EQUALISATION TECHNIQUES FOR MULTI-LEVEL DIGITAL MAGNETIC RECORDING

A large amount of research has been put into areas of signal processing, medium design, head and servo-mechanism design and coding for conventional longitudinal as well as perpendicular magnetic recording. This work presents some further investigation in the signal processing and coding aspects of longitudinal and perpendicular digital magnetic recording. The work presented in this thesis is based upon numerical analysis using various simulation methods. The environment used for implementation of simulation models is C/C + + programming. Important results based upon bit error rate calculations have been documented in this thesis. This work presents the new designed Asymmetric Decoder (AD) which is modified to take into account the jitter noise and shows that it has better performance than classical BCJR decoders with the use of Error Correction Codes (ECC). In this work, a new method of designing Generalised Partial Response (GPR) target and its equaliser has been discussed and implemented which is based on maximising the ratio of the minimum squared euclidean distance of the PR target to the noise penalty introduced by the Partial Response (PR) filter. The results show that the new designed GPR targets have consistently better performance in comparison to various GPR targets previously published. Two methods of equalisation including the industry's standard PR, and a novel Soft-Feedback- Equalisation (SFE) have been discussed which are complimentary to each other. The work on SFE, which is a novelty of this work, was derived from the problem of Inter Symbol Interference (ISI) and noise colouration in PR equalisation. This work also shows that multi-level SFE with MAP/BCJR feedback based magnetic recording with ECC has similar performance when compared to high density binary PR based magnetic recording with ECC, thus documenting the benefits of multi-level magnetic recording. It has been shown that 4-level PR based magnetic recording with ECC at half the density of binary PR based magnetic recording has similar performance and higher packing density by a factor of 2. A novel technique of combining SFE and PR equalisation to achieve best ISI cancellation in a iterative fashion has been discussed. A consistent gain of 0.5 dB and more is achieved when this technique is investigated with application of Maximum Transition Run (MTR) codes. As the length of the PR target in PR equalisation increases, the gain achieved using this novel technique consistently increases and reaches up to 1.2 dB in case of EEPR4 target for a bit error rate of 10-5

An Iteratively Decodable Tensor Product Code with Application to Data Storage

The error pattern correcting code (EPCC) can be constructed to provide a syndrome decoding table targeting the dominant error events of an inter-symbol interference channel at the output of the Viterbi detector. For the size of the syndrome table to be manageable and the list of possible error events to be reasonable in size, the codeword length of EPCC needs to be short enough. However, the rate of such a short length code will be too low for hard drive applications. To accommodate the required large redundancy, it is possible to record only a highly compressed function of the parity bits of EPCC's tensor product with a symbol correcting code. In this paper, we show that the proposed tensor error-pattern correcting code (T-EPCC) is linear time encodable and also devise a low-complexity soft iterative decoding algorithm for EPCC's tensor product with q-ary LDPC (T-EPCC-qLDPC). Simulation results show that T-EPCC-qLDPC achieves almost similar performance to single-level qLDPC with a 1/2 KB sector at 50% reduction in decoding complexity. Moreover, 1 KB T-EPCC-qLDPC surpasses the performance of 1/2 KB single-level qLDPC at the same decoder complexity.Comment: Hakim Alhussien, Jaekyun Moon, "An Iteratively Decodable Tensor Product Code with Application to Data Storage