The proposed project aims at the design and implementation of low complexity digital pre-distortion (DPD) algorithms for multiband and multiple input multiple output (MIMO) wireless transmitters. The power amplifier (PA) is one of the major sources of power dissipation in wireless base stations. The DPD techniques enable the PA to operate in a more efficient power level resulting in more energy efficient wireless networks.
Network stochastic control is considered as a primary goal in the design of emerging wireless networks. One of the objectives in the stochastic control of wireless networks is to enable crosslayer designs to achieve stochastically optimal resource allocation in the physical and MAC layers. Different stochastic performance criteria can be considered in the optimal control of wireless networks. Delay is one of the most challenging ones and has been addressed far less in the literature.
Finite Difference Time Domain (FDTD) simulations allow researchers to model complex devices and systems based on integrated micro/nano structures. The electrodynamic behaviour predicted by FDTD simulations match very well with the real physical systems, which significantly accelerates the development of novel devices. However, there are limitations in existing FDTD techniques to model metal nanoparticles on sub-100 nm length- scales, which are of great interest to research and industry.
Electrochemical reduction of carbon dioxide (ERC) is a process by which carbon dioxide (CO2) is converted into valuable chemical products via chemical reactions driven by electricity. The goal of this project is to fabricate and test catalytic metal electrodes to increase the efficiency of ERC reactors converting carbon dioxide from industrial exhaust gas streams into formic acid.
In this project we intend to find an abstract understanding of heterogeneous networks (HetNets. Our main focus is the small cell networks based on LTE-A and WiFi systems. We will start by investigating simple and efficient resource management algorithms in such networks and attempt to find a simplified model for the quality of service (QoS) in such networks. This model will be interfaced with a software tool already developed at Siradel and used to clarify the expected performance of a HetNet in a given wireless environment.
The mobile traffic has been increased significantly both in volume and in the variety of services in the new generation of broadband mobile networks. This made mobile operators to think about new approaches of data forwarding in wireless cellular networks. With this motivation, mobile operators have started to deploy WiFi to enhance the cellular network capacity. This is done by providing a seamless traffic steering between WiFi and cellular network.
he goal of this project is to achieve high quality real-time motion deblurring for images captured by cameras mounted on mobile devices. First, we will propose a novel two-camera technique that exploits the trade-off between spatial and temporal resolutions in capturing the photo with the camera movement information to be used in the deblurring process. Second, we will introduce new point-spread function (PSF) estimation algorithms by employing the motion information captured by the two-camera imaging device. Third, we will develop new deconvolution algorithms suitable for mobile devices.
he goal of this project is to achieve high quality real-time motion deblurring for images captured by cameras mounted on mobile devices. First, we will propose a novel two-camera technique that exploits the trade-off between spatial and temporal resolutions in capturing the photo with the camera movement information to be used in the deblurring process. Second, we will introduce new point-spread function (PSF) estimation algorithms by employing the motion information captured by the two-camera imaging device. Third, we will develop new deconvolution algorithms suitable for mobile devices.
In this project, new storage approaches for big data will be explored. Key point is the efficient use of modern hardware, especially modern storage technology such as SSDs. These new technologies have highly improved performance in comparison to traditional hardware. However, classical data structures and algorithms can not directly be applied due to the different characteristics of these devices. Also, the high cost of the new technology makes their exclusive use uneconomical in many cases.
In this project, I focus on low-delay error correction codes for streaming data at the application layer (c.f. Figure 1). Forward error correction codes designed for streaming sources require that (a) the channel input stream be produced sequentially from the source stream (b) the decoder sequentially reconsructs the source stream as it observes the channel output. Naturally both the optimal structure and the fundamental limits of streaming codes are expected to be different from classical error correction codes.
