2,146 research outputs found
Complexity-Aware Scheduling for an LDPC Encoded C-RAN Uplink
Centralized Radio Access Network (C-RAN) is a new paradigm for wireless
networks that centralizes the signal processing in a computing cloud, allowing
commodity computational resources to be pooled. While C-RAN improves
utilization and efficiency, the computational load occasionally exceeds the
available resources, creating a computational outage. This paper provides a
mathematical characterization of the computational outage probability for
low-density parity check (LDPC) codes, a common class of error-correcting
codes. For tractability, a binary erasures channel is assumed. Using the
concept of density evolution, the computational demand is determined for a
given ensemble of codes as a function of the erasure probability. The analysis
reveals a trade-off: aggressively signaling at a high rate stresses the
computing pool, while conservatively backing-off the rate can avoid
computational outages. Motivated by this trade-off, an effective
computationally aware scheduling algorithm is developed that balances demands
for high throughput and low outage rates.Comment: Conference on Information Sciences and Systems (CISS) 2017, to appea
Self-concatenated code design and its application in power-efficient cooperative communications
In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions
Some Applications of Coding Theory in Computational Complexity
Error-correcting codes and related combinatorial constructs play an important
role in several recent (and old) results in computational complexity theory. In
this paper we survey results on locally-testable and locally-decodable
error-correcting codes, and their applications to complexity theory and to
cryptography.
Locally decodable codes are error-correcting codes with sub-linear time
error-correcting algorithms. They are related to private information retrieval
(a type of cryptographic protocol), and they are used in average-case
complexity and to construct ``hard-core predicates'' for one-way permutations.
Locally testable codes are error-correcting codes with sub-linear time
error-detection algorithms, and they are the combinatorial core of
probabilistically checkable proofs
Near-capacity iterative decoding of binary self-concatenated codes using soft decision demapping and 3-D EXIT charts
In this paper 3-D Extrinsic Information Transfer (EXIT) charts are used to design binary Self-Concatenated Convolutional Codes employing Iterative Decoding (SECCC-ID), exchanging extrinsic information with the soft-decision demapper to approach the channel capacity. Recursive Systematic Convolutional (RSC) codes are selected as constituent codes, an interleaver is used for randomising the extrinsic information exchange of the constituent codes, while a puncturer helps to increase the achievable bandwidth efficiency. The convergence behaviour of the decoder is analysed with the aid of bit-based 3-D EXIT charts, for accurately calculating the operating EbN0 threshold, especially when SP based soft demapper is employed. Finally, we propose an attractive system configuration, which is capable of operating within about 1 dB from the channel capacity
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