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Coding theorems for turbo code ensembles [PDF]
IEEE Transactions on Information Theory, 2002 Summary: This paper is devoted to a Shannon-theoretic study of turbo codes. We prove that ensembles of parallel and serial turbo codes are good in the following sense. For a turbo code ensemble defined by a fixed set of component codes (subject only to mild necessary restrictions), there exists a positive number \(\gamma_0\) such that for any binary ...
R J Mceliece
exaly +4 more sources
Electronics (Switzerland), 2020 This paper proposes, for the first time, a two-source asymmetric turbo-coded-cooperative spatial modulation (SM) scheme over the slow Rayleigh fading channel. As in any coded cooperative communication, the interleaver plays a vital role in mitigating the
Rahim Umar, Shoaib Mughal
exaly +2 more sources
Separate Turbo Code and Single Turbo Code Adaptive OFDM Transmissions
EURASIP Journal on Wireless Communications and Networking, 2009 This paper discusses the application of adaptive modulation and adaptive rate turbo coding to orthogonal frequency-division multiplexing (OFDM), to increase throughput on the time and frequency selective channel.
Lei Ye, Alister Burr
doaj +3 more sources
VeriGen: A Large Language Model for Verilog Code Generation [PDF]
ACM Trans. Design Autom. Electr. Syst., 2023 In this study, we explore the capability of Large Language Models (LLMs) to automate hardware design by automatically completing partial Verilog code, a common language for designing and modeling digital systems. We fine-tune pre-existing LLMs on Verilog
Shailja Thakur +6 more
semanticscholar +1 more source
Structured Chain-of-Thought Prompting for Code Generation [PDF]
ACM Transactions on Software Engineering and Methodology, 2023 Large Language Models (LLMs) have shown impressive abilities in code generation. Chain-of-Thought (CoT) prompting is the state-of-the-art approach to utilizing LLMs.
Jia Li, Ge Li, Yongming Li, Zhi Jin
semanticscholar +1 more source
Using an LLM to Help with Code Understanding [PDF]
International Conference on Software Engineering, 2023 Understanding code is challenging, especially when working in new and complex development environments. Code comments and documentation can help, but are typically scarce or hard to navigate.
Daye Nam +4 more
semanticscholar +1 more source
Bias Testing and Mitigation in LLM-based Code Generation [PDF]
ACM Transactions on Software Engineering and Methodology, 2023 As the adoption of LLMs becomes more widespread in software coding ecosystems, a pressing issue has emerged: does the generated code contain social bias and unfairness, such as those related to age, gender, and race?
Dong Huang +5 more
semanticscholar +1 more source
Turbo Equalization With Irregular Turbo Codes [PDF]
2007 4th International Symposium on Wireless Communication Systems, 2007 We analyze a turbo equalization system that combines maximum a posteriori probability (MAP) equalization with irregular turbo codes. Our goal is to approach the information capacity limit for severe inter-symbol interference (ISI) channels. To this end, we optimize the degree profile of irregular turbo codes by maximizing the minimum distance between ...
Vladimir D. Trajkovic +2 more
openaire +1 more source
The Effect Of Constraint Length And Interleaver On The Performance Of Turbo Code [PDF]
Engineering and Technology Journal, 2010 This paper presents a class derived from convolutional code called turbo code. Theperformance of turbo code is investigated through examining the effect of different constraintlength, the effect of changing rate, and the effect of interleaver on the ...
Suad A. Essa +2 more
doaj +1 more source
Near Capacity Irregular Turbo Code [PDF]
arXiv.org, 2015 The purpose of this study is to construct a near capacity Irregular Turbo Code and to evaluate its performance over Gaussian channel. The methodology used to evaluate and measure the performance of the new design is by simulating the system by developing
Abiodun O. Sholiyi +4 more
semanticscholar +1 more source