Towards quantum belief propagation for LDPC decoding in wireless networks

We present Quantum Belief Propagation (QBP), a Quantum Annealing (QA) based decoder design for Low Density Parity Check (LDPC) error control codes, which have found many useful applications in Wi-Fi, satellite communications, mobile cellular systems, and data storage systems. QBP reduces the LDPC decoding to a discrete optimization problem, then embeds that reduced design onto quantum annealing hardware. QBP's embedding design can support LDPC codes of block length up to 420 bits on real state-of-the-art QA hardware with 2,048 qubits. We evaluate performance on real quantum annealer hardware, performing sensitivity analyses on a variety of parameter settings. Our design achieves a bit error rate of 10--8 in 20 μs and a 1,500 byte frame error rate of 10--6 in 50 μs at SNR 9 dB over a Gaussian noise wireless channel. Further experiments measure performance over real-world wireless channels, requiring 30 μs to achieve a 1,500 byte 99.99% frame delivery rate at SNR 15-20 dB. QBP achieves a performance improvement over an FPGA based soft belief propagation LDPC decoder, by reaching a bit error rate of 10--8 and a frame error rate of 10--6 at an SNR 2.5--3.5 dB lower. In terms of limitations, QBP currently cannot realize practical protocol-sized (e.g., Wi-Fi, WiMax) LDPC codes on current QA processors. Our further studies in this work present future cost, throughput, and QA hardware trend considerations.

[1]  Steven H. Adachi,et al.  Application of Quantum Annealing to Training of Deep Neural Networks , 2015, ArXiv.

[2]  Hiroshi Ishikawa,et al.  Higher-order clique reduction in binary graph cut , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  Alán Aspuru-Guzik,et al.  The theory of variational hybrid quantum-classical algorithms , 2015, 1509.04279.

[4]  Aidan Roy,et al.  Fast clique minor generation in Chimera qubit connectivity graphs , 2015, Quantum Inf. Process..

[5]  H. Nishimori,et al.  Quantum annealing in the transverse Ising model , 1998, cond-mat/9804280.

[6]  David J. C. MacKay,et al.  Good Error-Correcting Codes Based on Very Sparse Matrices , 1997, IEEE Trans. Inf. Theory.

[7]  Andrew Lucas,et al.  Ising formulations of many NP problems , 2013, Front. Physics.

[8]  M. W. Johnson,et al.  Quantum annealing with manufactured spins , 2011, Nature.

[9]  R. Biswas,et al.  A quantum annealing approach for fault detection and diagnosis of graph-based systems , 2014, The European Physical Journal Special Topics.

[10]  Catherine C. McGeoch Adiabatic Quantum Computation and Quantum Annealing: Theory and Practice , 2014, Adiabatic Quantum Computation and Quantum Annealing: Theory and Practice.

[11]  Emile H. L. Aarts,et al.  Simulated Annealing: Theory and Applications , 1987, Mathematics and Its Applications.

[12]  Seth Lloyd,et al.  Quantum-inspired algorithms in practice , 2019, Quantum.

[13]  Maria Schuld,et al.  Stochastic gradient descent for hybrid quantum-classical optimization , 2019, Quantum.

[14]  Robert Michael Tanner,et al.  A recursive approach to low complexity codes , 1981, IEEE Trans. Inf. Theory.

[15]  Aidan Roy,et al.  Discrete optimization using quantum annealing on sparse Ising models , 2014, Front. Phys..

[16]  Aidan Roy,et al.  Mapping Constrained Optimization Problems to Quantum Annealing with Application to Fault Diagnosis , 2016, Front. ICT.

[17]  M. Amin Searching for quantum speedup in quasistatic quantum annealers , 2015, 1503.04216.

[18]  Michael S. Berger,et al.  Cloud RAN for Mobile Networks—A Technology Overview , 2015, IEEE Communications Surveys & Tutorials.

[19]  Oana Boncalo,et al.  Design Trade‐Offs for FPGA Implementation of LDPC Decoders , 2017 .

[20]  Amir H. Banihashemi,et al.  On implementation of min-sum algorithm and its modifications for decoding low-density Parity-check (LDPC) codes , 2005, IEEE Transactions on Communications.

[21]  A. Orlitsky,et al.  Stopping sets and the girth of Tanner graphs , 2002, Proceedings IEEE International Symposium on Information Theory,.

[22]  Aidan Roy,et al.  A practical heuristic for finding graph minors , 2014, ArXiv.

[23]  Chi Wang,et al.  Quantum versus simulated annealing in wireless interference network optimization , 2016, Scientific Reports.

[24]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[25]  Toshiyuki Miyazawa,et al.  Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer , 2018, Front. Phys..

[26]  J. Christopher Beck,et al.  A Hybrid Quantum-Classical Approach to Solving Scheduling Problems , 2016, SOCS.

[27]  Daniel A. Lidar,et al.  Evidence for quantum annealing with more than one hundred qubits , 2013, Nature Physics.

[28]  J.R. Cavallaro,et al.  High Throughput, Parallel, Scalable LDPC Encoder/Decoder Architecture for OFDM Systems , 2006, 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software.

[29]  Karthikeyan Sundaresan Cloud-driven architectures for next generation small cell networks , 2013, MobiArch '13.

[30]  Cong Wang,et al.  Experimental evaluation of an adiabiatic quantum system for combinatorial optimization , 2013, CF '13.

[31]  Qing Wang,et al.  Wireless network cloud: Architecture and system requirements , 2010, IBM J. Res. Dev..

[32]  G. A. Margulis,et al.  Explicit constructions of graphs without short cycles and low density codes , 1982, Comb..

[33]  John Preskill,et al.  Quantum Computing in the NISQ era and beyond , 2018, Quantum.

[34]  David Wetherall,et al.  Tool release: gathering 802.11n traces with channel state information , 2011, CCRV.

[35]  S. Knysh,et al.  Quantum Optimization of Fully-Connected Spin Glasses , 2014, 1406.7553.

[36]  Mark W. Johnson,et al.  Observation of topological phenomena in a programmable lattice of 1,800 qubits , 2018, Nature.

[37]  Kyle Jamieson,et al.  Leveraging quantum annealing for large MIMO processing in centralized radio access networks , 2019, SIGCOMM.

[38]  Gustavo Alonso,et al.  FPGA acceleration for the frequent item problem , 2010, 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010).

[39]  D.E. Hocevar,et al.  A reduced complexity decoder architecture via layered decoding of LDPC codes , 2004, IEEE Workshop onSignal Processing Systems, 2004. SIPS 2004..

[40]  Matthias Troyer,et al.  Feedback-optimized parallel tempering Monte Carlo , 2006, cond-mat/0602085.

[41]  T. Hatsuda,et al.  Hybrid quantum annealing via molecular dynamics , 2020, Scientific reports.

[42]  Daniel A. Lidar,et al.  Solving a Higgs optimization problem with quantum annealing for machine learning , 2017, Nature.

[43]  J.M.F. Moura,et al.  Structured LDPC codes for high-density recording: large girth and low error floor , 2006, IEEE Transactions on Magnetics.

[44]  Brad Lackey A belief propagation algorithm based on domain decomposition , 2018, ArXiv.

[45]  A. Glavieux,et al.  Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[46]  Dung Viet Nguyen,et al.  Girth of the Tanner graph and error correction capability of LDPC codes , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[47]  Ryan Kastner,et al.  Parallel Programming for FPGAs , 2018, ArXiv.

[48]  Srikanth V. Krishnamurthy,et al.  FluidNet: A Flexible Cloud-Based Radio Access Network for Small Cells , 2013, IEEE/ACM Transactions on Networking.

[49]  Oscar Montiel,et al.  Quantum-Inspired Acromyrmex Evolutionary Algorithm , 2019, Scientific Reports.

[50]  Jong-Hwan Kim,et al.  Quantum-inspired evolutionary algorithm for a class of combinatorial optimization , 2002, IEEE Trans. Evol. Comput..

[51]  Robert G. Gallager,et al.  Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.

[52]  Alberto Morello,et al.  DVB-S2: The Second Generation Standard for Satellite Broad-Band Services , 2006, Proceedings of the IEEE.

[53]  Takayuki Shibasaki,et al.  Digital Annealer for High-Speed Solving of Combinatorial optimization Problems and Its Applications , 2020, 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC).

[54]  Fabián A. Chudak,et al.  The Ising model : teaching an old problem new tricks , 2010 .

[55]  T. Rolski On random discrete distributions , 1980 .

[56]  Masoud Ardakani,et al.  Efficient LLR Calculation for Non-Binary Modulations over Fading Channels , 2010, IEEE Transactions on Communications.

[57]  Robert G. Maunder,et al.  A Survey of FPGA-Based LDPC Decoders , 2016, IEEE Communications Surveys & Tutorials.

[58]  D. Venturelli,et al.  Quantum Annealing Implementation of Job-Shop Scheduling , 2015, 1506.08479.

[59]  Martin Leib,et al.  Solving Quantum Chemistry Problems with a D-Wave Quantum Annealer , 2018, QTOP@NetSys.