Research Projects (please email me if you are interested)

Efficient multidimensional signal processing algorithms for wireless communications applications

This project will investigate innovative methods of multidimensional signal processing algorithms for wireless communications. One important application is interference mitigation using co-located and distributed antenna arrays. The activities will deal with the use of cutting-edge signal processing algorithms, low-rank decompositions, optimization tools and matrix computations. The work will involve the development of system models using linear algebra, simulation tools with MATLAB, FPGA and analytical approaches.

This project is in collaboration with Prof. Martin Haardt from the Ilmenau University of Technology, Germany (http://www.tu-ilmenau.de/crl ) and can be carried out either in Germany, UK or both. Scholarships and funding for trips are readily available.

Cognitive approaches to adaptive signal processing and applications

This project will investigate innovative methods of adaptive signal processing for modeling both linear and nonlinear problems that appear in communications, control, electronic systems, and biological systems. The activities will consider the use of cognitive techniques, combinations, low-rank decompositions, optimization tools and matrix computations. The work will involve the development of system models using linear algebra, simulation tools with MATLAB, FPGA and analytical approaches.

This project is in collaboration with Prof. Vítor Nascimento from the University of São Paulo (USP), Brazil (http://www.lps.usp.br/~vitor/index-eng.html ) and can be carried out either in Brazil, UK or both. Scholarships and funding for trips are readily available.

Advanced distributed communications and signal processing algorithms for ad hoc and wireless sensor networks

This project will investigate novel distributed algorithms for power control, cooperation and interference cancellation using spread spectrum techniques in ad hoc and wireless sensor networks. The goal is to devise low-complexity and effective algorithms for increasing the capacity and the reliability of these networks. The activities will involve the development of system models, simulation tools and analytical approaches.

Compressive sensing algorithms using subspace methods

There has a growing recent interest in compressive sensing techniques for solving numerous problems in communications, signal processing, radar and sonar systems. In fact, compressive sensing techniques are important mathematical tools that allow the solution of problems with increased accuracy and lower computational complexity. In this project, we will investigate advanced subspace tracking algorithms and iterative thresholding methods with multipass strategies for solving problems that arise in a variety of applications such as system identification, channel estimation in wireless communications, image deblurring and filtering problems. The main goal is to devise low-complexity and effective algorithms with increased accuracy and low reconstruction errors. The activities will involve the development of system models using linear algebra, simulation tools and analytical approaches.

Cooperative diversity and resource allocation techniques for wireless networks

Recently, it has been shown that cooperative communications can increase the capacity and the reliability of wireless networks by exploiting a novel form of diversity via cooperation. This project will examine novel cooperative diversity techniques in conjunction with resource allocation algorithms for wireless networks. In particular, we will consider narrowband and OFDM systems and will investigate novel distributed space-time/frequency coding, physical-layer network coding, resource allocation and partner selection algorithms for improving the performance and the capacity of wireless networks. The activities will be based on mathematical formulation, simulation and analytical tools.

Advanced error-control coding techniques and applications

In this research project, we will investigate novel encoding and iterative decoding techniques for use in conjunction with Turbo codes, low-density parity-check (LDPC) codes and repeat accumulate codes. Specifically, we will examine novel forms of irregular encoding and more efficient iterative decoding algorithms such as improved versions of the M-best algorithm and list decoding. Applications in wireless networks including multi-antenna systems and multicarrier communications will be considered along with code design. The research activities will be based on mathematical modeling, and the building of simulation and analytical tools.

Precoding, scheduling and limited-feedback algorithms for multiuser MIMO systems

This project will investigate innovative techniques for significantly improving the capacity and the performance of multiuser MIMO networks such as WIMAX and 3GPP-LTE. In order to manage the high-level of interference in these systems, we will devise novel precoding and scheduling algorithms for the downlink of MIMO systems with multiple users and cells. The existence of multiple cells make the design of the precoders and schedulers significantly more challenging and we will examine novel approaches to this scenario. Since these algorithms require the channel state information (CSI), we will also investigate innovative ways of encoding the CSI and sending it via low-rate channel. In particular, we will focus on the scenarios with time-varying channels where limited feedback is quite challenging. The research activities will be based on the development of a system model, the derivation of algorithms, and the building of simulations and analytical tools.

Low-complexity channel estimation and equalization techniques for OFDM systems

This project will investigate advanced adaptive channel estimation techniques and innovative equalization concepts for OFDM systems in time-varying scenarios. We will examine strategies to model time-varying channels with basis expansion models and techniques to mitigate the inter-carrier interference that arises due to channel variations within an OFDM block. The main applications will be LTE advanced and DVB systems. The research activities will be based on the formulation of system and data models with linear algebra, simulations tools and analytical development and analysis.

Low-complexity interference alignment algorithms for wireless networks

This project will investigate innovative strategies for interference alignment in wireless networks that have multiple transmit and receive antennas as well as relays. We will consider strategies for spatial processing based on the alignment of interference via iterative receive and transmit filters with the aim of improving the BER and the sum-rate performances. We will also examine how resource allocation strategies that adjust the power levels and the selection of antennas can help improve the performance and increase the capacity of the network. The main application will be ad hoc and wireless sensor networks. The research activities will be based on the formulation of system and data models with linear algebra, simulations tools and analytical development and analysis.

Bit-interleaved coded modulation (BICM) and iterative processing techniques for wireless networks

This project will investigate novel concepts of BICM and iterative processing techniques for wireless networks such as WIMAX, UMTS and future systems. We will investigate appropriate mappings and interleaving strategies for BICM schemes, use of side information and innovative code designs. The proposed techniques will be considered in scenarios with relaying, block fading channels and MIMO systems. The research activities will consider the development of a system and data model, the building of simulations and analytical tools.

Joint iterative interference cancellation, data detection and decoding techniques with Network MIMO

This project will investigate novel concepts of joint iterative interference cancellation, data estimation and decoding with network MIMO in future wireless systems. The main idea is to formulate the problem of interference cancellation, parameter estimation and decoding as a joint optimisation problem. We will devise novel cost-effective algorithms for implementing the proposed approach in the uplink of MIMO networks. One significant challenge is how to estimate the channel of co-channel users and we will examine novel ways of determining these parameters. We will then apply the novel algorithms to MIMO systems with multiple cells and evaluate the performance of the proposed algorithms against the best methods available. The research activities will be based on the development of a system and data model, the building of simulations and analytical tools.

Adaptive reduced-rank filtering algorithms and applications

This project will investigate novel adaptive reduced-rank signal processing algorithms with high performance and flexible complexity. We will examine novel dimensionality reduction techniques and improved modeling of time-varying processes. In particular, the novel algorithms will be derived with flexible requirements provided by variable data-reuse properties and innovation check recursions. We will devise a novel framework for the design and analysis of these algorithms and will test them for typical adaptive filtering applications such as echo cancellation, beamforming and channel estimation in wireless communications. The research activities will be based on the description of a system model, the building of simulations and analytical tools.

Reduced-rank array signal processing algorithms and applications

This project will investigate novel reduced-rank array signal processing algorithms for beamforming and direction of arrival (DoA) estimation in applications with antenna arrays. We will examine novel rank reduction techniques and the use of knowledge-aided techniques for improving the performance of existing algorithms. We will study the application of the novel array-based algorithms to beamforming and DoA estimation with various array geometries such as circular, planar and rectangular. The research activities will be based on the development of a system and signal model with various array geometries, simulations tools and analytical development and analysis.

Signal processing techniques for synchronization and interference management in UWB systems with multiple antennas

This project aims to develop novel techniques for joint synchronization and interference management in UWB systems with multiple antennas. We will investigate novel cost-effective approaches for addressing these problems via a joint formulation of the problems of synchronization, interference management and iterative decoding. The research activities will be based on the formulation of a signal model with various array geometries, simulations tools and analytical development and analysis.

Advanced space-time processing algorithms for MIMO radar and sonar systems

This project will investigate a novel joint space-time processor for MIMO radar and sonar systems. We will investigate novel reduced-rank signal processing algorithms for multidimensional data and the use of prior knowledge for devising high performance target detection algorithms. The research activities will be based on the development of a signal model, simulations tools and analytical development and analysis.

Kernel-based adaptive signal processing algorithms and applications

This project will investigate signal modeling problems that arise in the design power amplifiers and time series with the use of kernel-based adaptive signal processing algorithms. An investigation into variable structures and low-rank techniques using kernels will be carried out. We will examine novel kernel-based adaptive signal processing algorithms with attractive tradeoffs between performance and complexity for modeling and learning. The research activities will be based on the development of system models with linear algebra, simulations tools and analytical development and analysis.