Research Projects  (Scholarships and funding for trips are readily available. Please email me if you are interested)

 

5G Lab

 

Precoding and detection algorithms for massive MIMO systems

 

            This project will investigate innovative precoding and detection techniques for massive MIMO systems that will play a big role in future wireless communication networks including satellite systems, wireless local area and cellular networks. The use of very large antenna arrays pose a major challenge to system designers and it is of fundamental importance to investigate ways of designing precoders and detectors for this purpose.  In particular, we will focus on the development of scalable algorithms and the analysis of the diversity order and sum rate of the studied techniques. 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.

 

Signal processing algorithms for ad hoc and wireless sensor networks

 

            This project will investigate novel distributed algorithms for power control, cooperation, physical-layer network coding and interference cancellation 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.

 

Cooperative diversity and resource allocation techniques for wireless networks

 

            Recently, cooperative communications were used to 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 multicarrier 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 in future networks. 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 multicarrier systems

 

            This project will investigate advanced adaptive channel estimation techniques and innovative equalization concepts for multicarrier (beyond 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 a block. The main applications will be 5G 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.

 

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 future wireless networks. 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.

 

Interference cancellation and decoding techniques with Network MIMO

 

            This project will investigate novel concepts of iterative interference cancellation 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, distributed antennas 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 signal processing algorithms exploiting prior knowledge and applications

 

This project will investigate innovative methods of adaptive signal processing for modeling both linear and nonlinear problems that exploit prior knowledge and consider their application to problems in communications and electronic systems. The activities will involve 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.

 

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.

 

Robust and low-complexity beamforming algorithms

 

This project will investigate robust adaptive beamforming algorithms and low-complexity strategies for implementing them in applications of sensing and wireless communications. We will consider both centralized and distributed scenarios along with realistic modeling methods for the sensor arrays. The activities will involve the use of constrained adaptive 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.

 

High-resolution direction finding algorithms

 

This project will investigate direction finding algorithms and low-complexity strategies for implementing them in applications of sensing, localisation and wireless communications. We will consider both centralized and distributed scenarios along with realistic modeling methods for the sensor arrays. The activities will involve the use of subspace tracking algorithms,  MUSIC and ESPRIT methods, 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.

 

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.