The research disciplines whose use I advocate include statistical inference and non-linear optimization. The aim is to model, design, and optimize different types of systems and networks. There are numerous thrust areas of my research group.

The following samples a few key thrusts of my research, with selected publications in each area.

Algorithms on Manifolds

My group has been focusing on developing theories and methodologies for representing large-dimensional multiple-input multiple-output (MIMO) channels on lower-dimensional subspaces by engaging manifold structure. Many algorithms on manifold bring expressiveness and accountability benefits, which can be used for developing optimized methods with considerably reduced complexity. My research has successfully engaged various manifold structures (Grassmannian, Riemannian, unit-simplex, etc.) for MIMO precoding, beamforming, channel estimation, and detection.

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High Frequency Beam Alignment, Tracking, and Channel Estimation

The so-called “beam alignment” is a procedure for finding the best transmit-and-receive beam pair to establish a link without estimating the channel state information (CSI). However, the use of directional narrow beams for searching the entire beam space is an extremely time-consuming operation.

In this thrust area, we have been focusing on developing theories and algorithms for the purpose of achieving fast beam alignment and tracking (refinement) performance by leveraging advanced channel representation on virtual beamspace, unit probability simplex, Krylov subspace, and restricted isometry. Recently, the emphasis has been placed on the learnability and interpretability of the beam refinement process and its time-varying causality with CSI estimation.

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Millimeter-Wave Basestation Deployment

Although mmWave cellular systems can carry a larger volume of traffic, the recent increase in the cost of deploying and maintaining mmWave small-cell BSs is a practical concern that wireless service providers are constantly facing.

My group has been studying methodologies to the problem of mmWave BS deployment in urban environments by minimizing BS deployment cost subject to BS association and user equipment (UE) outage constraints by integrating physical blockage, UE access-limited blockage, and signal-to-interference-plus-noise-ratio (SINR) outage into its quantification. Interestingly, the proposed methods produce a unique distribution of the macro-diversity orders over the network that is distinct from other benchmark deployments.

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Distributed Interference Management and Resource Allocation

In this thurst, we have been developing distributed interference mitigation and resource allocation algorithms for multicell multiuser (MCMU) networks. The focus is providing performance guarantees with the minimum possible resource utilization. This thrust has been providng sufficient conditions for the feasibility of the proposed distributed algorithms by developing precoding, combining, power control, subchannel allocation, and relay selection frameworks. The underlying principle is decomposing the origianl sum rate maximization or performance-guranteed power minimization problems into forward and backward (FB) subproblems to ensure desired properites of the original problems such as strong duality, convexity, and convergence.

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Feature Learning and Channel Charting

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