This research is directed to subspace signal processing for space-time processing of wireless transmissions to and from the internet, between fixed computers, or between computers and peripherals. It applies particularly to wireless channels that spread signals in space and time, thereby forcing the transceiver to adaptively trade off array and filter gain for diversity in order to achieve satisfactory performance.
The research (i) continues our exploitation of the connection between optimization theory and filtering; (ii) advances the state-of-the-art in reduced rank filter design for space-time adaptive processing (STAP); and (iii) applies the results to space-time wireless communication, imaging, and beamforming. The aim is to couple transmitter design to receiver design in wireless communication systems by showing how code design and power control directly influence the cost, complexity and convergence of receivers within a wireless network.
The project consists of these elements: (i) downlink cooperative transceiver optimization, using code design, power control, and the vector conjugate gradient Wiener filter to achieve warp convergence; (ii) uplink transceiver optimization, using the matrix conjugate gradient Wiener filter to achieve convergence in one step.
