Improved quantum algorithm for MMSE-based massive MIMO uplink detection
- PDF / 751,316 Bytes
- 17 Pages / 439.37 x 666.142 pts Page_size
- 50 Downloads / 220 Views
Improved quantum algorithm for MMSE-based massive MIMO uplink detection Fan-Xu Meng1,2 · Xu-Tao Yu1,2
· Zai-Chen Zhang2,3
Received: 2 January 2020 / Accepted: 15 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract In this paper, we propose an improved quantum algorithm for the minimum mean square error-based massive multiple-input multiple-output (MIMO) uplink. The new algorithm can reduce the dependency on the assumptions on the input vector, the channel matrix entries and the low rank of the channel matrix, which are indispensable in our previous results. Our improved quantum algorithm applies the quantum block-encoding technology, which depends on the quantum-accessible data structure. Moreover, we design an efficient algorithm for outputting classical data, which makes sure that output data can be utilized in classical devices. Both theoretically mathematical analyses and simulation realizations in massive MIMO systems confirm the applicability of the improved quantum algorithm. With desired precision, and theoretical and numerical analysis, our improved quantum algorithm can achieve a quadratic or even an exponential speedup over classical counterparts. Keywords Improved quantum algorithm · MIMO · MMSE · Classical data output · Quadratic speedup · Exponential speedup
1 Introduction As mobile access to Internet is getting faster and instant communication advances, stronger multimedia capabilities and higher transmission speed are required. Hence, groundbreaking wireless technologies are indispensable, and the fifth generation (5G) wireless technologies have started to be investigated. Massive MIMO, a promising key technology in 5G wireless communication, enlarges system capacity by increasing the
B
Xu-Tao Yu [email protected]
1
State Key Lab of Millimeter Waves, Southeast University, Nanjing 211189, China
2
Quantum Information Center of Southeast University, Nanjing 211189, China
3
National Mobile Communications Research Laboratory, Southeast University, Nanjing, China 0123456789().: V,-vol
123
267
Page 2 of 17
F.-X. Meng et al.
number of subchannels via equipping multiple antennas at both the transmitter and the receiver. A few decades ago, Marzetta pioneered the technology of massive MIMO and indicated that higher throughputs could be potentially achieved as the number of base station (BS) antennas grows without limit [1]. Then, Rusek et al. further derived the system asymptotic capacity explicitly and also discussed some prospective opportunities with the assistance of large antenna arrays [2]. As more in-depth research on massive MIMO is being conducted, it has shown that significant performance improvements can be obtained in terms of coverage, data rate, link reliability, spectral efficiency and energy efficiency [3–6]. Nevertheless, the advantages of massive MIMO systems come at the cost of excessively high computational complexity as the number of antennas increases significantly. Among the most challenging issues is low-complexity signal detection
Data Loading...
