Final Report Summary - REALMARS (Research on location estimation in multi-carrier systems)
Multi-carrier (MC) transmission, in particular orthogonal frequency division multiplexing (OFDM), is employed in various systems mainly due to its robustness. With the deployment of WiMAX and LTE systems, research in OFDM hastened. In OFDM systems, smart antenna systems with multiple transmit and receive antennae and location estimation are likely to be an area of interest. In recent years, adaptive antennae and array processing greatly impacted the performance of wireless communication systems. Also, location based services are gaining importance everyday increasing the need for better location estimation algorithms.
In this project, we investigate one of the most essential issues of adaptive antenna systems: the estimation of angles of arrival (AOA) for OFDM systems and its utilization in location estimation and development of location based services. Our objective is to design location estimation methodology for obtaining location estimates with high resolution in MC systems. In our work, we use basis selection (BS) algorithms, namely the matching pursuit (MP) family of algorithms for AOA and location estimation, by exploiting the sparsity property of AOA for OFDM. The main advantages of applying BS algorithms to this estimation problem are the decreased complexity and increased resolution. When OFDM systems are compared to single carrier systems in terms of AOA estimation, the main advantage is that for each subcarrier, the received phase depending on the angle of arrival is different. This results in diversity in the angle of arrival equations. In this work, we also concentrate on the advantage of this diversity and its improvement on the accuracy of location estimation systems as well as the location based services that can be developed based on the obtained accuracy levels. Furthermore, we investigate the interaction between the location estimation block and higher layers of the communication systems. We concentrate on estimation performance optimization.
A literature survey about application of sparse signal representation algorithms to communication systems for location estimation is completed for channel estimation and angle of arrival estimation algorithms. We have formulated the project problem definition and the proposed a novel location estimation system architecture. The proposed solution methodology makes use of the sparsity property of angle of arrivals of the received signals.
This sparse signal decomposition based location estimation process for multi-carrier systems and the associated algorithms is detailed in the project deliverable reports. Greedy heuristic sparse signal decomposition algorithms are implemented and their performances are investigated. Additionally, tree search structures are integrated to these algorithms for performance enhancement. Two types of tree search structures are considered; namely breadth-first search and depth-first search. The performances of these algorithms are evaluated using a component detection experiment, where we showed that the tree-search structure can drastically improve the system performance while keeping computational complexity at reasonable levels. The corresponding C# codes for both the algorithms are generated to build a code library. Under this architecture, Matching Pursuit based algorithms are added to the toolbox. The toolbox is designed in such a fashion that it will be easily utilized in the following stages of the project. A PCT patent application entitled "A Location Estimation System" is filed with identifier PCT/IB09/053645 based on the project.
Location estimation is one of the most important research areas in the wireless community. Its application range from location based cellular advertisements to emergency call locations. In the following phases of this project, the location estimation system will be combined with the user demands and other hardware requirements in cellular communication systems. By using the developped toolbox, system level simulations will be run; where Researcher's previous experience in the industry and implementation of the system in the wireless communications operator will enable realistic application scenarios.
In this project, we investigate one of the most essential issues of adaptive antenna systems: the estimation of angles of arrival (AOA) for OFDM systems and its utilization in location estimation and development of location based services. Our objective is to design location estimation methodology for obtaining location estimates with high resolution in MC systems. In our work, we use basis selection (BS) algorithms, namely the matching pursuit (MP) family of algorithms for AOA and location estimation, by exploiting the sparsity property of AOA for OFDM. The main advantages of applying BS algorithms to this estimation problem are the decreased complexity and increased resolution. When OFDM systems are compared to single carrier systems in terms of AOA estimation, the main advantage is that for each subcarrier, the received phase depending on the angle of arrival is different. This results in diversity in the angle of arrival equations. In this work, we also concentrate on the advantage of this diversity and its improvement on the accuracy of location estimation systems as well as the location based services that can be developed based on the obtained accuracy levels. Furthermore, we investigate the interaction between the location estimation block and higher layers of the communication systems. We concentrate on estimation performance optimization.
A literature survey about application of sparse signal representation algorithms to communication systems for location estimation is completed for channel estimation and angle of arrival estimation algorithms. We have formulated the project problem definition and the proposed a novel location estimation system architecture. The proposed solution methodology makes use of the sparsity property of angle of arrivals of the received signals.
This sparse signal decomposition based location estimation process for multi-carrier systems and the associated algorithms is detailed in the project deliverable reports. Greedy heuristic sparse signal decomposition algorithms are implemented and their performances are investigated. Additionally, tree search structures are integrated to these algorithms for performance enhancement. Two types of tree search structures are considered; namely breadth-first search and depth-first search. The performances of these algorithms are evaluated using a component detection experiment, where we showed that the tree-search structure can drastically improve the system performance while keeping computational complexity at reasonable levels. The corresponding C# codes for both the algorithms are generated to build a code library. Under this architecture, Matching Pursuit based algorithms are added to the toolbox. The toolbox is designed in such a fashion that it will be easily utilized in the following stages of the project. A PCT patent application entitled "A Location Estimation System" is filed with identifier PCT/IB09/053645 based on the project.
Location estimation is one of the most important research areas in the wireless community. Its application range from location based cellular advertisements to emergency call locations. In the following phases of this project, the location estimation system will be combined with the user demands and other hardware requirements in cellular communication systems. By using the developped toolbox, system level simulations will be run; where Researcher's previous experience in the industry and implementation of the system in the wireless communications operator will enable realistic application scenarios.