Training Beam Sequence Optimization for Millimeter Wave MIMO Tracking Systems

Fifth generation (5G) cellular standards are set to utilize millimeter wave (mmWave) frequencies, which enable data speeds greater than 10 Gbps and sub-centimeter localization accuracy. These capabilities rely on accurate estimates of the channel parameters, which we define as the angle of arrival, angle of departure, and path distance for each path between the transmitter and receiver. Estimating the channel parameters in a computationally efficient manner poses a challenge because it requires estimation of parameters from a high-dimensional measurement -particularly for multi-carrier systems since each subcarrier must be estimated separately. Additionally, channel parameter estimation must be able to handle hybrid beamforming, which uses a combination of digital and analog beamforming to reduce the number of required analog to digital converters. This paper introduces a channel parameter estimation technique based on the multilinear singular value decomposition (MSVD), a tensor analog of the singular value decomposition, for massive multiple input multiple output (MIMO) multi-carrier systems with hybrid beamforming. The MSVD tensor estimation approach provides a computationally efficient method and is shown to closely match the Cramer-Rao bound (CRB) of parameter estimates through simulations. Limitations of channel parameter estimation and communication waveform effects are also studied.

show abstract

“…The path distance is estimated in the tensor fiber subspace. From (12), the fiber vector for each path contains the terms:…”

Section: Distance Redundancymentioning

confidence: 99%

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Ruble

Güvenç

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…pairs. Moreover, the repetition times of B k,i during one beam training period is denoted by λ k,i , and the corresponding received symbols are expressed as y k,i [1], · · · , y k,i [λ k,i ], respectively. By adding up the λ k,i received symbols, we obtain that…”

Section: A Closed-form Astpmentioning

confidence: 99%

“…Thanks to Deyou Ming.Ding@data61.csiro.au). Part of this paper was presented at the IEEE International Conference on Communications, 2018 [1]. the rich available spectrum, millimeter-wave (mmWave) communication ranging from 30GHz to 300GHz emerged as a promising solution.…”

Section: Introductionmentioning

confidence: 99%

“…In Section III, orthogonal Tx-Rx training beam pairs are assumed and a power-based estimator is used to track the time-varying AoA and AoD. In Section IV, 1 It is worth mentioning that the Tx-Rx training beam pairs are also allowed to be used repeatedly in [29]. However, since an online stochastic optimization known as multi-armed bandit algorithm is considered, one feedback of the received energy is needed after each measurement, which may significantly exacerbate the system overhead.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Beam Allocation for Millimeter-Wave MIMO Tracking Systems

Zhang

Chen

et al. 2020

IEEE Trans. Veh. Technol.

Self Cite

View full text Add to dashboard Cite

In this paper, we propose a new beam allocation strategy aiming to maximize the average successful tracking probability (ASTP) of time-varying millimeter-wave MIMO systems. In contrast to most existing works that employ one transmitting-receiving (Tx-Rx) beam pair once only in each training period, we investigate a more general framework, where the Tx-Rx beam pairs are allowed to be used repeatedly to improve the received signal powers in specific directions. In the case of orthogonal Tx-Rx beam pairs, a power-based estimator is employed to track the time-varying AoA and AoD of the channel, and the resulting training beam pair sequence design problem is formulated as an integer nonlinear programming (I-NLP) problem. By dividing the feasible region into a set of subregions, the formulated I-NLP is decomposed into a series of concave sub I-NLPs, which can be solved by recursively invoking a nonlinear branch-and-bound algorithm. To reduce the computational cost, we relax the integer constraints of each sub I-NLP and obtain a low-complexity solution via solving the Karush-Kuhn-Tucker conditions of their relaxed problems. For the case when the Tx-Rx beam pairs are overlapped in the angular space, we estimate the updated AoA and AoD via an orthogonal matching pursuit (OMP) algorithm. Moreover, since no explicit expression for the ASTP exists for the OMP-based estimator, we derive a closed-form lower bound of the ASTP, based on which a favorable beam pair allocation strategy can be obtained. Numerical results demonstrate the superiority of the proposed beam allocation strategy over existing benchmarks. Index TermsMillimeter wave, time-varying channel, beam training, beam tracking, training beam sequence design.

show abstract

“…Conventional protocols such as exhaustive beam selection schemes, or received signal power protocols do not consider the positioning information in an explicit manner [8]. A great deal of research has been devoted to reduce the time for initial access, including methods for different array types (analog [8], [23], hybrid [14], arrays of subarrays [24], [25]), as well as methods that adapt rate and power [26], [27], operate in tracking mode [28]- [30], rely on low-complexity non-coherent processing [31], or consider learning-based approaches [32].…”

Section: Introductionmentioning

confidence: 99%

Fast in-Band Position-Aided Beam Selection in Millimeter-Wave MIMO

Garcia

Seco‐Granados

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Millimeter-wave (mm-wave) and massive multiple-input-multiple-output technologies appear as key enablers in future emerging wireless communication systems. Propagation in mm-wave communications is well described by geometric channel models, where a clear relation between communication and positioning arises. On one hand, initial access, a procedure that precedes high data rate transmission and consists of beam selection and alignment between two devices, can benefit from position information. On the other hand, accurate positioning relies on high-quality communication links with proper beam alignment. This work analyzes the interplay between communication and positioning, proposes a new in-band positionaided beam selection protocol considering scenarios with line-of-sight and reflected paths, and possible beam alignment errors. Simulation results show significant reductions in latency with respect to standard beam selection protocols.

show abstract

Training Beam Sequence Optimization for Millimeter Wave MIMO Tracking Systems

Cited by 14 publications

References 16 publications

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Multilinear Singular Value Decomposition for Millimeter Wave Channel Parameter Estimation

Beam Allocation for Millimeter-Wave MIMO Tracking Systems

Fast in-Band Position-Aided Beam Selection in Millimeter-Wave MIMO

Contact Info

Product

Resources

About