Block Markov Encoding & Decoding
نویسنده
چکیده
Various Markov encoding and decoding techniques are often proposed for specific channels, e.g., the multi-access channel (MAC) with feedback, the relay channel, the MAC with cribbing encoders [1], [2], [3]. The goal of this report is to summarize the basic ideas of some block Markov coding techniques and present them using two simple channels, namely the point-to-point channel and the relay channel. Transmission using block Markov coding operates over a number of blocks. In each block, with the exception of the first or the last block, a new message is sent. However, the codeword to send at each block depends on not only “fresh” information but also “past” information from one or more previous blocks. Hence the name “Markov encoding”. The information from previous blocks can be refined information for the previous message or cooperative information for other users, etc. At the receiver, since the channel output at each block is related with messages from previous blocks, different decoding schemes have been proposed. The rest of this summary is organized as follows. Section II discusses the application of Markov coding in the point-to-point, discrete memoryless channel (DMC). Block Markov coding is unnecessarily complicated for a simple point-to-point DMC, but studying this setting allows for a simplified treatment of the scheme’s mechanics. To illustrate the benefits of block Markov coding in multi-user information theory, Section III applies block Markov coding techniques to prove an achievable rate for the relay channel. Section IV concludes the paper.
منابع مشابه
Performance analysis of the error-forecasting decoding for interleaved block codes on Gilbert-Elliott channels
This paper investigates the performance of the errorforecasting decoding for an interleaved block code on Gilbert–Elliott channels in terms of the word-error probability, which is the sum of the decoder error and failure probabilities. We derive expressions by constructing several Markov chains, starting from a two-state Markov chain of the Gilbert–Elliott channel model. The derived formulas ar...
متن کاملSpatial Coupling of Generator Matrix: A General Approach to Design of Good Codes at a Target BER
For any given short code (referred to as the basic code), block Markov superposition transmission (BMST) provides a simple way to obtain predictable extra coding gain by spatial coupling the generator matrix of the basic code. This paper presents a systematic design methodology for BMST systems to approach the channel capacity at any given target bit-error-rate (BER) of interest. To simplify th...
متن کاملOn Jointly Optimal Real-Time Encoding and Decoding Strategies in Multi-Terminal Communication Systems
We consider a communication system consisting of two encoders communicating with a single receiver over a noiseless channel. The two encoders make distinct partial observations of a discrete-time Markov source. Each encoder must encode its observations into a sequence of discrete variables. The sequence is transmitted over a noiseless channel to a receiver which attempts to reproduce the output...
متن کاملDecoding LDPC Convolutional Codes on Markov Channels
This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveal...
متن کاملComdined Turbo Block Decoding and Equalisation
In this paper, the combination of equalization and turbo decoding is studied. In the iterative decoding of a product code in block turbo coding system, the equalization process is performed within the iteration loop. The present study aims to investigate the decision feedback equalizer (DFE) incorporated in the iterative decoding. Simulation results show that the more severe the channel interfe...
متن کامل