Syracuse University

Intelligent Fusion Technology, Inc.

Biao Chen

Yang Liu

John Matyjas

Michael Gans

Tiexing Wang

Genshe Chen

Dan Shen

Xin Tian

Yi Li

Nichole Sullivan

Wenhao Xiong

Janek Mroczek

Yuexin Jiang

Kapil Borle

Fangfang Zhu

Yu Zhao

Fangrong Peng

Jin Xu

A method of detecting and quantifying human objects in a given environment by passively observing wireless signals in an interesting environment. Information pertaining to observed wireless signals, such as wireless physical layer data and metadata, encrypted or unencrypted data and metadata in the wireless media-access control layer, and channel state information are extracted from the observed wireless signals and used to detect and quantify human objects in a location. The signals that are observed can originate from a wireless object used by a target of interest, such as cellular phone or workstations, or from infrastructure devices, such as wireless access points, IoT devices, or other transceivers. The signals can also originate from other recognizable signal sources, such as electromagnetic interference introduced by equipment such as elevator motors or microwave ovens.

Occupancy detection and people counting using passive wireless interfaces

A system for using radio frequency (RF) communication signals to extract situational awareness information thorough deep learning. Pre-processing is performed to maximally preserve discriminating features in spatial, temporal and frequency domains. A specially designed neural network architecture is used for handling complex RF signals and extracting spatial, temporal and frequency domain information. Data collection and training is used so that the learning system desensitizes from features orthogonal to the underlying classification problem.

Motion detection and classification using ambient wireless signals

A multiple-input multiple-output (MIMO) communication system that addresses three major challenges in airborne MIMO communications, namely, antenna blockage due largely to the movement and orientation of the airborne platforms, the presence of unknown interference inherent to the intended application, and the lack of channel state information (CSI) at the transmitter. The system is implemented on a Diagonal Bell-Labs Layered Space-Time (D-BLAST) MIMO architecture and includes spatial spreading to counter antenna blockage, temporal spreading to mitigate signal to interference and noise ratio degradation due to intended or unintended interference, and a simple low rate feedback scheme to enable real time adaptation in the absence of full transmitter CSI.

Variable rate MIMO for multi-user communications involving airborne platforms

Simultaneous 2-D room shape reconstruction and self-localization is accomplished using no pre-established infrastructure. A mobile device with co-located microphone and loudspeaker is used to collect echoes reflected by the walls. The system uniquely recovers arbitrary 2-D convex room shape as well as the position of mobile deviceby collecting and processing distances between three consecutive measurement points as well as acoustic echoes from the device. A practical algorithm for room shape reconstruction and self-localization in the presence of noise and higher order echoes is proposed. Experimental results are provided to demonstrate the effectiveness of the approach.

Motion sensor assisted room shape reconstruction and self-localization using first-order acoustic echoes

A three-layer protocol stack in a wireless communication device and a wireless communication network are provided. The three-layer protocol stack includes a physical layer; a medium access control (MAC) layer; and a network layer. The physical layer includes one or more circuits to conduct a power consumption minimization and a waveform selection. The MAC layer is configured to perform a medium access control and a resource block reconfiguration. The network layer is configured to perform an energy efficient routing and connection maintenance. The physical layer, the MAC layer and the network layer cooperate with each other to at least reduce an energy consumption of the wireless communication device.

Method and system for energy efficient wireless communications

A communication system that minimizes the transmission of pilot symbols while ensuring real-time channel tracking and symbol detection. The system employs a multiple-input multiple-output (MIMO) transmitter-receiver pair where there are many more receive antennas than transmit antennas. Communication occurs over a wide band RF channel via orthogonal frequency division multiplexing (OFDM) that employs a large number of sub-carriers.

Efficient channel estimation and symbol detection for massive MIMO-OFDM

A communication system that minimizes the transmission of pilot symbols while ensuring real-time channel tracking and symbol detection. The system employs a multiple-input multiple-output (MTMO) transmitter-receiver pair where there are many more receive antennas than transmit antennas. Communication occurs over a wide band RF channel via orthogonal frequency division multiplexing (OFDM) that employs a large number of sub-carriers.

A method of decoding a plurality of diverse signals for low-density parity-check (LDPC) decoders that takes advantage of signal diversity. The method allows for the combining of soft-decision LDPC encoded non-coherently modulated signals, which is in contrast to existing approaches where hard decision combining is used for non-coherently modulated signals. The method includes the steps of inputting each diversity signal into a unique demodulator, and calculating the LLR of each demodulated signal. When the diverse demodulated signals are combined into a single combined signal, each bit of the combined signal is selected according to the value of either the highest LLR value of each bit across the demodulated signals or according to the sum of the LLR of each bit across the demodulated signals.

Diversity combining of non-coherently modulated LDPC codes in wireless communications

A method for securely communicating a message from a source node to a destination node over a network can comprise the steps of converting the message into an initial bit sequence, pre-processing the initial bit sequence by a modulo adding the initial bit sequence with an auxiliary key message, constructing a reduced network, determining a multitude of paths from the source node to the destination node over the reduced network, constructing an expanded bit sequence comprising the initial bit sequence and the auxiliary key message, splitting the expanded bit sequence into two or more parts, transmitting the two or more parts of the expanded bit sequence over two or more paths of the multitude of paths, re-assembling the two or more parts of the expanded bit sequence at the destination node, and recovering the initial bit sequence by modulo adding the expanded bit sequence with the auxiliary key message.

Method for secure communication over heterogeneous networks

A method for blindly determining a channel impulse response (CIR) for a channel in an orthogonal frequency division multiplexing (OFDM) communications system includes constructing a matrix from two received signals. A singular value decomposition is performed on the matrix, which produces left and right singular matrixes. The right singular vector corresponding to the smallest singular value of the matrix is found, which yields the channel impulse response multiplied by an unknown scalar constant. The unknown scalar constant is then removed used known techniques. The method is data efficient, independent of the input symbol constellation, computationally efficient, and superior in performance compared with prior art blind algorithms.

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Jamesville, NY, United States of America

Biao Chen