Leveraging Quantum Annealing for Large MIMO Processing in Centralized Radio Access Networks

Speaker : Kyle Jamieson
Princeton University
Date: 26/06/2019
Time: 2:00 pm - 3:00 pm
Location: Paris-Rennes Room (EIT Digital)


Conventional thinking treats the wireless channel as a given constraint, so wireless networks to date center on the problem optimizing the communication endpoints. We instead explore whether it is possible to reconfigure the environment itself to facilitate wireless communication. In this work, we instrument the environment with a large array of inexpensive antennas (LAIA) and design algorithms to configure them in real time. We design and deploy a 36-element passive array in a real indoor home environment. Experiments with this prototype show that, by reconfiguring the wireless environment, we can achieve a 24% TCP throughput improvement on average and a median improvement of 51.4% in Shannon capacity over the baseline single-antenna links. Over the baseline multi-antenna links, LAIA achieves an improvement of 12.23% to 18.95% in Shannon capacity.

User demand for increasing amounts of wireless capacity continues to outpace supply, and while 5G Massive MIMO wireless designs begin to address this, even higher-performance systems now remain impractical largely only because their algorithms are extremely computationally demanding. The base station’s computational capacity is thus becoming one of the key limiting factors on wireless capacity. I will discuss work in large MIMO centralized radio access network designs backed by quantum computation. We have implemented one such design, QuAMax, on the 2,031 qubit D-Wave 2000Q quantum annealer, the state-of-the-art in the field. Our experimental results evaluate that implementation on real and synthetic MIMO channel traces, showing that 30 ?s of compute time on the 2000Q can enable 48 user, 48 AP antenna BPSK communication at 20 dB SNR with a bit error rate of 1 ppm and a 1,500 byte frame error rate of 0.01%.