937 resultados para Lexicographic Codes


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The UMTS turbo encoder is composed of parallel concatenation of two Recursive Systematic Convolutional (RSC) encoders which start and end at a known state. This trellis termination directly affects the performance of turbo codes. This paper presents performance analysis of multi-point trellis termination of turbo codes which is to terminate RSC encoders at more than one point of the current frame while keeping the interleaver length the same. For long interleaver lengths, this approach provides dividing a data frame into sub-frames which can be treated as independent blocks. A novel decoding architecture using multi-point trellis termination and collision-free interleavers is presented. Collision-free interleavers are used to solve memory collision problems encountered by parallel decoding of turbo codes. The proposed parallel decoding architecture reduces the decoding delay caused by the iterative nature and forward-backward metric computations of turbo decoding algorithms. Our simulations verified that this turbo encoding and decoding scheme shows Bit Error Rate (BER) performance very close to that of the UMTS turbo coding while providing almost %50 time saving for the 2-point termination and %80 time saving for the 5-point termination.

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Turbo codes experience a significant decoding delay because of the iterative nature of the decoding algorithms, the high number of metric computations and the complexity added by the (de)interleaver. The extrinsic information is exchanged sequentially between two Soft-Input Soft-Output (SISO) decoders. Instead of this sequential process, a received frame can be divided into smaller windows to be processed in parallel. In this paper, a novel parallel processing methodology is proposed based on the previous parallel decoding techniques. A novel Contention-Free (CF) interleaver is proposed as part of the decoding architecture which allows using extrinsic Log-Likelihood Ratios (LLRs) immediately as a-priori LLRs to start the second half of the iterative turbo decoding. The simulation case studies performed in this paper show that our parallel decoding method can provide %80 time saving compared to the standard decoding and %30 time saving compared to the previous parallel decoding methods at the expense of 0.3 dB Bit Error Rate (BER) performance degradation.

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In population surveys of the exposure to medical X-rays both the frequency of examinations and the effective dose per examination are required. The use of the Swiss medical tariffication system (TARMED) for establishing the frequency of X-ray medical examinations was explored. The method was tested for radiography examinations performed in 2008 at the Lausanne University Hospital. The annual numbers of radiographies determined from the "TARMED" database are in good agreement with the figures extracted from the local RIS (Radiology Information System). The "TARMED" is a reliable and fast method for establishing the frequency of radiography examination, if we respect the context in which the "TARMED" code is used. In addition, this billing context provides most valuable information on the average number of radiographs per examination as well as the age and sex distributions. Radiographies represent the major part of X-ray examinations and are performed by about 4,000 practices and hospitals in Switzerland. Therefore this method has the potential to drastically simplify the organisation of nationwide surveys. There are still some difficulties to overcome if the method is to be used to assess the frequency of computed tomography or fluoroscopy examinations; procedures that deliver most of the radiation dose to the population. This is due to the poor specificity of "TARMED" codes concerning these modalities. However, the use of CT and fluoroscopy installations is easier to monitor using conventional survey methods since there are fewer centres. Ways to overcome the "TARMED" limitations for these two modalities are still being explored.