Abstract:
Multitrack detection with array-head reading is a promising technique proposed for next generation magnetic storage systems. The multihead multitrack (MHMT) system is cha...Show MoreMetadata
Abstract:
Multitrack detection with array-head reading is a promising technique proposed for next generation magnetic storage systems. The multihead multitrack (MHMT) system is characterized by intersymbol interference in the downtrack direction and intertrack interference (ITI) in the crosstrack direction. Constructing the trellis of a MHMT maximum likelihood (ML) detector requires knowledge of the ITI, which is generally unknown at the receiver. Furthermore, in a time-varying ITI environment, updating ML trellis labels using adaptively-generated ITI estimates could incur significant delay. In this paper, we propose one approach to solve these issues. The proposed detector uses a different trellis structure whose output labels are independent of the ITI level, with ITI-dependence appearing only in a scale factor used to suitably weight the computed path metrics in order to retain ML optimality. The detector formulation facilitates the design of a gain loop structure that can track the time-varying ITI and provide ITI estimates to adaptively adjust the weights in the path metric evaluation. Simulation results show that the proposed detector architecture with ITI estimation offers a substantial performance advantage over ML detection using a static ITI estimate.
Published in: IEEE Transactions on Communications ( Volume: 65, Issue: 4, April 2017)