33,295 research outputs found
On the Use of Suffix Arrays for Memory-Efficient Lempel-Ziv Data Compression
Much research has been devoted to optimizing algorithms of the Lempel-Ziv
(LZ) 77 family, both in terms of speed and memory requirements. Binary search
trees and suffix trees (ST) are data structures that have been often used for
this purpose, as they allow fast searches at the expense of memory usage.
In recent years, there has been interest on suffix arrays (SA), due to their
simplicity and low memory requirements. One key issue is that an SA can solve
the sub-string problem almost as efficiently as an ST, using less memory. This
paper proposes two new SA-based algorithms for LZ encoding, which require no
modifications on the decoder side. Experimental results on standard benchmarks
show that our algorithms, though not faster, use 3 to 5 times less memory than
the ST counterparts. Another important feature of our SA-based algorithms is
that the amount of memory is independent of the text to search, thus the memory
that has to be allocated can be defined a priori. These features of low and
predictable memory requirements are of the utmost importance in several
scenarios, such as embedded systems, where memory is at a premium and speed is
not critical. Finally, we point out that the new algorithms are general, in the
sense that they are adequate for applications other than LZ compression, such
as text retrieval and forward/backward sub-string search.Comment: 10 pages, submited to IEEE - Data Compression Conference 200
Rate-Flexible Fast Polar Decoders
Polar codes have gained extensive attention during the past few years and
recently they have been selected for the next generation of wireless
communications standards (5G). Successive-cancellation-based (SC-based)
decoders, such as SC list (SCL) and SC flip (SCF), provide a reasonable error
performance for polar codes at the cost of low decoding speed. Fast SC-based
decoders, such as Fast-SSC, Fast-SSCL, and Fast-SSCF, identify the special
constituent codes in a polar code graph off-line, produce a list of operations,
store the list in memory, and feed the list to the decoder to decode the
constituent codes in order efficiently, thus increasing the decoding speed.
However, the list of operations is dependent on the code rate and as the rate
changes, a new list is produced, making fast SC-based decoders not
rate-flexible. In this paper, we propose a completely rate-flexible fast
SC-based decoder by creating the list of operations directly in hardware, with
low implementation complexity. We further propose a hardware architecture
implementing the proposed method and show that the area occupation of the
rate-flexible fast SC-based decoder in this paper is only of the total
area of the memory-based base-line decoder when 5G code rates are supported
On the Convergence Speed of Turbo Demodulation with Turbo Decoding
Iterative processing is widely adopted nowadays in modern wireless receivers
for advanced channel codes like turbo and LDPC codes. Extension of this
principle with an additional iterative feedback loop to the demapping function
has proven to provide substantial error performance gain. However, the adoption
of iterative demodulation with turbo decoding is constrained by the additional
implied implementation complexity, heavily impacting latency and power
consumption. In this paper, we analyze the convergence speed of these combined
two iterative processes in order to determine the exact required number of
iterations at each level. Extrinsic information transfer (EXIT) charts are used
for a thorough analysis at different modulation orders and code rates. An
original iteration scheduling is proposed reducing two demapping iterations
with reasonable performance loss of less than 0.15 dB. Analyzing and
normalizing the computational and memory access complexity, which directly
impact latency and power consumption, demonstrates the considerable gains of
the proposed scheduling and the promising contributions of the proposed
analysis.Comment: Submitted to IEEE Transactions on Signal Processing on April 27, 201
Flexible and Low-Complexity Encoding and Decoding of Systematic Polar Codes
In this work, we present hardware and software implementations of flexible
polar systematic encoders and decoders. The proposed implementations operate on
polar codes of any length less than a maximum and of any rate. We describe the
low-complexity, highly parallel, and flexible systematic-encoding algorithm
that we use and prove its correctness. Our hardware implementation results show
that the overhead of adding code rate and length flexibility is little, and the
impact on operation latency minor compared to code-specific versions. Finally,
the flexible software encoder and decoder implementations are also shown to be
able to maintain high throughput and low latency.Comment: Submitted to IEEE Transactions on Communications, 201
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