Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
175 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Multihead Multitrack Detection with Reduced-State Sequence Estimation (1602.05511v1)

Published 17 Feb 2016 in cs.IT and math.IT

Abstract: To achieve ultra-high storage capacity, the data tracks are squeezed more and more on the magnetic recording disks, causing severe intertrack interference (ITI). The multihead multitrack (MHMT) detector is proposed to better combat ITI. Such a detector, however, has prohibitive implementation complexity. In this paper we propose to use the reduced-state sequence estimation (RSSE) algorithm to significantly reduce the complexity, and render MHMT practical. We first consider a commonly used symmetric two-head two-track (2H2T) channel model. The effective distance between two input symbols is redefined. It provides a better distance measure and naturally leads to an unbalanced set partition tree. Different trellis configurations are obtained based on the desired performance/complexity tradeoff. Simulation results show that the reduced MHMT detector can achieve near maximum-likelihood (ML) performance with a small fraction of the original number of trellis states. Error event analysis is given to explain the behavior of RSSE algorithm on 2H2T channel. Search results of dominant RSSE error events for different channel targets are presented. We also study an asymmetric 2H2T system. The simulation results and error event analysis show that RSSE is applicable to the asymmetric channel.

Citations (8)

Summary

We haven't generated a summary for this paper yet.