Sparsifying Dictionary Analysis for FIR MIMO Channel-Shortening Equalizers

Abubakr O. Al-Abbasi1, Ridha Hamila, Waheed U. Bajwa2, Naofal Al-Dhahir3

  • 1Qatar University
  • 2Rutgers University
  • 3Ut-Dallas

Details

11:30 - 12:45 | Wed 6 Jul | Salisbury A | S12.3

Session: Role of Sparsity in Communication

Abstract

In this paper, we propose a general framework that transforms the problems of designing sparse finite-impulse response channel-shortening equalizers and target impulse response filters for multiple antenna systems into the problems of sparsest-approximation of a vector in different dictionaries. Additionally, we compare several choices of the sparsifying dictionaries in terms of the worst-case coherence metric, which determines their sparsifying effectiveness. Finally, the significance of our proposed approach is demonstrated through numerical experiments.