UOIT researcher receives funding for clean technology solutions

UOIT  online

2012-08-24

Communications technology may soon go green, thanks to new funding for clean technology solutions research at the University of Ontario Institute of Technology (UOIT). Dr. Min Dong, assistant professor, Faculty of Engineering and Applied Science, was recently awarded $140,000, over the next five years, through the Ministry of Economic Development and Innovation’s Early Researcher Awards program.

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Multi-Antenna Relay Network Beamforming Design for Multiuser Peer-to-Peer Communications

IEEE International Conference on Acoustics Speech and Signal Processing   Florence, Italy

2014-05-09

Channel-Aware Distributed Dynamic Spectrum Access via Learning-Based Heterogeneous Multichannel Auction

IEEE International Conference on Acoustics Speech and Signal Processing  Florence, Italy

2014-05-04

Optimal Power Allocation and Network Beamforming for OFDM-Based Relay Networks

IEEE International Conference on Acoustics Speech and Signal Processing  Florence, Italy

2014-05-04

Real-Time Energy Storage Management with Renewable Energy of Arbitrary Generation Dynamics

47th Asilomar Conference on Signals, Systems and Computers  Pacific Grove, California

2013-11-03

Distributed Regulation Allocation with Aggregator Co-ordinated Electric Vehicles

IEEE International Conference on Smart Grid Communications  Vancouver, British Columbia

2013-10-21

SNR-Based Channel Pairing for MABC-Based Two-Way Relaying

14th IEEE International Workshop on Signal Processing Advances in Wireless Communications  Darmstadt, Germany

2013-06-16

Learning-Stage Based Decentralized Adaptive Access Policy for Dynamic Spectrum Access

IEEE International Conference on Acoustics Speech and Signal Processing  Vancouver, British Columbia

2013-05-26

Online Control for Energy Storage Management with Renewable Energy Integration

IEEE International Conference on Acoustics Speech and Signal Processing  Vancouver, British Columbia

2013-05-26

Cooperative Relaying Optimization From Multichannel Resource Assignment to Multi-Antenna Processing Design

Invited Seminar  Shanghai Jiao Tong University, Institute of Wireless Communications, Shanghai, China

2012-08-27

Resource Assignment and its Optimization in Multichannel Cooperative Relaying

Invited Seminar  McMaster University, Hamilton, Ontario

2011-12-01

Low Complexity Beamforming for Multiple Antenna Systems

U.S. Patent No. 8,441,969

2013-05-01

Earlier U.S. Patent No. 8,363,577 granted January 2013. Abstract: Methods and apparatuses are disclosed that utilize the discrete Fourier transform of time domain responses to generate beamforming weights for wireless communication. In addition, in some embodiments frequency subcarriers constituting less than all of the frequency subcarriers allocated for communication to a user may utilized for generating the beamforming weights.

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Estimation of Data-to-Pilot Ratio in Wireless Communication Systems

U.S. Patent No. 8,102,935

2012-01-24

Abstract: Techniques for estimating data-to-pilot ratio are described. A terminal may receive pilot sent to multiple terminals and may receive data sent specifically to the terminal. The terminal may estimate channel gain and noise variance based on the received pilot. The terminal may then estimate a data-to-pilot ratio based on the received data y and the estimated channel gain h and noise variance σ2. In one design, the terminal may determine a metric Iy I 2 −σ2 / |h|2 and may average the metric across multiple received data symbols to obtain the data-to-pilot ratio. The terminal may receive pilot and data via multiple antennas and may combine the received data across these antennas to obtain combined data. The terminal may estimate signal-to-noise-and-interference ratio (SINR) based on the received pilot from the multiple antennas and may then estimate the data-to-pilot ratio based on the combined data and the estimated SINR.

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Orthogonal Resource Reuse with SDMA Beams

U.S. Patent No. 8,036,669, EP 2,334,112

2011-10-01

European Patent issued January 2013. Abstract: A wireless communication system can implement beamforming across multiple omni-directional antennas to create beams at different spatial directions. The communication system can arrange the beams in sets, with each set arranged to provide substantially complete coverage over a predetermined coverage area. The communication system can arrange the multiple SDMA beam sets to support substantially complementary coverage areas, such that a main beam from a first set provides coverage to a weak coverage area of the second beam set. The wireless communication system assigns or otherwise allocates substantially orthogonal resources to each of the beam sets. The wireless communication system allocates resources to a communication link using a combination of beam sets and substantially orthogonal resources in order to provide improved coverage without a corresponding increase in interference.

Cooperative and Cognitive Designs Towards Resource-Efficient Wireless Communications

NSERC Discovery Grant $145000

2014-04-01

PI. Dong. M. 2014-2019. The proposed research program aims to investigate distributed cooperative algorithms and cognitive network resource managing strategies for cooperative relaying. With the integrated view of network architecture, protocols, and processing algorithms, Dr. Dong is targetting novel unified designs that synergize techniques and strategies across the physical (PHY), medium access (MAC) and network-layers to maximize cooperation gain in a full-fledged scale.

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Cloud in the Air: A Heterogeneous Data Communication Framework for Mobile Cloud Computing

NSERC Strategic Project Grant $469,300

2013-01-01

CI. Dong, M. 2013-2016. This research project targets the large-scale heterogeneous communication and networking architecture expected to serve as the backbone of the emerging mobile cloud computing paradigm, and is projected to contribute substantially to state-of-the-art research towards establishing foundational design policies.

Building Green Communications Through Cooperation: Fundamental Limits and Practical Techniques

Ontario MRI Early Researcher Award $190,000

2012-04-30

PI. Dong, M. 2012-2017. This research project aims to design a relay mesh network with high bandwidth efficiency to fulfill the increasing throughput demand, high power-efficiency to move toward the green concept, but minimal overload to facilitate practical applications. A proposed dynamic and decentralized physical layer cooperation framework is based on distributed beamforming and considers physical layer designs jointly with medium access control techniques for a mesh relay network design.

Research Laboratory for Integrated High-Speed Broadband Wireless Communication Systems

CFI Leaders Opportunity Fund $275,000

2012-01-01

CI. Dong, M., 2012-2013

Cognitive Sensing for Dynamic Spectrum Access

NSERC Collaborative Research and Development $123,000

2010-01-01

CI. Dong, M. 2010-2014

Future Ubiquitous Green Mesh Relay Network Design Based on Distributed Beamforming

NSERC Strategic Project Grant $501,000

2010-01-01

CI. Dong, M. 2010-2013

Resource-Constrained Communications and Networking Through Adaptation and Cooperation

NSERC Discovery Grant $145,000

2009-01-01

PI. Dong, M. 2009-2014

Introduction to Engineering

ENGR 1015U, 1st Year, Undergraduate Course

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Signals and Systems

ELEE 3110, 3rd Year, Undergraduate Course

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Wireless Communications

ELEE 4500, 4th Year, Undergraduate Course

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Senior Capstone Design Projects

4th Year, Undergraduate Course

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Digital Communications

ELEE 4130, 4th Year, Undergraduate Course

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Advanced Wireless Communications

ENGH 5640, Graduate Course

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Real-Time Power Balancing in Electric Grids with Distributed Storage

2014-12-01

Abstract: Power balancing is crucial for the reliability of an electric power grid. In this paper, we consider an aggregator co-ordinating a group of distributed storage (DS) units to provide power balancing service to a power grid through charging or discharging. We present a real-time, distributed algorithm that enables the DS units to determine their own charging or discharging amounts. The algorithm accommodates a wide spectrum of vital system characteristics, including time-varying power imbalance amount and electricity price, finite battery size constraints, cost of using external energy sources, and battery degradation. We develop a modified Lyapunov optimization framework for real-time power balancing and provide a fast iterative method for distributed implementation. The two components interact through a novel cost cushion parameter that tunes the trade-off between system performance and convergence speed. We show analytically that the algorithm converges quickly and provides asymptotically optimal performance as the capacity of DS units increases. We further study through simulation the algorithm performance over a wide range of parameter values and demonstrate that it is highly competitive over a greedy alternative.

Real-Time Welfare-Maximizing Regulation Allocation in Dynamic Aggregator-EVs Systems

2014-05-01

Abstract: The concept of vehicle-to-grid (V2G) has gained recent interest as more and more electric vehicles (EVs) are put to use. In this paper, we consider a dynamic aggregator-EVs system, where an aggregator centrally coordinates a large number of dynamic EVs to provide regulation service. We propose a Welfare-Maximizing Regulation Allocation (WMRA) algorithm for the aggregator to fairly allocate the regulation amount among the EVs. Compared with previous works, WMRA accommodates a wide spectrum of vital system characteristics, including dynamics of EV, limited EV battery size, EV battery degradation cost, and the cost of using external energy sources for the aggregator. The algorithm operates in real time and does not require any prior knowledge of the statistical information of the system. Theoretically, we demonstrate that WMRA is away from the optimum by O(1/V), where V is a controlling parameter depending on EVs' battery size. In addition, our simulation results indicate that WMRA can substantially outperform a suboptimal greedy algorithm.

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Unicast Multi-Antenna Relay Beamforming with Per-Antenna Power Control: Optimization and Duality

2013-12-01

We consider amplify-and-forward multi-antenna relaying between a single pair of source and destination under relay per-antenna power constraints. We design the optimal relay processing matrix to minimize the maximum per-antenna power budget for a received SNR target. With given transmit and receive beamformers at the source and destination, respectively, we first focus on the equivalent system with single-antenna source and destination. Although non-convex, we show that the optimization satisfies strong Lagrange duality and can be solved in the Lagrangian dual domain. We reveal a prominent structure of this problem, by establishing its duality with direct SIMO beamforming system with an uncertain noise. This enables us to derive a semi-closed form expression for the optimal relay processing matrix that depends on a set of dual variables, which can be determined through numerical optimization with a significantly reduced problem space. We further show that the dual problem has a semi-definite programming form, which enables efficient numerical optimization methods to determine the dual variables with polynomial complexity. Using this result, the reverse problem of SNR maximization under a set of relay per-antenna power constraints is then addressed. We then consider the maximum relay beamforming achievable rate under different combinations of antenna setups at source and destination. In particular, we generalize the duality to MIMO relay beamforming vs. direct MIMO beamforming, and establish the dual relation of the two systems for different multi-antenna setups at source and destination.

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Optimal Fixed Gain Linear Processing for Amplify-and-Forward Multichannel Relaying

2012-11-01

Abstract: In this correspondence, we consider the problem of linear processing design at the relay for amplified-and-forward relaying in a multichannel system. Assuming a fixed-gain power amplification at the relay, we study the linear processing structure to maximize the end-to-end achievable rate. For both the cases of relaying with or without direct path, we show that the optimal unitary processing matrix is of permutation structure, i.e., channel pairing is optimal. Furthermore, in each case, the explicit optimal channel pairing strategy is obtained based on sorting certain function of received SNR over the incoming and outgoing subchannels. This result is especially noticeable for the case with direct path, where the optimal linear processing was not known before under any power allocation. Specifically, we show that the pairing is according to the ordering of the relative SNR ratio on a subchannel over first hop to its direct path, and that of SNR strengths on subchannels over the second hop. Simulation results are presented to demonstrate the achievable gain of optimal channel pairing over non-optimal linear processing or no-pairing cases. It is also shown that the performance of channel pairing under the simple fixed-gain power allocation outperforms that under the traditional uniform power allocation.

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Prediction-Based Energy-Aware Relay Cooperation for Lifetime Maximization

2012-08-01

Abstract: In this paper, we investigate into the problem of energy-aware power allocation for a dual-hop cooperative relay network, and propose a prediction-based perceived lifetime (P-PLT) power allocation algorithm for network lifetime maximization. We obtain MMSE channel prediction for the future time slots and maximize perceived lifetime at each time slot to determine the power allocation. The P-PLT algorithm implements m-step channel prediction for power allocation, where m depends on the trade-off between performance and complexity. Compared to the existing non-prediction based energy-aware power allocation algorithm, which is solely based on the current channel state information, the proposed algorithm can provide substantial performance improvement as shown in the numerical results.

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A Semi-Closed-Form Solution to Optimal Distributed Beamforming for Two-Way Relay Networks

2012-03-01

Abstract: In this correspondence, we present a computationally simple semi-closed-form solution to the problem of designing distributed beamformer for two-way (bidirectional) multi-relay networks. In such a network, the relay nodes use amplify-and-forward relaying protocol to help two transceivers exchange information in a bidirectional manner. We consider a total power minimization approach to optimally find the relay beamforming weights and the transceiver transmit powers. This approach is based on the minimization of the total transmit power, consumed in the whole network, subject to SNR constraints at the two transceivers. We show that as far as the relay beamforming weight vector is concerned, this minimization problem is equivalent to the minimization of the total transmit power for a one-way relay network where the target SNR of the receiving transceiver is equal to the sum of the target SNRs of the two transceivers in the original two-way relay network. Based on this observation, we show that the relay beamforming weight vector can be obtained in a closed from given that an intermediate parameter, namely the transmit power of the transmitter in the equivalent one-way relay network, is available. This intermediate parameter is shown to be the solution to a one-dimensional optimization problem, and thus, it can be obtained using a simple bisection method. Our semi-closed-form solution not only reveals the structure of the optimal beamforming weight vector, but also leads to a one-dimensional search regardless of the number of relays. This provides the computational advantage over the gradient based numerical method of Havary-Nassab , where the gradient dimension reflects the number of relays.

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Jointly Optimal Channel Pairing and Power Allocation for Multichannel Multihop Relaying

2011-10-01

Abstract: We study the problem of channel pairing and power allocation in a multichannel multihop relay network to enhance the end-to-end data rate. Both amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are considered. Given fixed power allocation to the channels, we show that channel pairing over multiple hops can be decomposed into independent pairing problems at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal, where each relay pairs its incoming and outgoing channels by their SNR order. For the joint optimization of channel pairing and power allocation under both total and individual power constraints, we show that the problem can be decoupled into two subproblems solved separately. This separation principle is established by observing the equivalence between sorting SNRs and sorting channel gains in the jointly optimal solution. It significantly reduces the computational complexity in finding the jointly optimal solution. It follows that the channel pairing problem in joint optimization can be again decomposed into independent pairing problems at each relay based on sorted channel gains. The solution for optimizing power allocation for DF relaying is also provided, as well as an asymptotically optimal solution for AF relaying. Numerical results are provided to demonstrate substantial performance gain of the jointly optimal solution over some suboptimal alternatives. It is also observed that more gain is obtained from optimal channel pairing than optimal power allocation through judiciously exploiting the variation among multiple channels. Impact of the variation of channel gain, the number of channels, and the number of hops on the performance gain is also studied through numerical examples.

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Maximizing Lifetime in Relay Cooperation Through Energy-Aware Power Allocation

2010-08-01

Nominated for 2012 IEEE Signal Processing Society Young Author Best Paper Award. Abstract: We study the problem of optimal power allocation among relays for lifetime maximization in a dual-hop cooperative network operated by amplify-and-forward relays with battery limitation. We first formulate the optimization problem for global noncausal power allocation and present a solution based on dual decomposition. In the special case of static channels, we provide a closed-form solution for lifetime maximization, which simply requires equally distributing energy over time for each participating relay. Based on this, we then develop a perceived lifetime (PLT) power allocation strategy, which can be viewed as a causal implementation of the noncausal solution by considering only the current channel state information. We also present a minimum weighted total power (MWTP) strategy that does not depend on the prediction of future channel state. PLT and MWTP are compared through analysis and simulation, and it is demonstrated that both result in lifetime performance close to that of the noncausal optimal solution, and that they significantly outperform the conventional strategy of minimizing the total power per transmission, especially when the link conditions are asymmetric or initial energy levels nonuniform among relays. We further extend the proposed power allocation strategies to relay cooperation with multiple sources and discuss how different network configurations affect relay power sharing among the sources.

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