533 research outputs found
On Path Memory in List Successive Cancellation Decoder of Polar Codes
Polar code is a breakthrough in coding theory. Using list successive
cancellation decoding with large list size L, polar codes can achieve excellent
error correction performance. The L partial decoded vectors are stored in the
path memory and updated according to the results of list management. In the
state-of-the-art designs, the memories are implemented with registers and a
large crossbar is used for copying the partial decoded vectors from one block
of memory to another during the update. The architectures are quite area-costly
when the code length and list size are large. To solve this problem, we propose
two optimization schemes for the path memory in this work. First, a folded path
memory architecture is presented to reduce the area cost. Second, we show a
scheme that the path memory can be totally removed from the architecture.
Experimental results show that these schemes effectively reduce the area of
path memory.Comment: 5 pages, 6 figures, 2 table
Low Complexity Belief Propagation Polar Code Decoders
Since its invention, polar code has received a lot of attention because of
its capacity-achieving performance and low encoding and decoding complexity.
Successive cancellation decoding (SCD) and belief propagation decoding (BPD)
are two of the most popular approaches for decoding polar codes. SCD is able to
achieve good error-correcting performance and is less computationally expensive
as compared to BPD. However SCDs suffer from long latency and low throughput
due to the serial nature of the successive cancellation algorithm. BPD is
parallel in nature and hence is more attractive for high throughput
applications. However since it is iterative in nature, the required latency and
energy dissipation increases linearly with the number of iterations. In this
work, we borrow the idea of SCD and propose a novel scheme based on
sub-factor-graph freezing to reduce the average number of computations as well
as the average number of iterations required by BPD, which directly translates
into lower latency and energy dissipation. Simulation results show that the
proposed scheme has no performance degradation and achieves significant
reduction in computation complexity over the existing methods.Comment: 6 page
The Performance on a Computerized Attention Assessment System between Children with and without Learning Disabilities
AbstractAttention is an essential function for children's learning. Cancellation tasks are one of most popular tools used for the assessment of visuospatial attention. A computerized cancellation test system was developed to investigate whether the children with or without learning disabilities (LD) would have different performances on cancellation tasks. The result showed that group differences regarding task performance are all significant and independent from types of stimulus and layout. Post hoc analysis of between-group effects showed that the control group had more correct responses (F = 28.177, p < .001), and spent less time (F = 5.592, p = .021) than the LD group
An Implementation of List Successive Cancellation Decoder with Large List Size for Polar Codes
Polar codes are the first class of forward error correction (FEC) codes with
a provably capacity-achieving capability. Using list successive cancellation
decoding (LSCD) with a large list size, the error correction performance of
polar codes exceeds other well-known FEC codes. However, the hardware
complexity of LSCD rapidly increases with the list size, which incurs high
usage of the resources on the field programmable gate array (FPGA) and
significantly impedes the practical deployment of polar codes. To alleviate the
high complexity, in this paper, two low-complexity decoding schemes and the
corresponding architectures for LSCD targeting FPGA implementation are
proposed. The architecture is implemented in an Altera Stratix V FPGA.
Measurement results show that, even with a list size of 32, the architecture is
able to decode a codeword of 4096-bit polar code within 150 us, achieving a
throughput of 27MbpsComment: 4 pages, 4 figures, 4 tables, Published in 27th International
Conference on Field Programmable Logic and Applications (FPL), 201
A Two-staged Adaptive Successive Cancellation List Decoding for Polar Codes
Polar codes achieve outstanding error correction performance when using
successive cancellation list (SCL) decoding with cyclic redundancy check. A
larger list size brings better decoding performance and is essential for
practical applications such as 5G communication networks. However, the decoding
speed of SCL decreases with increased list size. Adaptive SCL (ASCL) decoding
can greatly enhance the decoding speed, but the decoding latency for each
codeword is different so A-SCL is not a good choice for hardware-based
applications. In this paper, a hardware-friendly two-staged adaptive SCL
(TA-SCL) decoding algorithm is proposed such that a constant input data rate is
supported even if the list size for each codeword is different. A mathematical
model based on Markov chain is derived to explore the bounds of its decoding
performance. Simulation results show that the throughput of TA-SCL is tripled
for good channel conditions with negligible performance degradation and
hardware overhead.Comment: 5 pages, 7 figures, 1 table. Accepted by ISCAS 201
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