Adaptive Set - Membership Signal Processing in CommunicationsShirish

| A novel ltering methodology, recently introduced as a viable tool for adaptive signal processing , is presented for applications to interference suppression in communication systems. This technique is based on bounding the worst-case lter error by a designer-speciied value. I. Introduction This paper presents some recent work on alternative method-ologies for ltering based on a deterministic error speciication with applications to emerging communications technologies. Most problems of interference suppression in present and future generation communication systems require the use of high performance (in terms of tracking, accuracy and robustness) and low-complexity adaptive signal processing methodologies. An attractive solution, which ooers performance beyond what is possible by conventional techniques is the so-called Set-Membership Filtering (SMF) paradigm. These methods give rise to an admissible set of lters which meet a certain bounded error requirement. This formulation is an extension of the theory of Set-Membership Identiication (SMI) 1] so as to handle: system identiication with possibly unbounded noise, and model independent, hence general, ltering problems.