THESIS
2017
Abstract
List successive cancellation decoder (LSCD) architectures have been recently
proposed for the decoding of polar codes to achieve high decoding performance.
However the existing architectures for updating the partial sums of all the list
candidate paths scale with the code length and hence induce significant area
and delay overhead for polar codes with long code length or list size. In this
thesis, a list high performance partial-sum network (LHPPSN) is proposed
based on a folded partial-sum network (PSN) architecture of which the complexity
does not scale with the code length. A design based on replicating
units of high performance PSN and lazy copying is presented, first. Then, to
improve the area and performance, some new methods using indices copying
and management are prop...[
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List successive cancellation decoder (LSCD) architectures have been recently
proposed for the decoding of polar codes to achieve high decoding performance.
However the existing architectures for updating the partial sums of all the list
candidate paths scale with the code length and hence induce significant area
and delay overhead for polar codes with long code length or list size. In this
thesis, a list high performance partial-sum network (LHPPSN) is proposed
based on a folded partial-sum network (PSN) architecture of which the complexity
does not scale with the code length. A design based on replicating
units of high performance PSN and lazy copying is presented, first. Then, to
improve the area and performance, some new methods using indices copying
and management are proposed. In addition, by exploiting the properties of the
PSN, the complexity is further reduced by sharing the path copying logic of
the PSN. Experimental results show that the proposed LHPPSN improves the
area and delay significantly especially for long code and long list size, when
compared to the state-of-the-art LSCD architectures.
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