Multihead Multitrack Detection with ITI Estimation in Next Generation Magnetic Recording System

TL;DR

This paper introduces a modified maximum likelihood detector for multitrack magnetic recording systems that adaptively estimates intertrack interference, improving performance when ITI varies over time.

Contribution

A novel ML detector with a trellis independent of ITI level and an ITI estimation loop, enabling dynamic tracking of ITI changes in multitrack magnetic recording.

Findings

The proposed detector outperforms static ITI ML detectors in simulations.

The trellis structure remains unaffected by ITI variations.

Adaptive ITI estimation enhances detection accuracy under changing interference conditions.

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 (ISI) 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. In addition, to retain efficiency, the ML detector requires a static estimate of the ITI, whose true value may in reality vary. In this paper we propose a modified ML detector on the $n$-head, $n$-track ($n$H$n$T) channel which could efficiently track the change of ITI, and adapt to new estimates. The trellis used in the proposed detector is shown to be independent of the ITI level. A gain loop structure is used to estimate the ITI. Simulation results show that the proposed detector offers a performance advantage in settings where complexity constraints limit the traditional ML detector to use a static ITI estimate.