Abstract
Beamforming training refers to the exhaustive scan over which the transmitter and receiver jointly steer their beams along a predefined set of double-directional angles to determine the beam pairs that coincide with the dominant propagation paths of the channel, for spatial multiplexing at millimeter-wave. When mobile, training necessitates a high refresh rate to maintain connectivity and so, to reduce overhead, beamtracking algorithms exploit the spatial-temporal consistency of the channel to localize the scan around the beam pairs determined at a previous time. The algorithms’ true performance, however, is still unknown since results reported to date are based on oversimplified channel models. In this paper, we propose a novel beamtracking algorithm formulated as a first-order Markov process that supports multiple beam pairs. The algorithm is evaluated through actual channel measurements – <i>not a channel model</i> – recorded with our high-precision 3D double-directional 60 GHz channel sounder. The measurement campaign, to our knowledge, is unprecedented: with 10, 895 large-scale measurements, spaced 8.8 cm apart on average to emulate continuous motion, over which the mobile receiver traversed a total of 900.2 m. We demonstrate that four beam pairs can be sustained always and that eight pairs can be sustained 57% of the time.
Highlights
The ever-rising demand for reliable and ubiquitous broadband access has prompted cellular providers to expand beyond the sub-6 GHz frequency bands – where 1G–4G networks have operated to date – to millimeter-wave bands for 5G – effectively 28-100 GHz – where 100x more bandwidth is available
The IEEE 802.11ay standard [5]-[7] for wireless local area network (WLAN) operating in the 60 GHz unlicensed band estimates the channel through a protocol known as beamforming training (BT): through dedicated pilot sequences, DD beams exhaustively scan a predefined set of DD angles, constituting a codebook, to identify the ones e.g. with the highest signal-to-noise ratio (SNR)
In the presence of mobility, beams will quickly misalign with the dominant paths – a small angle misalignment with such narrow pencilbeams can inflict a huge drop in SNR – requiring a high refresh rate for BT, exacerbating the already burdensome overhead, especially in MIMO (Multiple-Input MultipleOutput) architectures, where multiple DD beams are supported through spatial multiplexing
Summary
The ever-rising demand for reliable and ubiquitous broadband access has prompted cellular providers to expand beyond the sub-6 GHz frequency bands – where 1G–4G networks have operated to date – to millimeter-wave (mmWave) bands for 5G – effectively 28-100 GHz – where 100x more bandwidth is available. In the presence of mobility, beams will quickly misalign with the dominant paths – a small angle misalignment with such narrow pencilbeams can inflict a huge drop in SNR – requiring a high refresh rate for BT, exacerbating the already burdensome overhead, especially in MIMO (Multiple-Input MultipleOutput) architectures, where multiple DD beams are supported through spatial multiplexing. The single paper that employs actual measurements only considers motion over a meter or so and does not capture large-scale variation over which the number of scatterers and their properties change significantly. 2. We formulate a beamtracking algorithm as a first-order Markov process that supports multiple beams through hybrid beamforming in SU-MIMO, that entertains multiple hypotheses, and that dynamically adjusts the scan locality within the codebook to the rate of motion.
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