The aim of the paper is to present the results of research into Component-Based software development by providing a specification mechanism allowing searching for components in a component repository. A new component classification framework is proposed based on which a Component Description Manager has been designed and implemented. The classification framework combines domain knowledge, ontological information and some semantics to allow descriptions of components to be constructed in a consistent, yet informative way. The Component Description Manager consists of the classification framework and a repository of component descriptions constructed using this framework. This new approach is compared to alternative component repositories and marketplaces.

This paper proposes an approach for estimating the spatial and polarization angles of mixed-targets in bistatic MIMO radar. Mixed-targets mean the combination of uncorrelated, partially correlated, and groups of coherent targets. The approach resolves rank deficiency of received signal covariance matrix and then exploits the ESPRIT-based method for estimating the angles of directionof-departure (DOD) and direction-of-arrival (DOA). This paper also presents an analytical review and necessary conditions for resolving the rank deficiency under various scenarios of the MIMO radar. Simulation results show the effectiveness of the proposed approach.

In this research work, a novel enhanced large scale multi-input multi-output (MIMO) approximate message passing (LAMA) based optimal data detection is proposed for large scale MIMO systems. Existing LAMA and sub-optimal detection techniques suffer from iteration complexity and performance loss in finite dimensional systems due to large scale user fading. To over come these, Gram matrix and message damping techniques are incorporated in the traditional LAMA. The effectiveness of the proposed enhanced LAMA and existing techniques are analyzed with 64, 32 and 16 user antennas, 256, 128, 64 and 16 base station elements with 64QAM, 16QAM, QPSK and BPSK. The simulation results show that the proposed enhanced LAMA gives superior performance when compared to existing matrix inversion methods such as Gauss sidle and Neumann, box techniques such as optimal co-ordinate descent and alternating direction method of multipliers based on the infinity norm, minimum mean square error and LAMA.