming. Adopting the achievable sum-rate as a performance metric, we show how many compressed sensing measurements are needed to approach the perfect channel knowledge performance. The results illustrate that the proposed algorithm requires an order of magnitude less training overhead compared with traditional lower-frequency solutions, while employing mmWave-suitable hardware. They also show that the number of measurements need to be optimized to handle the trade-off between the channel estimate quality and the training overhead.

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“…To overcome such disadvantages that both massive MU-MIMO and mmWave communication have in common, analog beamforming implemented just by employing the phase shifters at each RF chain and the combiner to coherently sum the phase-corrected signals by the phase shifters has been considered [17,18]. Unfortunately, the performance of analog beamforming is sub-optimal due to the limitation of controlling the signal phase.…”

Section: Introductionmentioning

confidence: 99%

Channel estimation and analog beam selection for uplink multiuser hybrid beamforming system

Kim

2016

J Wireless Com Network

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This paper considers an uplink multiuser hybrid beamforming system where a base station (BS) communicates with multiple users simultaneously. The performance of the uplink multiuser hybrid beamforming system depends on the effective channel which is given by the product of channel matrix and the analog beams. Therefore, to maximize the performance, we need to acquire information of the channels and select the appropriate analog beams from the set of predefined analog beams. In this paper, we propose the channel estimation methods and analog beam selection algorithm for the uplink multiuser hybrid beamforming system. First, we design the estimation methods to exploit the channel information of the users by considering Rayleigh fading and millimeter wave (mmWave) channel models. Then, using the estimated channel information, we propose a low-complexity analog beam selection algorithm for the uplink multiuser hybrid beamforming system. We compare the complexity to show that the proposed analog beam selection algorithm has much less complexity than the exhaustive search-based optimum analog beam selection while the performance loss of the proposed analog beam selection algorithm is not significant compared to the optimum analog beam selection, which is shown by the numerical results.

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Coding the Beams: Improving Beamforming Training in mmWave Communication System

Abstract: Abstract-The

Cited by 163 publications

References 11 publications

5G Position and Orientation Estimation through Millimeter Wave MIMO

5G Position and Orientation Estimation through Millimeter Wave MIMO

Compressed sensing based multi-user millimeter wave systems: How many measurements are needed?

Channel estimation and analog beam selection for uplink multiuser hybrid beamforming system

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