An Optimal Signal Processing Algorithm/System That Will Allow Complex Signals to Adapt to Time-Changing/Unknown

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Block diagram showing application of the inventive complex individually adaptive/independent component analysis (complex IA-ICA) method applied to a wireless communication system
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Researchers
Wasfy Mikhael, Ph.D.
Raghuram Ranganathan
Managed By
Andrea Adkins
Assistant Director 407.823.0138
Patent Protection

Adaptive methods employing optimal convergence factors for processing complex signals and systems

US Patent 8,144,759 B2

Algorithms, systems and methods for processing information/signals with speed and accuracy by employing a higher degree of freedom in environments that are rapidly changing or time varying.

Signal processing in the world of communications, is the analysis, interpretation and manipulation of signals (e.g., audio, images, radio signals, biological data, etc.). In wireless systems, it is common to utilize complex signals when transferring data. A complex signal consists of two or more real signals (e.g., audio or images) which are combined to occupy the same space and time in order to transfer larger amounts of data more efficiently. Unfortunately, accurately reconstructing these complex signals is extremely difficult since such signals suffer from noise and distortion as they are propagated. Additionally, many communications systems suffer from significant limitations within dynamic environments because their medium of transport is constantly or abruptly changing. Hence a need exists for these systems to adapt to the effects of their changing environment which may interfere with the desired signal.

Technical Details

One example of such is the proliferation of mobile radios, or the possibility of transmitting and receiving data from highly mobile stations to a central computer database. If the transmitter is mobile (i.e., located in a car), the signal is sent over an atmospheric radio channel, and the propagation (or movement) path between the transmitter and the fixed receiver is constantly changing. This causes several parameters, such as the power of the received signal and its propagation loss, to become time varying /unknown to the system, rendering the system’s performance unacceptable. Current technologies and algorithms used in retrieving the desired signals from these situations are ineffective because their systems are based on the assumption that the environment is fixed or slowly changing. UCF engineers have designed a more efficient algorithm that employs factors which take into account the degree a signal moves or propagates in a rapidly changing environment, while effectively suppressing signal interference.

Benefits

  • Enables the fast and accurate processing of complex signals which propagate through time varying and dynamic environments
  • Significant increase in interference suppression
  • Increased convergence speed and accuracy

Applications

  • Interference suppression
  • Telecommunications
  • Military
  • System identification
  • System modeling
  • Audio, speech, and video processing