Communications and Signal Processing Research Group - PhD Research Projects

PhD research projects are currently available in the following areas. Some projects listed may also be suitable for the MSc by Research – please contact the member of academic staff involved if you are interested in the MSc by Research. Please note that funding opportunities, if available, are advertised on our Funding page.

Advanced Codes and Turbo Techniques

Cognitive and Green Communications

Wireless Sensor Networks (WSNs)

MIMO and Spread Spectrum Systems

Signal Processing

Audio Lab

 

Adaptive coded MIMO-OFDM systems

Prof Alister Burr, email: alister.burr@york.ac.uk

The combination of MIMO and OFDM technologies for broadband wireless communications seems likely to dominate future standards like WiFi, WiMAX, and other fourth generation wireless systems. The efficiency of such systems can be greatly increased by making it adaptive to the wireless channel. Moreover FEC coding using codes such as turbo and LDPC codes can also greatly enhance performance. The research will develop new schemes based on these technologies, consider reduced complexity detection and decoding strategies, and also evaluate the overall improvement in system capacity resulting from adaptive coded MIMO-OFDM. This will also require the development of resource allocation and scheduling methods.

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Cognitive Radio for Multiple Heterogeneous Systems employing Smart Antennas (also suitable for MSc by research)

Dr David Grace, email: david.grace@york.ac.uk

This project will examine how smart antennas can be used with multiple systems (e.g. terrestrial ad hoc, terrestrial cellular, high altitude platform) sharing pooled spectrum. Spectrum assignment strategies will be developed which take into account dynamic changes in the beam pattern of both transmit and receive antennas. The impact of the degree of control information exchange required between the different systems, possibly owned by multiple operators will be addressed. The benefits and drawbacks of such an approach over conventional spectrum assignment methods will be evaluated. A mixture of simulation and analysis will be used to assess performance. Game theory and Markov analysis will be particularly important analytical tools.

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Cooperative MIMO techniques for wireless mesh networks

Prof Alister Burr, email: alister.burr@york.ac.uk

Future wireless networks are likely to consist of very large numbers of cheap, low-power nodes forming very large mesh networks, instead of the conventional cellular or access point architecture that dominates today. This sort of architecture will also be used in wireless sensor network, "smart grid" networks, and similar machine-to-machine communication networks. It is well known, however, that in large wireless networks congestion rapidly builds up, so that the capacity per node decreases with network size. The project will investigate the application of cooperative MIMO techniques to such networks, allowing groups of nodes to cooperate to form "virtual MIMO" transmitters/receivers, and thus helping to overcome this bottleneck. It will make use of distributed source coding, wireless network coded modulation, and cooperative MIMO techniques, with iterative methods applied to detection, decoding and channel estimation at intermediate nodes.

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Crosslayer Design for Cognitive Networks (also suitable for MSc by research)

Dr David Grace, email: david.grace@york.ac.uk

This project will examine how crosslayer design can be used to improve the performance of future cognitive ad hoc and sensor networks. Spectrum assignment and routing strategies will be developed which take into account dynamic changes in traffic flow throughout a network. The impact of the degree of control information exchange required between multiple networks and nodes sharing the pooled spectrum, possibly owned by multiple operators, will be addressed. The benefits and drawbacks of such an approach over more traditional ad hoc network techniques will be evaluated. A mixture of simulation and analysis will be used to assess performance. Game theory and Markov analysis will be particularly important analytical tools.

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Cross-Layer Protocol Development for Ad Hoc Networks

Dr Paul Mitchell, email: paul.mitchell@york.ac.uk

This research project will explore cross-layer protocol design for ad hoc networks. Protocols that combine medium access control and routing functionality will be developed for energy-constrained ad hoc networks, where great savings in energy and capacity can be made through the use of common signalling mechanisms for both medium access and routing functionality. Simulation and/or analytical models will be developed and the benefits of the proposed techniques evaluated through comparison with current state of the art protocols.

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Development and FPGA design of efficient sparse recovery techniques

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

This project will deal with developing innovative sparse recovery methods that can be efficiently implemented in real-time systems, e.g. on FPGAs. The sparse recovery methods have recently become very popular in many applications of signal processing, including modern communications systems, image and audio processing, smart antennas, sensor networks, underwater sonar systems, etc. The activity will be based on using modern methods of the optimization theory, linear algebra, mathematical statistics, as well as on using simulation tools such as Matlab, and FPGA design tools.

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Efficient adaptive equalizers for wireless communications applications

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

This project will develop and investigate novel low-complexity adaptive methods for equalization in wireless communications systems. These will include multiuser communications, systems with multiple transmit and multiple receive antennas, communications in fast-varying fading channels. The activities will deal with the use of cutting-edge signal processing algorithms, optimization tools and matrix computations. The work will involve the development of system models using simulation tools with MATLAB, analytical approaches, and possibly FPGA design.

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Efficient signal processing for underwater acoustic communication systems

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

The aim of this project is to develop efficient signal processing techniques for reliable high data rate underwater communications. With increase of the interest in exploitation of sea and ocean resources as well as the environment monitoring, underwater communications has been recently attracting significant attention. As radio waves cannot propagate underwater at large distances, acoustic waves are used in practice. However, underwater acoustic propagation results in specific distortions of signals that should be compensated for before reliable demodulation can be achieved. These include the multipath interference and Doppler effect. The project will develop and investigate innovative signal processing techniques that can estimate and compensate for the signal distortions, increase the data transmission rate and improve the performance of underwater communication systems.

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Implementation of soft-input, soft-output detectors and decoders using FPGA

Prof Alister Burr, email: alister.burr@york.ac.uk

Many emerging wireless communication standards, such as WiMAX and 3GPP LTE, use iteratively-decoded error correcting codes, such as turbo-codes and LDPC, based on soft-input, soft-output (SISO) component decoders. Moreover iterative techniques can be used to improve the performance of other functions, such as detectors and equalisers, and hence SISO detectors/equalisers may also be required. However SISO decoders may be complex and expensive to implement. The project will develop implementations of such components using field programmable gate arrays (FPGA), focusing firstly on minimising the gate count required, and secondly on maximising speed.

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Learning and Reasoning Strategies in Cognitive Radio (also suitable for MSc by research)

Dr David Grace, email: david.grace@york.ac.uk

This project will explore how different learning and reasoning strategies should be applied to cognitive radio based systems. Strategies could include reinforcement-based learning, possibly applied using game theoretic techniques. By modelling a realistic wireless communications environment, the purpose of the project will be to show how, by applying this form of intelligence, it is possible to improve the flexibility and usage of pooled radio spectrum, both on a local and system wide basis. The project will establish where the learning/reasoning should best reside (nodes and/or network), and also the degree of control information exchange required between nodes. A mixture of simulation and analysis will be used to assess performance.

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Low power medium access control for wireless sensor networks

Dr Paul Mitchell, email: paul.mitchell@york.ac.uk

This research project will investigate issues associated with the development of energy-efficient medium access control (MAC) protocols for wireless sensor networks, identifying key sources of energy waste. The performance of the IEEE 802.15.4 MAC protocol will be studied through analysis, simulation in OPNET Modeler and/or practical implementation in MICA2 devices. Novel ideas will be explored to improve the performance of the 802.15.4 MAC layer for multi-hop communication in a wireless sensor network.

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Modelling of underwater acoustic communication systems

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

The aim of this project is the modelling of underwater acoustic communication systems. This will be based on using state-of-the-art software for modelling the underwater acoustic propagation and building new simulation tools that would allow one to analyse different communication systems in specific ocean environments. The simulation tools will be verified using real data from ocean experiments.

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Modelling of underwater acoustic data transmission for moving transmitter/receiver

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

The project will continue research in the Communications Research Group of the University of York on modelling of data transmission to/from underwater moving platforms. The aim is to develop computationally-efficient simulation tools for modelling acoustic signal propagation with moving transmitter/receiver. One of the approaches considered will be the use of multicore computational platforms. The simulation tool(s) will be verified on real data from sea experiments.

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Multiuser MIMO techniques with imperfect channel information

Prof Alister Burr, email: alister.burr@york.ac.uk

MIMO provides a means of serving multiple users in the same spectrum - however on the downlink MU-MIMO requires accurate channel state information (CSI) at the transmitter. On rapidly time varying channels CSI may be out of date at the base station. The project will research means for overcoming this problem, considering on the one hand MU-MIMO precoding methods which provide increased robustness to CSI errors, and on the other hand developing improved MIMO channel estimation and prediction techniques. The project will be implemented largely using Matlab, based on state of the art MIMO channel models.

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Network MIMO-OFDMA for next generation wireless broadband access

Prof Alister Burr, email: alister.burr@york.ac.uk

Next generation wireless telecommunication networks will need to provide greatly increased capacity density. A vital technique for achieving this is likely to be Network MIMO, in which multiple base stations collaborate to provide a single virtual MIMO terminal with an increased number of antennas. This approach is already included in next generation standards, but there are many problems remaining to be overcome. In particular it relies on the availability of a high capacity and reliable backhaul network, which may be difficult to provide when only wireless links are available for the backhaul. When large numbers of base stations collaborate it may also result in excessive complexity. The proposed project will investigate the combination of OFDMA, widely used for multiple access, with network MIMO to optimally serve a user terminal at minimal complexity. It may also involve wireless network coding techniques. It will make use of analytical and simulation techniques, based on Matlab, together with network level simulation software developed at York.

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Optimised coded MIMO schemes with iterative decoding and detection

Prof Alister Burr, email: alister.burr@york.ac.uk

Serially-concatenated coding schemes which can be iteratively decoded are capable of approaching closely to the Shannon capacity limit for wireless channels, including MIMO wireless channels. MIMO techniques in turn are able to significantly increase link capacity, and are employed in most emerging wireless standards. The research will investigate improved and low complexity MIMO detection systems operating in serial concatenation with outer FEC codes, using iterative decoding and detection. It will make use of EXIT curve matching techniques to optimise the joint performance.

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Physical Layer Network Coding for Cooperative Wireless Networks

Prof Alister Burr, email: alister.burr@york.ac.uk

Network Coding is a new technique for wireless relaying or multi-hop networks in which data received from multiple sources at intermediate nodes is combined and re-coded, instead of being simply selected and forwarded. It has the potential of significantly increasing throughput in multiuser wireless networks: for example it can readily double the capacity of a pair of terminals communicating with one another via a relay. However its application in wireless networks is more complex because of the inherent interference between links, and problems such as fading. The project will exploit a new approach to physical layer network coding, known as soft network-coded modulation, introduced at York in collaboration with other researchers, to find both the limits on the capacity of this approach, and practical implementations of it.

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Reinforcement Learning Based Carrier Sense Multiple Access

Dr Paul Mitchell, email: paul.mitchell@york.ac.uk

This research project will explore the application of reinforcement learning to the Carrier Sense Multiple Access (CSMA) family of medium access control protocols. The ability of nodes to learn from their experience transmitting on a channel offers great potential in reducing contention and increasing channel throughput. Simulation and/or analytical models will be developed and the benefits of the proposed techniques evaluated through comparison with current state of the art protocols.

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Self-Organising Wireless Sensor Networks based on Machine Learning

Dr Paul Mitchell, email: paul.mitchell@york.ac.uk

This research project will explore the use of machine learning techniques to assist with self-organisation in wireless sensor networks. The ability of nodes to learn from their interactions with the radio environment provides scope to significantly enhance their ability to self-organise and adapt to changes in the environment. Important processes where this approach may offer benefit include the formation of clusters in a fully distributed network and the discovery and selection of routes through a network based on a suitable metric. Simulation and/or analytical models will be developed and the benefits of the proposed techniques evaluated through comparison with current state of the art protocols.

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Sparse adaptive algorithms

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

Recently, there has been significant interest to developing novel computationally efficient adaptive algorithms based on sparse recovery principles. These can be used in such applications as acoustic echo cancellation, active noise control, channel estimation and equalization in communication systems, adaptive antenna arrays, and many others. The project will be based on the recent research within the Communications Research Group of the University of York in developing sparse recovery techniques and low complexity algorithms. In this project, such mathematical tools as optimization methods and linear algebra will be used. The adaptive algorithms will be analysed analytically and by simulation in Matlab. The developed algorithms can be also implemented on DSP and/or FPGA design platforms.

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Spectrum Charging in Cognitive Radio Networks (also suitable for MSc by research)

Dr David Grace, email: david.grace@york.ac.uk

This project will investigate how spectrum can be charged for in cognitive radio based systems. The project will examine the most effective degree of centralisation required to complete charging transactions, while balancing usability at the radio system level. Coupled with this will be an investigation into techniques that would allow primary users to resell unused spectrum, comparing them with bandwidth broker techniques. The effectiveness of spectrum price levels to control or shape demand will also be investigated. It is likely that auction techniques will prove particularly useful. A mixture of simulation and analysis will be used to assess performance. Linear programming, set theory and game theory will be particularly important analytical tools.

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Underwater acoustic localization

Dr Yuriy Zakharov, email: yury.zakharov@york.ac.uk

The project will develop innovative signal processing methods for underwater acoustic localization. This will be based on using the matched-field approach as well as recently developed methods for sparse signal representation. The work will further develop methods that have been recently proposed in the Communications Research Group of the University of York. New signal processing techniques developed in the project will be verified on real data from sea experiments.

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Admissions Enquiries: Helen Fagan
Postgraduate Admissions Tutor: Dr Steve Smith
Tel: (+44) 01904 324485

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