Fig. 1. Principle of computational sensing integrated with free-space optical communication. (a) Spatial light modulation is incorporated into a temporally encoded free-space optical communication system. (b), (c) Recorded optical signals by separate users are computationally processed to recover both the transmitting data and the 3D location. The position-variant responses to the SI sequence within each receiver’s reception field are leveraged to retrieve the spatial information.

Fig. 2. 3D position reconstruction from compressive sampling. (a) Illustration of wireless optical communication of a wide angle with structured illumination. (b) Pipeline of temporal and spatial modulation on the illumination at the transmitter side. (c) Concept of CAP, which optimizes structured illumination to speed up the computational sensing. (d) Coded measurements captured by the receiver and (e) corresponding average downsampled signals in response to different SIs. (f) Recovered angular projections via back-projection. (g) Spatial recovery from (f); scale bar: 100 mm. (h) Pipeline of zero-truncated quadratic fitting-based position estimation.

Fig. 3. Characterization of 3D localization resolution. (a) Illustration of testing points by lateral scanning at 2 m and vertical scanning over distance. (b) MSE and variations in lateral position estimation over the full field at 2 m prove the high accuracy of CAP. (c) Lateral position estimations at small displacements prove the spatial resolving limit of CAP. (d) Recovered images describing the relative position and size of receiver’s reception field at different depths. The estimated aperture sizes by repeated trials are noted in millimeters. (e) Estimation on depth resolution at small depth displacement. (f) Dynamic moving of the receiver and (g) reconstructed 3D trace with example time-points presented.

Fig. 4. Integrated waveform design and communication performance. (a) Waveform design of spatio-temporal encoding to optimize SNR for both data transmission and position sensing. (b) Transmission data rate and received signal intensity with respect to different SIs. Estimated communication performance for SI patterns #5 and #29 is presented in detail. (c) Transmission data rates recorded at different spatial positions at 2 and 1.8 m distances. The relation of data rates and the baud rate is analyzed. (d) Transmission data rates when the receiver is dynamically moving in 3D.

Fig. 5. Adaptive beamforming to enhance the transmission data rate and support VR video transmission. (a) Illustration of adaptive beamforming to focus structured illumination onto the target receiver. (b) Data rates with and without beamforming tested at representative locations: X and Y coordinates in the unit of mm are (264, 190), (346, 264), (554, 554), (190, 129) originating from the left-top corner at 2 m, and (232, 30), (265, 319) at 3 m. (c) Comparison of communication performance after beamforming at the first position at 2 m in (b). Concept of (d) content change and (g) user view change in wireless VR application. Recovered VR video frames transmitted via the 2 m free-space VLC link (e), (h) without and (f), (i) with beamforming.

Fig. 6. Structured illumination reprojection to achieve refined localization resolution. (a) Concept of refined location recovery after beamforming using ROI-focused structured illumination. Characterization of the localization resolution improvement in the (b) XY plane and (c) Z direction.