Contributions to adaptive equalization and timing recovery for optical storage systems

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The Deep Space Network

Progress on the Deep Space Network (DSN) supporting research and technology, advanced development, engineering and implementation, and DSN operations is presented. The functions and facilities of the DSN are described

Non-iterative joint decoding and signal processing: universal coding approach for channels with memory

A non-iterative receiver is proposed to achieve near capacity performance on intersymbol interference (ISI) channels. There are two main ingredients in the proposed design. i) The use of a novel BCJR-DFE equalizer which produces optimal soft estimates of the inputs to the ISI channel given all the observations from the channel and L past symbols exactly, where L is the memory of the ISI channel. ii) The use of an encoder structure that ensures that L past symbols can be used in the DFE in an error free manner through the use of a capacity achieving code for a memoryless channel. Computational complexity of the proposed receiver structure is less than that of one iteration of the turbo receiver. We also provide the proof showing that the proposed receiver achieves the i.i.d. capacity of any constrained input ISI channel. This DFE-based receiver has several advantages over an iterative (turbo) receiver, such as low complexity, the fact that codes that are optimized for memoryless channels can be used with channels with memory, and finally that the channel does not need to be known at the transmitter. The proposed coding scheme is universal in the sense that a single code of rate r; optimized for a memoryless channel, provides small error probability uniformly across all AWGN-ISI channels of i.i.d. capacity less than r: This general principle of a proposed non-iterative receiver also applies to other signal processing functions, such as timing recovery, pattern-dependent noise whiten ing, joint demodulation and decoding etc. This makes the proposed encoder and receiver structure a viable alternative to iterative signal processing. The results show significant complexity reduction and performance gain for the case of timing recovery and patter-dependent noise whitening for magnetic recording channels

Development of a Nanosatellite Software Defined Radio Communications System

Communications systems designed with application-specific integrated circuit (ASIC) technology suffer from one very significant disadvantage - the integrated circuits do not possess the ability of programmability. However, Software Defined Radio’s (SDR’s) integrated with Field Programmable Gate Arrays (FPGA) provide an opportunity to update the communication system on nanosatellites (which are physically difficult to access) due to their capability of performing signal processing in software. SDR signal processing is performed in software on reprogrammable elements such as FPGA’s. Applying this technique to nanosatellite communications systems will optimize the operations of the hardware, and increase the flexibility of the system. In this research a transceiver algorithm for a nanosatellite software defined radio communications is designed. The developed design is capable of modulation of data to transmit information and demodulation of data to receive information. The transceiver algorithm also works at different baud rates. The design implementation was successfully tested with FPGA-based hardware to demonstrate feasibility of the transceiver design with a hardware platform suitable for SDR implementation

Two dimensional signal processing for storage channels

Over the past decade, storage channels have undergone a steady increase in capacity. With the prediction of achieving 10 Tb/in2 areal density for magnetic recording channels in sight, the industry is pushing towards di erent technologies for storage channels. Heat-assisted magnetic recording, bit-patterned media, and twodimensional magnetic recording (TDMR) are cited as viable alternative technologies to meet the increasing market demand. Among these technologies, the twodimensional magnetic recording channel has the advantage of using conventional medium while relying on improvement from signal processing. Capacity approaching codes and detection methods tailored to the magnetic recording channels are the main signal processing tools used in magnetic recording. The promise is that two-dimensional signal processing will play a role in bringing about the theoretical predictions. The main challenges in TDMR media are as follows: i) the small area allocated to each bit on the media, and the sophisticated read and write processes in shingled magnetic recording devices result in signi cant amount of noise, ii) the twodimensional inter-symbol interference is intrinsic to the nature of shingled magnetic recording. Thus, a feasible two-dimensional communication system is needed to combat the errors that arise from aggressive read and write processes. In this dissertation, we present some of the work done on signal processing aspect for storage channels. We discuss i) the nano-scale model of the storage channel, ii) noise characteristics and corresponding detection strategies, iii) two-dimensional signal processing targeted at shingled magnetic recording

Advanced Modulation and Coding Technology Conference

The objectives, approach, and status of all current LeRC-sponsored industry contracts and university grants are presented. The following topics are covered: (1) the LeRC Space Communications Program, and Advanced Modulation and Coding Projects; (2) the status of four contracts for development of proof-of-concept modems; (3) modulation and coding work done under three university grants, two small business innovation research contracts, and two demonstration model hardware development contracts; and (4) technology needs and opportunities for future missions