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

Channel Detection and Decoding With Deep Learning

In this thesis, we investigate the designs of pragmatic data detectors and channel decoders with the assistance of deep learning. We focus on three emerging and fundamental research problems, including the designs of message passing algorithms for data detection in faster-than-Nyquist (FTN) signalling, soft-decision decoding algorithms for high-density parity-check codes and user identification for massive machine-type communications (mMTC). These wireless communication research problems are addressed by the employment of deep learning and an outline of the main contributions are given below. In the first part, we study a deep learning-assisted sum-product detection algorithm for FTN signalling. The proposed data detection algorithm works on a modified factor graph which concatenates a neural network function node to the variable nodes of the conventional FTN factor graph to compensate any detrimental effects that degrade the detection performance. By investigating the maximum-likelihood bit-error rate performance of a finite length coded FTN system, we show that the error performance of the proposed algorithm approaches the maximum a posterior performance, which might not be approachable by employing the sum-product algorithm on conventional FTN factor graph. After investigating the deep learning-assisted message passing algorithm for data detection, we move to the design of an efficient channel decoder. Specifically, we propose a node-classified redundant decoding algorithm based on the received sequence’s channel reliability for Bose-Chaudhuri-Hocquenghem (BCH) codes. Two preprocessing steps are proposed prior to decoding, to mitigate the unreliable information propagation and to improve the decoding performance. On top of the preprocessing, we propose a list decoding algorithm to augment the decoder’s performance. Moreover, we show that the node-classified redundant decoding algorithm can be transformed into a neural network framework, where multiplicative tuneable weights are attached to the decoding messages to optimise the decoding performance. We show that the node-classified redundant decoding algorithm provides a performance gain compared to the random redundant decoding algorithm. Additional decoding performance gain can be obtained by both the list decoding method and the neural network “learned” node-classified redundant decoding algorithm. Finally, we consider one of the practical services provided by the fifth-generation (5G) wireless communication networks, mMTC. Two separate system models for mMTC are studied. The first model assumes that low-resolution digital-to-analog converters are equipped by the devices in mMTC. The second model assumes that the devices' activities are correlated. In the first system model, two rounds of signal recoveries are performed. A neural network is employed to identify a suspicious device which is most likely to be falsely alarmed during the first round of signal recovery. The suspicious device is enforced to be inactive in the second round of signal recovery. The proposed scheme can effectively combat the interference caused by the suspicious device and thus improve the user identification performance. In the second system model, two deep learning-assisted algorithms are proposed to exploit the user activity correlation to facilitate channel estimation and user identification. We propose a deep learning modified orthogonal approximate message passing algorithm to exploit the correlation structure among devices. In addition, we propose a neural network framework that is dedicated for the user identification. More specifically, the neural network aims to minimise the missed detection probability under a pre-determined false alarm probability. The proposed algorithms substantially reduce the mean squared error between the estimate and unknown sequence, and largely improve the trade-off between the missed detection probability and the false alarm probability compared to the conventional orthogonal approximate message passing algorithm. All the aforementioned three parts of research works demonstrate that deep learning is a powerful technology in the physical layer designs of wireless communications

On Coding and Detection Techniques for Two-Dimensional Magnetic Recording

Edited version embargoed until 15.04.2020 Full version: Access restricted permanently due to 3rd party copyright restrictions. Restriction set on 15/04/2019 by AS, Doctoral CollegeThe areal density growth of magnetic recording systems is fast approaching the superparamagnetic limit for conventional magnetic disks. This is due to the increasing demand for high data storage capacity. Two-dimensional Magnetic Recording (TDMR) is a new technology aimed at increasing the areal density of magnetic recording systems beyond the limit of current disk technology using conventional disk media. However, it relies on advanced coding and signal processing techniques to achieve areal density gains. Current state of the art signal processing for TDMR channel employed iterative decoding with Low Density Parity Check (LDPC) codes, coupled with 2D equalisers and full 2D Maximum Likelihood (ML) detectors. The shortcoming of these algorithms is their computation complexity especially with regards to the ML detectors which is exponential with respect to the number of bits involved. Therefore, robust low-complexity coding, equalisation and detection algorithms are crucial for successful future deployment of the TDMR scheme. This present work is aimed at finding efficient and low-complexity coding, equalisation, detection and decoding techniques for improving the performance of TDMR channel and magnetic recording channel in general. A forward error correction (FEC) scheme of two concatenated single parity bit systems along track separated by an interleaver has been presented for channel with perpendicular magnetic recording (PMR) media. Joint detection decoding algorithm using constrained MAP detector for simultaneous detection and decoding of data with single parity bit system has been proposed. It is shown that using the proposed FEC scheme with the constrained MAP detector/decoder can achieve a gain of up to 3dB over un-coded MAP decoder for 1D interference channel. A further gain of 1.5 dB was achieved by concatenating two interleavers with extra parity bit when data density along track is high. The use of single bit parity code as a run length limited code as well as an error correction code is demonstrated to simplify detection complexity and improve system performance. A low-complexity 2D detection technique for TDMR system with Shingled Magnetic Recording Media (SMR) was also proposed. The technique used the concatenation of 2D MAP detector along track with regular MAP detector across tracks to reduce the complexity order of using full 2D detection from exponential to linear. It is shown that using this technique can improve track density with limited complexity. Two methods of FEC for TDMR channel using two single parity bit systems have been discussed. One using two concatenated single parity bits along track only, separated by a Dithered Relative Prime (DRP) interleaver and the other use the single parity bits in both directions without the DRP interleaver. Consequent to the FEC coding on the channel, a 2D multi-track MAP joint detector decoder has been proposed for simultaneous detection and decoding of the coded single parity bit data. A gain of up to 5dB was achieved using the FEC scheme with the 2D multi-track MAP joint detector decoder over un-coded 2D multi-track MAP detector in TDMR channel. In a situation with high density in both directions, it is shown that FEC coding using two concatenated single parity bits along track separated by DRP interleaver performed better than when the single parity bits are used in both directions without the DRP interleaver.9mobile Nigeri

Performance Prediction of a Turbo-coded Link in Fading Channels

Channel coding is the method of adding redundancy to the data in order to reduce the frequency of errors or to increase the capacity of a channel. Turbo codes are the most superior class of codes making achievable channel capacity almost at par with the Shannon limits. In Adaptive Modulation and Coding (AMC) the prediction of error performance of a channel is an important step before choosing one of the Modulation Coding Scheme (MCS). Since in Turbo-coded system we donot have analytical relations to relate error performance with the Signal to Noise Ratio (SNR). Therefore, normally simulation results are stored in the form of the look up tables. In this work we propose an error performance prediction model for a BPSK modulated Turbo-coded link. This model predicts performance addressing the fading phenomena for wireless radio channels. It takes the large variations in the SNR level within a code block into account along with the coding parameters. The SNR dB values profile inside a code block is considered in terms of their mean and variance. The model proposed is UMTS compliant and is continuous for values of the MCS code rate and the mean and variance of SNR dB values. It is an easier way of predicting link level performance as it replaces the discrete look up tables. Unlike the look-up tables it can be used for differentiation based analytical techniques used in system level optimization

Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems

Nach einer Einleitung behandelt Teil 2 Mehrbenutzer-Scheduling für die Abwärtsstrecke von drahtlosen MIMO Systemen mit einer Sendestation und kanaladaptivem precoding: In jeder Zeit- oder Frequenzressource kann eine andere Nutzergruppe gleichzeitig bedient werden, räumlich getrennt durch unterschiedliche Antennengewichte. Nutzer mit korrelierten Kanälen sollten nicht gleichzeitig bedient werden, da dies die räumliche Trennbarkeit erschwert. Die Summenrate einer Nutzermenge hängt von den Antennengewichten ab, die wiederum von der Nutzerauswahl abhängen. Zur Entkopplung des Problems schlägt diese Arbeit Metriken vor basierend auf einer geschätzten Rate mit ZF precoding. Diese lässt sich mit Hilfe von wiederholten orthogonalen Projektionen abschätzen, wodurch die Berechnung von Antennengewichten beim Scheduling entfällt. Die Ratenschätzung kann basierend auf momentanen Kanalmessungen oder auf gemittelter Kanalkenntnis berechnet werden und es können Datenraten- und Fairness-Kriterien berücksichtig werden. Effiziente Suchalgorithmen werden vorgestellt, die die gesamte Systembandbreite auf einmal bearbeiten können und zur Komplexitätsreduktion die Lösung in Zeit- und Frequenz nachführen können. Teil 3 zeigt wie mehrere Sendestationen koordiniertes Scheduling und kooperative Signalverarbeitung einsetzen können. Mittels orthogonalen Projektionen ist es möglich, Inter-Site Interferenz zu schätzen, ohne Antennengewichte berechnen zu müssen. Durch ein Konzept virtueller Nutzer kann der obige Scheduling-Ansatz auf mehrere Sendestationen und sogar Relays mit SDMA erweitert werden. Auf den benötigten Signalisierungsaufwand wird kurz eingegangen und eine Methode zur Schätzung der Summenrate eines Systems ohne Koordination besprochen. Teil4 entwickelt Optimierungen für Turbo Entzerrer. Diese Nutzen Signalkorrelation als Quelle von Redundanz. Trotzdem kann eine Kombination mit MIMO precoding sinnvoll sein, da bei Annahme realistischer Fehler in der Kanalkenntnis am Sender keine optimale Interferenzunterdrückung möglich ist. Mit Hilfe von EXIT Charts wird eine neuartige Methode zur adaptiven Nutzung von a-priori-Information zwischen Iterationen entwickelt, die die Konvergenz verbessert. Dabei wird gezeigt, wie man semi-blinde Kanalschätzung im EXIT chart berücksichtigen kann. In Computersimulationen werden alle Verfahren basierend auf 4G-Systemparametern überprüft.After an introduction, part 2 of this thesis deals with downlink multi-user scheduling for wireless MIMO systems with one transmitting station performing channel adaptive precoding:Different user subsets can be served in each time or frequency resource by separating them in space with different antenna weight vectors. Users with correlated channel matrices should not be served jointly since correlation impairs the spatial separability.The resulting sum rate for each user subset depends on the precoding weights, which in turn depend on the user subset. This thesis manages to decouple this problem by proposing a scheduling metric based on the rate with ZF precoding such as BD, written with the help of orthogonal projection matrices. It allows estimating rates without computing any antenna weights by using a repeated projection approximation.This rate estimate allows considering user rate requirements and fairness criteria and can work with either instantaneous or long term averaged channel knowledge.Search algorithms are presented to efficiently solve user grouping or selection problems jointly for the entire system bandwidth while being able to track the solution in time and frequency for complexity reduction. Part 3 shows how multiple transmitting stations can benefit from cooperative scheduling or joint signal processing. An orthogonal projection based estimate of the inter-site interference power, again without computing any antenna weights, and a virtual user concept extends the scheduling approach to cooperative base stations and finally included SDMA half-duplex relays in the scheduling.Signalling overhead is discussed and a method to estimate the sum rate without coordination. Part 4 presents optimizations for Turbo Equalizers. There, correlation between user signals can be exploited as a source of redundancy. Nevertheless a combination with transmit precoding which aims at reducing correlation can be beneficial when the channel knowledge at the transmitter contains a realistic error, leading to increased correlation. A novel method for adaptive re-use of a-priori information between is developed to increase convergence by tracking the iterations online with EXIT charts.A method is proposed to model semi-blind channel estimation updates in an EXIT chart. Computer simulations with 4G system parameters illustrate the methods using realistic channel models.Im Buchhandel erhältlich: Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems / Fuchs-Lautensack,Martin Ilmenau: ISLE, 2009,116 S. ISBN 978-3-938843-43-

Development of an acoustic communication link for micro underwater vehicles

PhD ThesisIn recent years there has been an increasing trend towards the use of Micro Remotely Operated Vehicles (μROVs), such as the Videoray and Seabotix LBV products, for a range of subsea applications, including environmental monitoring, harbour security, military surveillance and offshore inspection. A major operational limitation is the umbilical cable, which is traditionally used to supply power and communications to the vehicle. This tether has often been found to significantly restrict the agility of the vehicle or in extreme cases, result in entanglement with subsea structures. This thesis addresses the challenges associated with developing a reliable full-duplex wireless communications link aimed at tetherless operation of a μROV. Previous research has demonstrated the ability to support highly compressed video transmissions over several kilometres through shallow water channels with large range-depth ratios. However, the physical constraints of these platforms paired with the system cost requirements pose significant additional challenges. Firstly, the physical size/weight of transducers for the LF (8-16kHz) and MF (16-32kHz) bands would significantly affect the dynamics of the vehicle measuring less than 0.5m long. Therefore, this thesis explores the challenges associated with moving the operating frequency up to around 50kHz centre, along with the opportunities for increased data rate and tracking due to higher bandwidth. The typical operating radius of μROVs is less than 200m, in water < 100m deep, which gives rise to multipath channels characterised by long timespread and relatively sparse arrivals. Hence, the system must be optimised for performance in these conditions. The hardware costs of large multi-element receiver arrays are prohibitive when compared to the cost of the μROV platform. Additionally, the physical size of such arrays complicates deployment from small surface vessels. Although some recent developments in iterative equalisation and decoding structures have enhanced the performance of single element receivers, they are not found to be adequate in such channels. This work explores the optimum cost/performance trade-off in a combination of a micro beamforming array using a Bit Interleaved Coded Modulation with Iterative Decoding (BICM-ID) receiver structure. The highly dynamic nature of μROVs, with rapid acceleration/deceleration and complex thruster/wake effects, are also a significant challenge to reliable continuous communications. The thesis also explores how these effects can best be mitigated via advanced Doppler correction techniques, and adaptive coding and modulation via a simultaneous frequency multiplexed down link. In order to fully explore continuous adaptation of the transmitted signals, a real-time full-duplex communication system was constructed in hardware, utilising low cost components and a highly optimised PC based receiver structure. Rigorous testing, both in laboratory conditions and through extensive field trials, have enabled the author to explore the performance of the communication link on a vehicle carrying out typical operations and presenting a wide range of channel, noise, Doppler and transmission latency conditions. This has led to a comprehensive set of design recommendations for a reliable and cost effective link capable of continuous throughputs of >30 kbits/s