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Chris Ng

Publications and source records attributed to Chris Ng.

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Design of a Robust Fiber Optic Communications System for Future IceCube Detectors

In this work we discuss ongoing development of a hybrid fiber/copper data and timing infrastructure for the future IceCube-Gen2 detector. The IceCube Neutrino Observatory is a kilometer-scale detector operating with 86 strings of modules. These modules communicate utilizing a custom protocol to mitigate the signaling challenges of long distance copper cables. Moving past the limitations of a copper-based backbone will allow larger future IceCube detectors with extremely precise timing and a large margin of excess throughput to accommodate innovative future modules. To this end, the upcoming IceCube Upgrade offers an opportunity to deploy a pathfinder for the new fiber optic infrastructure, called the Fiber Test System. This design draws on experience from AMANDA and IceCube and incorporates recently matured technologies such as ruggedized fibers and White Rabbit timing to deliver robust and high-performance data and timing transfer.

astro-ph.IM

Subband Beamforming in Coherent Hybrid Massive MIMO Using Eigenbeams

Hybrid Massive MIMO reduces implementation complexity but only supports beamforming coefficients that are common across all subbands. However, in macro cellular where the channel has limited degrees of freedom, the long-term component of the channel can be decomposed into a set of subband-independent beamforming basis functions referred to as eigenbeams. A Coherent Hybrid Massive MIMO system can form arbitrary linear combinations of the eigenbeams at every subband to mimic Digital Massive MIMO beamforming as observed across all locations in the cell.

eess.SP

Adaptive Hybrid Beamforming with Massive Phased Arrays in Macro-Cellular Networks

Hybrid beamforming via large antenna arrays has shown a great potential for increasing data rate in cellular networks by delivering multiple data streams simultaneously. In this paper, several beamforming design algorithms are proposed based on the long-term channel information for macro-cellular environments where the base station is equipped with a massive phased array under per-antenna power constraint. Using an adaptive scheme, beamforming vectors are updated whenever the long-term channel information changes. First, the problem is studied when the base station has a single RF chain (single-beam scenario). Semi-definite relaxation (SDR) with randomization is used to solve the problem. As a second approach, a low-complexity heuristic beam composition algorithm is proposed which performs very close to the upper-bound obtained by SDR. Next, the problem is studied for a generic number of RF chains (multi-beam scenario) where the Gradient Projection method is used to obtain local solutions. Numerical results reveal that using massive antenna arrays with optimized beamforming vectors can lead to 5X network throughput improvement over systems with conventional antennas.

cs.IT