One of the key ideas for reducing downlink channel acquisition overhead for FDD massive MIMO systems is to exploit a combination of two assumptions: (i) the dimension of channel models in propagation domain may be much smaller than the next-generation base-station array sizes (e.g., 64 or more antennas), and (ii) uplink and downlink channels may share the same low-dimensional propagation domain. Our channel measurements demonstrate that the two assumptions may not always hold, thereby impacting the predicted performance of methods that rely on the above assumptions. In this paper, we analyze the error in modeling the downlink channel using uplink measurements, caused by the mismatch from the above two assumptions. We investigate how modeling error varies with base-station array size and provide both numerical and experimental results. We observe that modeling error increases with the number of base-station antennas, and channels with larger angular spreads have larger modeling error. Utilizing our modeling error analysis, we then investigate the resulting beamforming performance rate loss. Accordingly, we observe that the rate loss increases with the number of base-station antennas, and channels with larger angular spreads suffer from higher rate loss.
Interpolant-based demosaicing routines for dual-mode visible/near-infrared imaging systems
Dual-mode visible/near-infrared imaging systems, including a bioinspired six-channel design and more conventional four-channel implementations, have transitioned from a niche in surveillance to general use in machine vision. However, the demosaicing routines that transform the raw images from these sensors into processed images that can be consumed by humans or computers rely on assumptions that may not be appropriate when the two portions of the spectrum contribute different information about a scene. A solution can be found in a family of demosaicing routines that utilize interpolating polynomials and splines of different dimensionalities and orders to process images with minimal assumptions.
more » « less- Award ID(s):
- 2030421
- NSF-PAR ID:
- 10370817
- Publisher / Repository:
- Optical Society of America
- Date Published:
- Journal Name:
- Optics Express
- Volume:
- 30
- Issue:
- 19
- ISSN:
- 1094-4087; OPEXFF
- Format(s):
- Medium: X Size: Article No. 34201
- Size(s):
- Article No. 34201
- Sponsoring Org:
- National Science Foundation
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