Browsing by Author "Lin, Tsung-Han"
Now showing items 1-12 of 12
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Achieving High Throughput Ground-to-UAV Transport via Parallel Links
Lin, Chit-Kwan; Kung, H. T.; Lin, Tsung-Han; Tarsa, Stephen John; Vlah, Dario (IEEE, 2011)Wireless data transfer under high mobility, as found in unmanned aerial vehicle (UAV) applications, is a challenge due to varying channel quality and extended link outages. We present FlowCode, an easily deployable link-layer ... -
Compressive Sensing Medium Access Control for Wireless LANs
Lin, Tsung-Han; Kung, H. T. (Institute of Electrical and Electronics Engineers, 2012)We propose a medium access control (MAC) protocol for wireless local area networks (LANs) that leverages the theory of compressive sensing. The proposed compressive sensing MAC (CS-MAC) exploits the sparse property that, ... -
Computing Sparse Representations in O(N log N) Time
Lin, Tsung-Han; Kung, H. T. (Signal Processing with Adaptive Sparse Structured Representations (SPARS 2013), 2013) -
Concurrent Channel Access and Estimation for Scalable Multiuser MIMO Networking
Lin, Tsung-Han; Kung, H. T. (2012-07-26)This paper presents the design of MIMO/CON (“MIMO with concurrent channel access and estimation”), a PHY/MAC cross-layer design delivering throughput scalable to many users for multiuser MIMO wireless networking. By allowing ... -
FlowCode: Multi-site data exchange over wireless ad-hoc networks using network coding
Kung, H. T.; Lin, Chit-Kwan; Lin, Tsung-Han; Tarsa, Stephen John; Vlah, Dario (IEEE, 2009)We present FlowCode, a system that exploits network coding at the granularity of traffic flows to facilitate fault-tolerant data exchange in wireless mesh networks. Applications include multi-site data replication in ad-hoc ... -
Identifying bad measurements in compressive sensing
Kung, H. T.; Lin, Tsung-Han; Vlah, Dario (2011)We consider the problem of identifying bad measurements in compressive sensing. These bad measurements can be present due to malicious attacks and system malfunction. Since the system of linear equations in compressive ... -
Localization with Snap-Inducing Shaped Residuals (SISR) - Coping with Errors in Measurement
Kung, H. T.; Lin, Chit-Kwan; Lin, Tsung-Han; Vlah, Dario (2009)We consider the problem of localizing wireless nodes in an outdoor, open-space environment, using ad-hoc radio ranging measurements, e.g., 802.11. As in other range-based methods, we cast ranging measurements as a set of ... -
A location-dependent runs-and-gaps model for predicting TCP performance over a UAV wireless channel
Kung, H. T.; Lin, Chit-Kwan; Lin, Tsung-Han; Tarsa, Stephen John; Vlah, Dario; Hague, Daniel; Muccio, Michael; Poland, Brendon; Suter, Bruce (IEEE, 2010)In this paper, we use a finite-state model to predict the performance of the Transmission Control Protocol (TCP) over a varying wireless channel between an unmanned aerial vehicle (UAV) and ground nodes. As a UAV traverses ... -
Measuring diversity on a low-altitude UAV in a ground-to-air wireless 802.11 mesh network
Kung, H. T.; Lin, Chit-Kwan; Lin, Tsung-Han; Tarsa, Stephen John; Vlah, Dario (IEEE, 2010)We consider the problem of mitigating a highly varying wireless channel between a transmitting ground node and receivers on a small, low-altitude unmanned aerial vehicle (UAV) in a 802.11 wireless mesh network. One approach ... -
Parallelization Primitives for Dynamic Sparse Computations
Lin, Tsung-Han; Tarsa, Stephen John; Kung, H. T. (2013)We characterize a general class of algorithms common in machine learning, scientific computing, and signal processing, whose computational dependencies are both sparse, and dynamically defined throughout execution. Existing ... -
Performance Gains in Conjugate Gradient Computation with Linearly Connected GPU Multiprocessors
Tarsa, Stephen John; Lin, Tsung-Han; Kung, H.T. (USENIX Association, 2012)Conjugate gradient is an important iterative method used for solving least squares problems. It is compute-bound and generally involves only simple matrix computations. One would expect that we could fully parallelize such ... -
Stable and Efficient Sparse Recovery for Machine Learning and Wireless Communication
Lin, Tsung-Han (2014-06-06)Recent theoretical study shows that the sparsest solution to an underdetermined linear system is unique, provided the solution vector is sufficiently sparse, and the operator matrix has sufficiently incoherent column ...