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CoVRage: Millimeter-Wave Beamforming for Mobile Interactive Virtual Reality

Jakob Struye, Filip Lemic, Jeroen Famaey

TL;DR

CoVRage tackles the challenge of delivering high-bandwidth, ultra-low-latency mmWave video for mobile VR by performing receive-side beamforming that proactively covers the predicted AoA trajectory using dynamically formed sub-arrays. It relies on on-device orientation prediction to generate a near-future trajectory and synthesizes an oblong, trajectory-covering beam by distributing sub-beams across virtual sub-arrays, with a transitional sub-array mechanism to mitigate aperture fusion. Through extensive simulations, coVRage demonstrates high, stable receive gains along diverse trajectories, resilience to prediction errors, and compatibility with quantized phase shifters and multipath channels, while maintaining practical runtimes on mobile hardware. The work lays groundwork for truly wireless VR at 120 GHz and points to future extensions involving multi-AP coordination and intelligent reflectors to broaden coverage and reliability.

Abstract

Contemporary Virtual Reality (VR) setups often include an external source delivering content to a Head-Mounted Display (HMD). "Cutting the wire" in such setups and going truly wireless will require a wireless network capable of delivering enormous amounts of video data at an extremely low latency. The massive bandwidth of higher frequencies, such as the millimeter-wave (mmWave) band, can meet these requirements. Due to high attenuation and path loss in the mmWave frequencies, beamforming is essential. In wireless VR, where the antenna is integrated into the HMD, any head rotation also changes the antenna's orientation. As such, beamforming must adapt, in real-time, to the user's head rotations. An HMD's built-in sensors providing accurate orientation estimates may facilitate such rapid beamforming. In this work, we present coVRage, a receive-side beamforming solution tailored for VR HMDs. Using built-in orientation prediction present on modern HMDs, the algorithm estimates how the Angle of Arrival (AoA) at the HMD will change in the near future, and covers this AoA trajectory with a dynamically shaped oblong beam, synthesized using sub-arrays. We show that this solution can cover these trajectories with consistently high gain, even in light of temporally or spatially inaccurate orientational data.

CoVRage: Millimeter-Wave Beamforming for Mobile Interactive Virtual Reality

TL;DR

CoVRage tackles the challenge of delivering high-bandwidth, ultra-low-latency mmWave video for mobile VR by performing receive-side beamforming that proactively covers the predicted AoA trajectory using dynamically formed sub-arrays. It relies on on-device orientation prediction to generate a near-future trajectory and synthesizes an oblong, trajectory-covering beam by distributing sub-beams across virtual sub-arrays, with a transitional sub-array mechanism to mitigate aperture fusion. Through extensive simulations, coVRage demonstrates high, stable receive gains along diverse trajectories, resilience to prediction errors, and compatibility with quantized phase shifters and multipath channels, while maintaining practical runtimes on mobile hardware. The work lays groundwork for truly wireless VR at 120 GHz and points to future extensions involving multi-AP coordination and intelligent reflectors to broaden coverage and reliability.

Abstract

Contemporary Virtual Reality (VR) setups often include an external source delivering content to a Head-Mounted Display (HMD). "Cutting the wire" in such setups and going truly wireless will require a wireless network capable of delivering enormous amounts of video data at an extremely low latency. The massive bandwidth of higher frequencies, such as the millimeter-wave (mmWave) band, can meet these requirements. Due to high attenuation and path loss in the mmWave frequencies, beamforming is essential. In wireless VR, where the antenna is integrated into the HMD, any head rotation also changes the antenna's orientation. As such, beamforming must adapt, in real-time, to the user's head rotations. An HMD's built-in sensors providing accurate orientation estimates may facilitate such rapid beamforming. In this work, we present coVRage, a receive-side beamforming solution tailored for VR HMDs. Using built-in orientation prediction present on modern HMDs, the algorithm estimates how the Angle of Arrival (AoA) at the HMD will change in the near future, and covers this AoA trajectory with a dynamically shaped oblong beam, synthesized using sub-arrays. We show that this solution can cover these trajectories with consistently high gain, even in light of temporally or spatially inaccurate orientational data.
Paper Structure (25 sections, 20 equations, 13 figures, 3 tables)

This paper contains 25 sections, 20 equations, 13 figures, 3 tables.

Figures (13)

  • Figure 1: Different (virtual) sub-array layouts in a phased array. A black square designates a block, which is the maximal region within which all sub-arrays are interleaved with each other. Any two sub-arrays from different blocks are localized to each other. The indicated inter-element spacings are chosen to maintain an inter-element spacing of $0.5\lambda$ within a sub-array. Each element label consists of the index of its block (a letter) and the index of its sub-array within that block (a digit).
  • Figure 2: 16 beams, with $\theta$ and $\psi \in \{-60,-15,15,60\}$ degrees, all appear as near-perfect circles in UV-space, but are warped significantly near the edges in Euler coordinates. Green circles show the intended directions.
  • Figure 3: Aperture fusion is clearly visible when forming the same two adjacent sub-beams (large green circle) with the same midpoint (small brown circle) with sub-arrays either in the same block, or in horizontally/vertically/diagonally different blocks.
  • Figure 4: On the left, a $16 \times 4$ antenna array is configured as two $8 \times 4$ blocks of four $4 \times 2$ interleaved sub-arrays each. To reduce aperture fusion between sub-arrays from different blocks, we introduce transitional sub-arrays in the right configuration, shown with thicker edges. Half of the elements initially assigned to sub-arrays A1 and B1 now form a new transitional sub-array T1, in a new transitional block (delimited by dotted lines), overlapping with the two original blocks (separated by dashed line). The remaining elements of A1 and B1 are disabled, shown in white. Analogously, T2 is formed from A2 and B2.
  • Figure 5: The order in which sub-arrays are mapped to sub-beams, for each type of beam, for an array such as seen in Fig. \ref{['fig:hybrid']}. Each circle is a sub-array, consisting of several antenna elements. Each sub-array may be active (green) or inactive (pink). The orange line connects all active sub-arrays in order, such that connected sub-arrays form adjacent sub-beams. For each transitional sub-array (in a grey box), a sub-array is deactivated in each adjacent block. Within a block, sub-arrays are interchangeable.
  • ...and 8 more figures