Increasing the Information Density of Storage Systems Using the Precision-Resolution Paradigm

Arguably, the most prominent constrained system in storage applications is the (d, k)-RLL (Run-Length Limited) system, where every binary sequence obeys the constraint that every two adjacent 1's are separated by at least d consecutive 0's and at most k consecutive 0's, namely, runs of 0's are length limited. The motivation for the RLL constraint arises mainly from the physical limitations of the read and write technologies in magnetic and optical storage systems. We revisit the rationale for the RLL system and reevaluate its relationship to the physical media. As a result, we introduce a new paradigm that better matches the physical constraints. We call the new paradigm the Precision-Resolution (PR) system, where the write operation is limited by precision and the read operation is limited by resolution. We compute the capacity of a general PR system and demonstrate that it provides a significant increase in the information density compared to the traditional RLL system (for identical physical limitations). For example, the capacity of the (2, 10)-RLL used in CD-ROMs and DVDs is approximately 0.5418, while our PR system provides the capacity of about 0.7725, resulting in a potential increase of about 40% in information density

An RLL code design that maximises channel utilisation

Comprehensive (d,k) sequences study is presented, complemented with the design of a new, efficient, Run-Length Limited (RLL) code. The new code belongs to group of constrained coding schemas with a coding rate of R = 2/5 and with the minimum run length between two successive transitions equal to 4. Presented RLL (4, oo) code uses channel capacity highly efficiently, with 98.7% and consequently it achieves a high-density rate of DR = 2.0. It is implying that two bits can be recorded, or transmitted with one transition. Coding techniques based on the presented constraints and the selected coding rate have better efficiency than many other currently used codes for high density optical recording and transmission

On row-by-row coding for 2-D constraints

A constant-rate encoder--decoder pair is presented for a fairly large family of two-dimensional (2-D) constraints. Encoding and decoding is done in a row-by-row manner, and is sliding-block decodable. Essentially, the 2-D constraint is turned into a set of independent and relatively simple one-dimensional (1-D) constraints; this is done by dividing the array into fixed-width vertical strips. Each row in the strip is seen as a symbol, and a graph presentation of the respective 1-D constraint is constructed. The maxentropic stationary Markov chain on this graph is next considered: a perturbed version of the corresponding probability distribution on the edges of the graph is used in order to build an encoder which operates in parallel on the strips. This perturbation is found by means of a network flow, with upper and lower bounds on the flow through the edges. A key part of the encoder is an enumerative coder for constant-weight binary words. A fast realization of this coder is shown, using floating-point arithmetic

On the Capacity of the Precision-Resolution System

Arguably, the most prominent constrained system in storage applications is the (d,k)-run-length limited (RLL) system, where every binary sequence obeys the constraint that every two adjacent 1's are separated by at least d consecutive 0's and at most k consecutive 0's, namely, runs of 0's are length limited. The motivation for the RLL constraint arises mainly from the physical limitations of the read and write technologies in magnetic and optical storage systems. We revisit the rationale for the RLL system, reevaluate its relationship to the constraints of the physical media and propose a new framework that we call the Precision-Resolution (PR) system. Specifically, in the PR system there is a separation between the encoder constraints (which relate to the precision of writing information into the physical media) and the decoder constraints (which relate to its resolution, namely, the ability to distinguish between two different signals received by reading the physical media). We compute the capacity of a general PR system and compare it to the traditional RLL system

Multilevel sequences and line codes

M.Ing. (Electrical Engineering)As the demand for high-speed data communications over conventional channels such as coaxial cables and twisted pairs grows, it becomes neccesary to optimize every aspect of the communication system at reasonable cost to meet this demand effectively. The choice of a line code is one of the most important aspects in the design of a communications system, as the line code determines the complexity, and thus also the cost, of several circuits in the system. It has become known in recent years that a multilevel line code is preferable to a binary code in cases where high-speed communications are desired. Apart from ternary codes, not many multilevel codes are available. Some of the existing line codes also suffer from serious drawbacks regarding a lack of complying to input restrictions, small values of efficiency, and great code complexity. In this study, Markov models and values of channel capacity are presented for several classes of restricted multilevel sequences which are thought to be of practical importance in view of the channel input restrictions that these codes satisfy. Different coding methods are used to construct low-complexity encoders and decoders for generating and decoding these sequences with high values of efficiency, good error behaviour and favourable power spectral densitie