Xueyuan Zhao

Low-power all-analog circuit for rectangular-type analog joint source channel coding

A low-complexity and low-power all-analog circuit is proposed to perform efficiently Analog Joint Source Channel Coding (AJSCC). The proposed idea is to adopt Voltage Controlled Voltage Source (VCVS) to realize the rectangular-type mapping in AJSCC. The proposal is verified by Spice simulations as well as via breadboard and Printed Circuit Board (PCB) implementations. Field testing results indicate that the design is feasible for low-complexity and low-power systems such as wireless sensor networks for environmental monitoring.

Energy-efficient analog sensing for large-scale, high-density persistent wireless monitoring

The research challenge of current Wireless Sensor Networks (WSNs) is to design energy-efficient, low-cost, high-accuracy, self-healing, and scalable systems for applications such as environmental monitoring. Traditional WSNs consist of low density, power-hungry digital motes that are expensive and cannot remain functional for long periods on a single charge. In order to address these challenges, a dumb-sensing and smart-processing architecture that splits sensing and computation capabilities among tiers is proposed. Tier-1 consists of dumb sensors that only sense and transmit, while the nodes in Tier-2 do all the smart processing on Tier-1 sensor data. A low-power and low-cost solution for Tier-1 sensors has been proposed using Analog Joint Source Channel Coding (AJSCC). An analog circuit that realizes the rectangular type of AJSCC has been proposed and realized on a Printed Circuit Board for feasibility analysis. A prototype consisting of three Tier-1 sensors (sensing temperature and humidity) communicating to a Tier-2 Cluster Head has been demonstrated to verify the proposed approach. Results show that our framework is indeed feasible to support large scale high density and persistent WSN deployment.

Towards low-power wearable wireless sensors for molecular biomarker and physiological signal monitoring

A low-power wearable wireless sensor measuring both molecular biomarkers and physiological signals is proposed, where the former are measured by a microfluidic biosensing system while the latter are measured electrically. The low-power consumption of the sensor is achieved by an all-analog circuit implementing Analog Joint Source-Channel Coding (AJSCC) compression. The sensor is applicable to a wide range of biomedical applications that require real-time concurrent molecular biomarker and physiological signal monitoring.

AMMCA: Acoustic Massive MIMO with Carrier Aggregation to Boost the Underwater Communication Data Rate

A new communication approach based on massive Multiple Input Multiple Output (MIMO) with Carrier Aggregation (CA), named AMMCA, is proposed to boost the achievable data rate for multimedia traffic in underwater acoustic channels. The system under study is composed of a surface buoy station with many hydrophones and of an underwater static or mobile node such as an Autonomous Underwater Vehicle (AUV) with a few transducers. The proposed idea presents two components: (i) the first consists in deploying a large number of hydrophones at the buoy for uplink massive MIMO reception; (ii) the second requires employing carrier aggregation of Orthogonal Frequency Division Multiplexing (OFDM) symbols to exploit a wider underwater bandwidth than in traditional acoustic systems that use only a few tens of KHz. Via both theoretical analysis and computer-based simulations, AMMCA is shown to boost the achievable data rate in underwater acoustic channels for both medium/short and long distances.

BD-ZCS: Multi-cell interference coordination via Zadoff-Chu sequence-based block diagonalization

Multi-cell interference coordination via Block Diagonalization (BD), which is widely used in LTE-Advanced interference management, has three main drawbacks: (1) limitation on the number of supported co-channel users; (2) performance degradation in Doppler channels with feedback delay and quantization; and (3) high signaling overhead to exchange Channel State Information (CSI) and to generate precoding matrix. In this paper, a new approach is proposed to overcome these drawbacks and to improve the multi-cell interference coordination. The core idea is to create a null space only to the users within one cell; to achieve this goal, Zadoff-Chu Sequence (ZCS) spreading is used to eliminate the multi-cell interference by leveraging the zero-correlation property of cyclic shifts of the ZCS. This way, the capacity of the cellular network is improved in Doppler channels with delayed and quantized feedback; moreover, signaling overhead and computational complexity are both reduced. The auxiliary sampling capability of the hardware is utilized to realize the higher sampling rate required by the proposed approach. The new interference-management solution is compared against the existing one via computer simulations and is shown to lead to significant capacity gains even in high-mobility scenarios.

Improved Circuit Design of Analog Joint Source Channel Coding for Low-Power and Low-Complexity Wireless Sensors

To enable low-power and low-complexity wireless monitoring, an improved circuit design of Analog Joint Source Channel Coding (AJSCC) is proposed for wireless sensor nodes. This innovative design is based on Analog Divider Blocks (ADB) with tunable spacing between AJSCC levels. The ADB controls the switching between two types of Voltage Controlled Voltage Sources (VCVS). LTSpice simulations have been performed to evaluate the performance of the circuit, and the power consumption and circuit complexity of this new ADB-based design have been compared with our previous parallel-VCVS design. It is found that this improved circuit design based on ADB outperforms the design based on parallel VCVS for a large number of AJSCC levels (≥16), both in terms of power consumption as well as circuit complexity, thus enabling persistent and higher temporal/spatial resolution environmental sensing.

Walsh-hadamard transform of DNA methylation profile for the classification of human cancer cells

The discovery is reported on the low dimension and three step property of transform domain vector of of DNA methylation profile after Walsh-Hadamard Transform. The transform domain vector is unique for particular tissue type, and shows difference between normal and disease cells of the same tissue type. A new human disease cell classification approach is further proposed in this work, and the approach is tested with multiple datasets and classifiers. Results show that the proposed approach can achieve high classification accuracy and has great potential for practical applications.