Partitioned Successive-Cancellation List Decoding of Polar Codes - PowerPoint PPT Presentation

Partitioned Successive-Cancellation List Decoding of Polar Codes Seyyed Ali Hashemi ⋆ , Alexios Balatsoukas-Stimming † , Pascal Giard ⋆ , Claude Thibeault ⋄ , Warren J. Gross ⋆ ⋆ McGill University, Montr´ eal, Qu´ ebec, Canada † ´ Ecole polytechnique f´ ed´ erale de Lausanne, Lausanne, Switzerland ⋄ ´ Ecole de technologie sup´ erieure, Montr´ eal, Qu´ ebec, Canada March 23, 2016 1/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 1 / 14

Motivation What is the problem? Polar codes are state-of-the-art codes with interesting properties Successive-Cancellation List (SCL) decoding can outperform LDPC codes SCL requires large amount of memory High memory requirement translates into high area occupation In this talk: We reduce the memory usage of SCL and improve its performance! 2/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 2 / 14

Background Polar Codes First family of codes which can provably achieve the channel capacity with explicit construction and low-complexity decoding 1 The encoding process consists of recursive application of a linear � 1 0 � to get the generator matrix G ⊗ n transformation of G = 1 1 The channels are then sorted as being either good or bad As the number of channels increases, the fraction of good channels tends to the channel capacity Different decoding schemes are available: Successive-Cancellation (SC) SC List 1E. Arıkan, ”Channel polarization: A method for constructing capacity achieving codes for symmetric binary input memoryless channels,” Information Theory, IEEE Transactions on , vol. 55, no. 7, pp. 3051-3073, July 2009. 3/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 3 / 14

Background Polar Encoding x 0 0 x 1 0 x 2 0 u 3 x 3 x 4 0 u 5 x 5 u 6 x 6 u 7 x 7 ���� ���� � �� � � �� � level 0 1 2 3 For a rate K N code P ( N , K ), the K best channels are found and the information bits are assigned to those channels The N − K worse channels are set to a predefined value (usually 0). These are called frozen bits F 4/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 4 / 14

Background Successive-Cancellation Decoding level 3 α β 2 β r α l α r β l 1 0 α l [ i ] =sgn( α [ i ])sgn( α [ i + 2 s − 1 ]) min( | α [ i ] | , | α [ i + 2 s − 1 ] | ), α r [ i ] = α [ i + 2 s − 1 ] + (1 − 2 β l [ i ]) α [ i ], � i < 2 s − 1 β l [ i ] ⊕ β r [ i ] , if β [ i ] = β r [ i + 2 s − 1 ] , otherwise , 5/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 5 / 14

Background SC List Decoding SC decoding � 0 , if i ∈ F or α i ≥ 0 , ˆ u i = 1 , otherwise . SCL decoding � 0 , if i ∈ F u l ˆ i = 0 or 1 , otherwise . � � � �� PM l i = 1 u l α l if ˆ 1 − sgn i − 1 , , PM l 2 i i = PM l i − 1 + | α l i | , otherwise , Cyclic Redundancy Check (CRC) code can be used to help SCL find the correct candidate 6/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 6 / 14

Proposed Algorithm Partitioned SCL Decoding The decoder tree is broken into partitions (subtrees) SCL decoding is performed only on the partitions Standard SC rules are applied to the remainder of the decoding tree Each partition outputs a single candidate codeword which is selected with the help of a CRC and then sent to the next partition The decoding process starts with the standard SC update rules The decoder does not require memory to store L entire trees of internal LLRs Only L copies of the partitions on which SCL decoding is performed are stored 7/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 7 / 14

Proposed Algorithm Partitioned SCL Decoding level n β α l r α β l r n − 1 CRC-aided CRC-aided SCL SCL level n α β n − 1 β r α l α r β l n − 2 CRC-aided CRC-aided CRC-aided CRC-aided SCL SCL SCL SCL 8/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 8 / 14

Proposed Algorithm Memory Requirements M SC = (2 N − 1) Q α + N − 1 , � �� � � �� � β (partial sums) α (LLR values) M SCL = ( N + ( N − 1) L ) Q α + + (2 N − 1) L LQ PM , � �� � � �� � � �� � path metrics α (LLR values) β (partial sums) � N � P − 1 � � N � M PSCL = 2 k + 2 P − 1 − 1 + L Q α LQ PM � �� � k =0 path metrics � �� � α (LLR values) � N P − 2 � N � + 2 k + 2 P − 2 − 1 L k =1 � �� � β (partial sums) 9/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 9 / 14

Proposed Algorithm Memory Requirements · 10 5 1 . 5 PSCL2 PSCL4 PSCL8 SC Bound Memory Bits SCL2 Bound 1 SCL4 Bound SCL8 Bound 0 . 5 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 2 10 2 11 Number of Partitions 10/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 10 / 14

Results Performance Results P (2048 , 1024) 10 0 10 − 1 10 − 1 10 − 2 10 − 2 10 − 3 FER BER 10 − 3 10 − 4 10 − 4 10 − 5 10 − 6 10 − 5 10 − 7 10 − 6 1 2 3 1 2 3 E b / N 0 [dB] E b / N 0 [dB] SC SCL2-CRC32 SCL4-CRC32 PSCL(2 , 2)-CRC16 PSCL(4 , 2)-CRC8 PSCL(4 , 4)-CRC8 11/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 11 / 14

Results Implementation Results P (2048 , 1024) Total (mm 2 ) Memory (mm 2 ) Algorithm SC 0 . 723 0 . 413 SCL2-CRC32 1 . 563 0 . 702 SCL4-CRC32 3 . 075 1 . 214 PSCL(2 , 2)-CRC16 1 . 189 0 . 540 PSCL(4 , 2)-CRC8 0 . 909 0 . 415 PSCL(4 , 4)-CRC8 1 . 356 0 . 543 12/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 12 / 14

Conclusions Conclusions We proposed a novel PSCL decoding algorithm for polar codes The code is broken into partitions and each partition is decoded with a CRC-aided SCL decoder The memory requirements of PSCL decoder is significantly smaller than that of an SCL decoder At equivalent error-correction performance, PSCL leads to memory and total area savings of 41% and 42% compared to a similar SCL decoder implementation PSCL enables a coding gain of approximately 0 . 25 dB at a BER of 10 − 5 while occupying 13% less total area than the SCL decoder In short: PSCL achieves better performance and reduces memory usage at the same time! 13/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 13 / 14

Thank you! 14/14 Seyyed Ali Hashemi (McGill) PSCL Decoding of Polar Codes ICASSP 2016 14 / 14