Novel Minimum Total-Model-Order Determination for the Inverse of Mixing-Phase Systems and Applications of Communications Equalization

The inverse system approximation using the finite impulse responses (FIR) and the corresponding model-order determination are important to a broad area of communications and signal processing applications. However, there exists no algorithm to determine the minimum total model-order of the appropriate truncated inverse filter to achieve a specified Li approximation error. In this paper, we design a novel model-order determination algorithm, which can be utilized for efficient dynamic memory allocation on cost-effective transceiver platforms since such a minimum total-model-order is proportional to the memory usage for implementing any inverse filter (equalizer).