Minsung Kim will present his General Exam on January 14, 2019 at 3pm in CS 402.

The members of his committee are as follows: Kyle Jamieson (adviser), Jennifer Rexford, and Andrew Houck (ELE).  

Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so.  His abstract and reading list follow below.

Abstract : User demand for increasing amounts of wireless capacity continues to outpace supply, and so to meet this demand, significant progress has been made in new MIMO wireless physical layer techniques. Higher-performance systems now remain impractical largely because their algorithms are extremely computationally demanding. For optimal performance, an amount of computation that increases at an exponential rate both with the number of users and with the data rate of each user is often required. The base station's computational capacity is thus becoming the limiting factor on wireless capacity. QuAMax is the first large MIMO wireless base station design that addresses this issue with a fundamentally different type of computation called quantum annealing. QuAMax solves computationally-demanding MIMO maximum likelihood signal detector. We argue that using quantum computing assisted technology in the future could hold the potential to overcome computational limits of digital electronics on the number of mobile users that a MIMO base station with a particular number of antennas could effectively serve. We have implemented QuAMax on the 2,031 qubit D-Wave 2000Q quantum annealer, the state-of-art of the field. Our experimental results evaluate that implementation on real and synthetic MIMO channel traces, showing under what conditions the quantum annealer can maintain optimal maximum likelihood performance for 30 user, 30 AP antenna QPSK communication, or 60 user, 60 AP antenna BPSK communication. Our work paves the way for quantum hardware and software to significantly expand the performance envelope of Massive MIMO.

Reading list :

[1] King, Andrew D and McGeoch, Catherine C. "Algorithm engineering for a quantum annealing platform." arXiv preprint arXiv:1410.2628 (2014)

[2] E. D. Dahl. "Programming with D-Wave: Map Coloring Problem." D-Wave whitepaper (2013)

[3] Perdomo-Ortiz, Alejandro, et al. "A performance estimator for quantum annealers: Gauge selection and parameter setting." arXiv preprint arXiv:1503.01083 (2015).

[4] King, James, et al. "Benchmarking a quantum annealing processor with the time-to-target metric." arXiv preprint arXiv:1508.05087 (2015).

[5] Venturelli, Davide, and Alexei Kondratyev. "Reverse quantum annealing approach to portfolio optimization problems." arXiv preprint arXiv:1810.08584 (2018).

[6] Halperin, Daniel, et al. "802.11 with multiple antennas for dummies." ACM SIGCOMM Computer Communication Review 40.1 (2010)

[7] Chan, Albert M., and Inkyu Lee. "A new reduced-complexity sphere decoder for multiple antenna systems." Communications, 2002. ICC 2002. IEEE International Conference on. Vol. 1. IEEE, 2002.

[8] Nikitopoulos, Konstantinos, et al. "Geosphere: Consistently turning MIMO capacity into throughput." ACM SIGCOMM Computer Communication Review. Vol. 44. No. 4. ACM, 2014.

[9] Barbero, Luis G., and John S. Thompson. "Fixing the complexity of the sphere decoder for MIMO detection." IEEE Transactions on Wireless Communications 7.6 (2008).

[10] Abari, Omid, et al. "Enabling High-Quality Untethered Virtual Reality." NSDI. 2017.